NLU release notes

 

NLU Version 4.2.2

  • support for Medical Summarizers

New Medical Summarizers:

  • ‘en.summarize.clinical_jsl’
  • ‘en.summarize.clinical_jsl_augmented’
  • ‘en.summarize.biomedical_pubmed’
  • ‘en.summarize.generic_jsl’
  • ‘en.summarize.clinical_questions’
  • ‘en.summarize.radiology’
  • ‘en.summarize.clinical_guidelines_large’
  • ‘en.summarize.clinical_laymen’

NLU Version 4.2.1

Bugfixes for saving and reloading pipelines on databricks

NLU Version 4.2.0

Support for Speech2Text, Images-Classification, Tabular Data, Zero-Shot-NER, via Wav2Vec2, Tapas, VIT , 4000+ New Models, 90+ Languages, in John Snow Labs NLU 4.2.0

We are incredibly excited to announce NLU 4.2.0 has been released with new 4000+ models in 90+ languages and support for new 8 Deep Learning Architectures. 4 new tasks are included for the very first time, Zero-Shot-NER, Automatic Speech Recognition, Image Classification and Table Question Answering powered by Wav2Vec 2.0, HuBERT, TAPAS, VIT, SWIN, Zero-Shot-NER.

Additionally, CamemBERT based architectures are available for Sequence and Token Classification powered by Spark-NLPs CamemBertForSequenceClassification and CamemBertForTokenClassification

Automatic Speech Recognition (ASR)

Demo Notebook Wav2Vec 2.0 and HuBERT enable ASR for the very first time in NLU. Wav2Vec2 is a transformer model for speech recognition that uses unsupervised pre-training on large amounts of unlabeled speech data to improve the accuracy of automatic speech recognition (ASR) systems. It is based on a self-supervised learning approach that learns to predict masked portions of speech signal, and has shown promising results in reducing the amount of labeled training data required for ASR tasks.

These Models are powered by Spark-NLP’s Wav2Vec2ForCTC Annotator Wav2Vec2

HuBERT models match or surpass the SOTA approaches for speech representation learning for speech recognition, generation, and compression. The Hidden-Unit BERT (HuBERT) approach was proposed for self-supervised speech representation learning, which utilizes an offline clustering step to provide aligned target labels for a BERT-like prediction loss.

These Models is powered by Spark-NLP’s HubertForCTC Annotator

HUBERT

Usage

You just need an audio-file on disk and pass the path to it or a folder of audio-files.

import nlu
# Let's download an audio file 
!wget https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/audio/samples/wavs/ngm_12484_01067234848.wav
# Let's listen to it 
from IPython.display import Audio
FILE_PATH = "ngm_12484_01067234848.wav"
asr_df = nlu.load('en.speech2text.wav2vec2.v2_base_960h').predict('ngm_12484_01067234848.wav')
asr_df
text
PEOPLE WHO DIED WHILE LIVING IN OTHER PLACES

To test out HuBERT you just need to update the parameter for load()

asr_df = nlu.load('en.speech2text.hubert').predict('ngm_12484_01067234848.wav')
asr_df

Image Classification

Demo Notebook

For the first time ever NLU introduces state-of-the-art image classifiers based on
VIT and Swin giving you access to hundreds of image classifiers for various domains.

Inspired by the Transformer scaling successes in NLP, the researchers experimented with applying a standard Transformer directly to images, with the fewest possible modifications. To do so, images are split into patches and the sequence of linear embeddings of these patches were provided as an input to a Transformer. Image patches were actually treated the same way as tokens (words) in an NLP application. Image classification models were trained in supervised fashion.

You can check Scale Vision Transformers (ViT) Beyond Hugging Face article to learn deeper how ViT works and how it is implemeted in Spark NLP. This is Powerd by Spark-NLP’s VitForImageClassification Annotator

VIT

Swin is a hierarchical Transformer whose representation is computed with Shifted windows. The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection. This hierarchical architecture has the flexibility to model at various scales and has linear computational complexity with respect to image size. These qualities of Swin Transformer make it compatible with a broad range of vision tasks This is powerd by Spark-NLP’s Swin For Image Classification Swin Transformer: Hierarchical Vision Transformer using Shifted Windows by Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo.

swin

Usage:

# Download an image
os.system('wget https://raw.githubusercontent.com/JohnSnowLabs/nlu/release/4.2.0/tests/datasets/ocr/vit/ox.jpg') 
# Load VIT model and predict on image file
vit = nlu.load('en.classify_image.base_patch16_224').predict('ox.jpg')

Lets download a folder of images and predict on it

!wget -q https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/images/images.zip
import shutil
shutil.unpack_archive("images.zip", "images", "zip")
! ls /content/images/images/

Once we have image data its easy to label it, we just pass the folder with images to nlu.predict() and NLU will return a pandas DF with one row per image detected

nlu.load('en.classify_image.base_patch16_224').predict('/content/images/images')

image_classification 1.png

To use SWIN we just update the parameter to load()

load('en.classify_image.swin.tiny').predict('/content/images/images')

Visual Table Question Answering

TapasForQuestionAnswering can load TAPAS Models with a cell selection head and optional aggregation head on top for question-answering tasks on tables (linear layers on top of the hidden-states output to compute logits and optional logits_aggregation), e.g. for SQA, WTQ or WikiSQL-supervised tasks. TAPAS is a BERT-based model specifically designed (and pre-trained) for answering questions about tabular data.

Demo Notebook

Powered by TAPAS: Weakly Supervised Table Parsing via Pre-training TAPAS

Usage:

First we need a pandas dataframe on for which we want to ask questions. The so called “context”

import pandas as pd 

context_df = pd.DataFrame({
    'name':['Donald Trump','Elon Musk'], 
    'money': ['$100,000,000','$20,000,000,000,000'], 
    'married': ['yes','no'], 
    'age' : ['75','55'] })
context_df

Then we create an array of questions

questions = [
    "Who earns less than 200,000,000?",
    "Who earns more than 200,000,000?",
    "Who earns 100,000,000?",
    "How much money has Donald Trump?",
    "Who is the youngest?",
]
questions

Now Combine the data, pass it to NLU and get answers for your questions

import nlu
# Now we combine both to a tuple and we are done! We can now pass this to the .predict() method
tapas_data  = (context_df, questions)
# Lets load a TAPAS QA model and predict on (context,question). 
# It will give us an aswer for every question in the questions array, based on the context in context_df
answers = nlu.load('en.answer_question.tapas.wtq.large_finetuned').predict(tapas_data)
answers
sentence tapas_qa_UNIQUE_aggregation tapas_qa_UNIQUE_answer tapas_qa_UNIQUE_cell_positions tapas_qa_UNIQUE_cell_scores tapas_qa_UNIQUE_origin_question
Who earns less than 200,000,000? NONE Donald Trump [0, 0] 1 Who earns less than 200,000,000?
Who earns more than 200,000,000? NONE Elon Musk [0, 1] 1 Who earns more than 200,000,000?
Who earns 100,000,000? NONE Donald Trump [0, 0] 1 Who earns 100,000,000?
How much money has Donald Trump? SUM SUM($100,000,000) [1, 0] 1 How much money has Donald Trump?
Who is the youngest? NONE Elon Musk [0, 1] 1 Who is the youngest?

Zero-Shot NER

Demo Notebook Based on John Snow Labs Enterprise-NLP ZeroShotNerModel This architecture is based on RoBertaForQuestionAnswering. Zero shot models excel at generalization, meaning that the model can accurately predict entities in very different data sets without the need to fine tune the model or train from scratch for each different domain. Even though a model trained to solve a specific problem can achieve better accuracy than a zero-shot model in this specific task, it probably won’t be be useful in a different task. That is where zero-shot models shows its usefulness by being able to achieve good results in various domains.

Usage:

We just need to load the zero-shot NER model and configure a set of entity definitions.

import nlu 
# load zero-shot ner model
enterprise_zero_shot_ner = nlu.load('en.zero_shot.ner_roberta')

# Configure entity definitions
enterprise_zero_shot_ner['zero_shot_ner'].setEntityDefinitions(
    {
        "PROBLEM": [
            "What is the disease?",
            "What is his symptom?",
            "What is her disease?",
            "What is his disease?",
            "What is the problem?",
            "What does a patient suffer",
            "What was the reason that the patient is admitted to the clinic?",
        ],
        "DRUG": [
            "Which drug?",
            "Which is the drug?",
            "What is the drug?",
            "Which drug does he use?",
            "Which drug does she use?",
            "Which drug do I use?",
            "Which drug is prescribed for a symptom?",
        ],
        "ADMISSION_DATE": ["When did patient admitted to a clinic?"],
        "PATIENT_AGE": [
            "How old is the patient?",
            "What is the gae of the patient?",
        ],
    }
)

Then we can already use this pipeline to predict labels

# Predict entities
df = enterprise_zero_shot_ner.predict(
    [
        "The doctor pescribed Majezik for my severe headache.",
        "The patient was admitted to the hospital for his colon cancer.",
        "27 years old patient was admitted to clinic on Sep 1st by Dr."+
        "X for a right-sided pleural effusion for thoracentesis.",
    ]
)
df
document entities_zero_shot entities_zero_shot_class entities_zero_shot_confidence entities_zero_shot_origin_chunk entities_zero_shot_origin_sentence
The doctor pescribed Majezik for my severe headache. Majezik DRUG 0.646716 0 0
The doctor pescribed Majezik for my severe headache. severe headache PROBLEM 0.552635 1 0
The patient was admitted to the hospital for his colon cancer. colon cancer PROBLEM 0.88985 0 0
27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. 27 years old PATIENT_AGE 0.694308 0 0
27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. Sep 1st ADMISSION_DATE 0.956461 1 0
27 years old patient was admitted to clinic on Sep 1st by Dr. X for a right-sided pleural effusion for thoracentesis. a right-sided pleural effusion for thoracentesis PROBLEM 0.500266 2 0

New Models Overview

Supported Languages are: ab, am, ar, ba, bem, bg, bn, ca, co, cs, da, de, dv, el, en, es, et, eu, fa, fi, fon, fr, fy, ga, gam, gl, gu, ha, he, hi, hr, hu, id, ig, is, it, ja, jv, kin, kn, ko, kr, ku, ky, la, lg, lo, lt, lu, luo, lv, lwt, ml, mn, mr, ms, mt, nb, nl, no, pcm, pl, pt, ro, ru, rw, sg, si, sk, sl, sq, st, su, sv, sw, swa, ta, te, th, ti, tl, tn, tr, tt, tw, uk, unk, ur, uz, vi, wo, xx, yo, yue, zh, zu

Automatic Speech Recognition Models Overview

Language NLU Reference Spark NLP Reference Annotator Class
ab ab.speech2text.wav2vec_xlsr.gpu.by_hf_test asr_xls_r_ab_test_by_hf_test_gpu Wav2Vec2ForCTC
ba ba.speech2text.wav2vec_xlsr.v2_large_300m_gpu asr_wav2vec2_large_xls_r_300m_bashkir_cv7_opt_gpu Wav2Vec2ForCTC
bem bem.speech2text.wav2vec_xlsr.v2_large_gpu.by_csikasote asr_wav2vec2_large_xlsr_bemba_gpu Wav2Vec2ForCTC
bg bg.speech2text.wav2vec_xlsr.v2_large_300m_d2_gpu asr_wav2vec2_large_xls_r_300m_d2_gpu Wav2Vec2ForCTC
ca ca.speech2text.wav2vec2.voxpopuli.v2_large_gpu asr_wav2vec2_large_100k_voxpopuli_catala_by_ccoreilly_gpu Wav2Vec2ForCTC
cs cs.speech2text.wav2vec_xlsr.v2_large.by_arampacha asr_wav2vec2_large_xlsr_czech Wav2Vec2ForCTC
da da.speech2text.wav2vec2.v2_base asr_alvenir_wav2vec2_base_nst_cv9 Wav2Vec2ForCTC
de de.speech2text.wav2vec_xlsr.v3_large.by_marcel asr_wav2vec2_large_xlsr_german_demo Wav2Vec2ForCTC
el el.speech2text.wav2vec_xlsr.v3_large_gpu.by_skylord asr_wav2vec2_large_xlsr_greek_2_gpu Wav2Vec2ForCTC
en en.speech2text.wav2vec_xlsr.v2gpu.by_bakhtullah123 asr_xlsr_training_gpu Wav2Vec2ForCTC
fa fa.speech2text.wav2vec2.v2_gpu_s117_exp asr_exp_w2v2t_pretraining_s117_gpu Wav2Vec2ForCTC
fa fa.speech2text.wav2vec_xlsr.v2_s44_exp asr_exp_w2v2t_xls_r_s44 Wav2Vec2ForCTC
fi fi.speech2text.wav2vec2.voxpopuli.v2_base asr_wav2vec2_base_10k_voxpopuli Wav2Vec2ForCTC
fi fi.speech2text.wav2vec_xlsrby_aapot asr_wav2vec2_xlsr_1b_finnish_lm_by_aapot Wav2Vec2ForCTC
fon fon.speech2text.wav2vec_xlsr asr_fonxlsr Wav2Vec2ForCTC
fr fr.speech2text.wav2vec_xlsr.v2_s800_exp asr_exp_w2v2t_xlsr_53_s800 Wav2Vec2ForCTC
gu gu.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_gpu Wav2Vec2ForCTC
hi hi.speech2text.wav2vec2.by_harveenchadha asr_hindi_model_with_lm_vakyansh Wav2Vec2ForCTC
hi hi.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_hindi_gpu Wav2Vec2ForCTC
hu hu.speech2text.wav2vec2.voxpopuli.v2_base_gpu asr_wav2vec2_base_10k_voxpopuli_gpu Wav2Vec2ForCTC
hu hu.speech2text.wav2vec_xlsr.v2_large_gpu.by_gchhablani asr_wav2vec2_large_xlsr_gpu Wav2Vec2ForCTC
id id.speech2text.wav2vec_xlsr.v2_s449_exp asr_exp_w2v2t_xlsr_53_s449 Wav2Vec2ForCTC
it it.speech2text.wav2vec2.v2_gpu_s149_vp_exp asr_exp_w2v2t_vp_100k_s149_gpu Wav2Vec2ForCTC
it it.speech2text.wav2vec_xlsr.v2_s417_exp asr_exp_w2v2t_xls_r_s417 Wav2Vec2ForCTC
ja ja.speech2text.wav2vec_xlsr.v2_large asr_wav2vec2_large_xlsr_japanese_hiragana Wav2Vec2ForCTC
ko ko.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_korean_gpu Wav2Vec2ForCTC
kr kr.speech2text.wav2vec_xlsr.v2 asr_wav2vec2_xlsr_korean_senior Wav2Vec2ForCTC
kr kr.speech2text.wav2vec_xlsr.v2_gpu asr_wav2vec2_xlsr_korean_senior_gpu Wav2Vec2ForCTC
ku ku.speech2text.wav2vec_xlsr.gpu asr_xlsr_kurmanji_kurdish_gpu Wav2Vec2ForCTC
ky ky.speech2text.wav2vec_xlsr.v2_large asr_wav2vec2_large_xlsr_53_kyrgyz Wav2Vec2ForCTC
ky ky.speech2text.wav2vec_xlsr.v2_large_gpu.by_iarfmoose asr_wav2vec2_large_xlsr_kyrgyz_by_iarfmoose_gpu Wav2Vec2ForCTC
la la.speech2text.wav2vec2.v2_base asr_wav2vec2_base_latin Wav2Vec2ForCTC
la la.speech2text.wav2vec2.v2_base_gpu asr_wav2vec2_base_latin_gpu Wav2Vec2ForCTC
lg lg.speech2text.wav2vec_xlsr.v2_multilingual_gpu asr_wav2vec2_xlsr_multilingual_56_gpu Wav2Vec2ForCTC
lt lt.speech2text.wav2vec_xlsr.v2_large_gpu.by_dundar asr_wav2vec2_large_xlsr_53_lithuanian_by_dundar_gpu Wav2Vec2ForCTC
lv lv.speech2text.wav2vec_xlsr.v2_large asr_wav2vec2_large_xlsr_53_latvian Wav2Vec2ForCTC
lv lv.speech2text.wav2vec_xlsr.v2_large_gpu.by_jimregan asr_wav2vec2_large_xlsr_latvian_gpu Wav2Vec2ForCTC
mn mn.speech2text.wav2vec_xlsr.v2_large_gpu.by_manandey asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu Wav2Vec2ForCTC
nl nl.speech2text.wav2vec_xlsr.v2_s972_exp asr_exp_w2v2t_xlsr_53_s972 Wav2Vec2ForCTC
pt pt.speech2text.wav2vec_xlsr.voxforge1.gpu.by_lgris asr_bp_voxforge1_xlsr_gpu Wav2Vec2ForCTC
ro ro.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_53_romanian_by_gmihaila_gpu Wav2Vec2ForCTC
sg sg.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_53_swiss_german_gpu Wav2Vec2ForCTC
su su.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_sundanese_gpu Wav2Vec2ForCTC
sv sv.speech2text.wav2vec_xlsr.v2_large_gpu.by_marma asr_wav2vec2_large_xlsr_swedish_gpu Wav2Vec2ForCTC
tt tt.speech2text.wav2vec_xlsr.v2_large_small asr_wav2vec2_large_xlsr_53_W2V2_TATAR_SMALL Wav2Vec2ForCTC
tw tw.speech2text.wav2vec_xlsr.v2 asr_wav2vec2large_xlsr_akan Wav2Vec2ForCTC
uz uz.speech2text.wav2vec2 asr_uzbek_stt Wav2Vec2ForCTC
vi vi.speech2text.wav2vec_xlsr.v2_large_gpu.by_not_tanh asr_wav2vec2_large_xlsr_53_vietnamese_by_not_tanh_gpu Wav2Vec2ForCTC
wo wo.speech2text.wav2vec_xlsr.v2_300m_gpu asr_av2vec2_xls_r_300m_wolof_lm_gpu Wav2Vec2ForCTC
yue yue.speech2text.wav2vec_xlsr.v2_large_gpu asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu Wav2Vec2ForCTC

Image Classification Models Overview

Language NLU Reference Spark NLP Reference Annotator Class
en en.classify_image.Check_GoodBad_Teeth image_classifier_vit_Check_GoodBad_Teeth ViTForImageClassification
en en.classify_image.Check_Gum_Teeth image_classifier_vit_Check_Gum_Teeth ViTForImageClassification
en en.classify_image.Check_Missing_Teeth image_classifier_vit_Check_Missing_Teeth ViTForImageClassification
en en.classify_image.Infrastructures image_classifier_vit_Infrastructures ViTForImageClassification
en en.classify_image.Insectodoptera image_classifier_vit_Insectodoptera ViTForImageClassification
en en.classify_image.Tomato_Leaf_Classifier image_classifier_vit_Tomato_Leaf_Classifier ViTForImageClassification
en en.classify_image.Visual_transformer_chihuahua_cookies image_classifier_vit_Visual_transformer_chihuahua_cookies ViTForImageClassification
en en.classify_image._spectrogram image_classifier_vit__spectrogram ViTForImageClassification
en en.classify_image.age_classifier image_classifier_vit_age_classifier ViTForImageClassification
en en.classify_image.airplanes image_classifier_vit_airplanes ViTForImageClassification
en en.classify_image.animal_classifier image_classifier_vit_animal_classifier ViTForImageClassification
en en.classify_image.anomaly image_classifier_vit_anomaly ViTForImageClassification
en en.classify_image.apes image_classifier_vit_apes ViTForImageClassification
en en.classify_image.autotrain_cifar10__base image_classifier_vit_autotrain_cifar10__base ViTForImageClassification
en en.classify_image.autotrain_dog_vs_food image_classifier_vit_autotrain_dog_vs_food ViTForImageClassification
en en.classify_image.baked_goods image_classifier_vit_baked_goods ViTForImageClassification
en en.classify_image.base_beans image_classifier_vit_base_beans ViTForImageClassification
en en.classify_image.base_cats_vs_dogs image_classifier_vit_base_cats_vs_dogs ViTForImageClassification
en en.classify_image.base_cifar10 image_classifier_vit_base_cifar10 ViTForImageClassification
en en.classify_image.base_food101 image_classifier_vit_base_food101 ViTForImageClassification
en en.classify_image.base_movie_scenes_v1 image_classifier_vit_base_movie_scenes_v1 ViTForImageClassification
en en.classify_image.base_mri image_classifier_vit_base_mri ViTForImageClassification
en en.classify_image.base_patch16_224 image_classifier_vit_base_patch16_224 ViTForImageClassification
en en.classify_image.base_patch16_224.by_google image_classifier_vit_base_patch16_224 ViTForImageClassification
en en.classify_image.base_patch16_224_cifar10 image_classifier_vit_base_patch16_224_cifar10 ViTForImageClassification
en en.classify_image.base_patch16_224_finetuned_eurosat image_classifier_vit_base_patch16_224_finetuned_eurosat ViTForImageClassification
en en.classify_image.base_patch16_224_finetuned_kvasirv2_colonoscopy image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy ViTForImageClassification
en en.classify_image.base_patch16_224_in21k_snacks image_classifier_vit_base_patch16_224_in21k_snacks ViTForImageClassification
en en.classify_image.base_patch16_224_in21k_ucSat image_classifier_vit_base_patch16_224_in21k_ucSat ViTForImageClassification
en en.classify_image.base_patch16_224_recylce_ft image_classifier_vit_base_patch16_224_recylce_ft ViTForImageClassification
en en.classify_image.base_patch16_384 image_classifier_vit_base_patch16_384 ViTForImageClassification
en en.classify_image.base_patch16_384.by_google image_classifier_vit_base_patch16_384 ViTForImageClassification
en en.classify_image.base_patch32_384.by_google image_classifier_vit_base_patch32_384 ViTForImageClassification
en en.classify_image.base_xray_pneumonia image_classifier_vit_base_xray_pneumonia ViTForImageClassification
en en.classify_image.baseball_stadium_foods image_classifier_vit_baseball_stadium_foods ViTForImageClassification
en en.classify_image.beer_vs_wine image_classifier_vit_beer_vs_wine ViTForImageClassification
en en.classify_image.beer_whisky_wine_detection image_classifier_vit_beer_whisky_wine_detection ViTForImageClassification
en en.classify_image.blocks image_classifier_vit_blocks ViTForImageClassification
en en.classify_image.cifar10 image_classifier_vit_cifar10 ViTForImageClassification
en en.classify_image.cifar_10_2 image_classifier_vit_cifar_10_2 ViTForImageClassification
en en.classify_image.computer_stuff image_classifier_vit_computer_stuff ViTForImageClassification
en en.classify_image.croupier_creature_classifier image_classifier_vit_croupier_creature_classifier ViTForImageClassification
en en.classify_image.deit_base_patch16_224 image_classifier_vit_deit_base_patch16_224 ViTForImageClassification
en en.classify_image.deit_base_patch16_224.by_facebook image_classifier_vit_deit_base_patch16_224 ViTForImageClassification
en en.classify_image.deit_flyswot image_classifier_vit_deit_flyswot ViTForImageClassification
en en.classify_image.deit_small_patch16_224 image_classifier_vit_deit_small_patch16_224 ViTForImageClassification
en en.classify_image.deit_small_patch16_224.by_facebook image_classifier_vit_deit_small_patch16_224 ViTForImageClassification
en en.classify_image.deit_tiny_patch16_224 image_classifier_vit_deit_tiny_patch16_224 ViTForImageClassification
en en.classify_image.deit_tiny_patch16_224.by_facebook image_classifier_vit_deit_tiny_patch16_224 ViTForImageClassification
en en.classify_image.demo image_classifier_vit_demo ViTForImageClassification
en en.classify_image.denver_nyc_paris image_classifier_vit_denver_nyc_paris ViTForImageClassification
en en.classify_image.diam image_classifier_vit_diam ViTForImageClassification
en en.classify_image.digital image_classifier_vit_digital ViTForImageClassification
en en.classify_image.dog image_classifier_vit_dog ViTForImageClassification
en en.classify_image.dog_breed_classifier image_classifier_vit_dog_breed_classifier ViTForImageClassification
en en.classify_image.dog_food__base_patch16_224_in21k image_classifier_vit_dog_food__base_patch16_224_in21k ViTForImageClassification
en en.classify_image.dog_races image_classifier_vit_dog_races ViTForImageClassification
en en.classify_image.dog_vs_chicken image_classifier_vit_dog_vs_chicken ViTForImageClassification
en en.classify_image.doggos_lol image_classifier_vit_doggos_lol ViTForImageClassification
en en.classify_image.dogs image_classifier_vit_dogs ViTForImageClassification
en en.classify_image.dwarf_goats image_classifier_vit_dwarf_goats ViTForImageClassification
en en.classify_image.electric_2 image_classifier_vit_electric_2 ViTForImageClassification
en en.classify_image.electric_pole_type_classification image_classifier_vit_electric_pole_type_classification ViTForImageClassification
en en.classify_image.ex_for_evan image_classifier_vit_ex_for_evan ViTForImageClassification
en en.classify_image.finetuned_eurosat_kornia image_classifier_vit_finetuned_eurosat_kornia ViTForImageClassification
en en.classify_image.flowers image_classifier_vit_flowers ViTForImageClassification
en en.classify_image.food image_classifier_vit_food ViTForImageClassification
en en.classify_image.fruits image_classifier_vit_fruits ViTForImageClassification
en en.classify_image.garbage_classification image_classifier_vit_garbage_classification ViTForImageClassification
en en.classify_image.grain image_classifier_vit_grain ViTForImageClassification
en en.classify_image.greens image_classifier_vit_greens ViTForImageClassification
en en.classify_image.hot_dog_or_sandwich image_classifier_vit_hot_dog_or_sandwich ViTForImageClassification
en en.classify_image.hotdog_not_hotdog image_classifier_vit_hotdog_not_hotdog ViTForImageClassification
en en.classify_image.housing_categories image_classifier_vit_housing_categories ViTForImageClassification
en en.classify_image.hugging_geese image_classifier_vit_hugging_geese ViTForImageClassification
en en.classify_image.ice_cream image_classifier_vit_ice_cream ViTForImageClassification
en en.classify_image.iiif_manuscript_ image_classifier_vit_iiif_manuscript_ ViTForImageClassification
en en.classify_image.indian_snacks image_classifier_vit_indian_snacks ViTForImageClassification
en en.classify_image.koala_panda_wombat image_classifier_vit_koala_panda_wombat ViTForImageClassification
en en.classify_image.lawn_weeds image_classifier_vit_lawn_weeds ViTForImageClassification
en en.classify_image.llama_alpaca_guanaco_vicuna image_classifier_vit_llama_alpaca_guanaco_vicuna ViTForImageClassification
en en.classify_image.llama_alpaca_snake image_classifier_vit_llama_alpaca_snake ViTForImageClassification
en en.classify_image.llama_or_potato image_classifier_vit_llama_or_potato ViTForImageClassification
en en.classify_image.llama_or_what image_classifier_vit_llama_or_what ViTForImageClassification
en en.classify_image.lotr image_classifier_vit_lotr ViTForImageClassification
en en.classify_image.lucky_model image_classifier_vit_lucky_model ViTForImageClassification
en en.classify_image.lung_cancer image_classifier_vit_lung_cancer ViTForImageClassification
en en.classify_image.mit_indoor_scenes image_classifier_vit_mit_indoor_scenes ViTForImageClassification
en en.classify_image.modelversion01 image_classifier_vit_modelversion01 ViTForImageClassification
en en.classify_image.my_bean_VIT image_classifier_vit_my_bean_VIT ViTForImageClassification
en en.classify_image.new_york_tokyo_london image_classifier_vit_new_york_tokyo_london ViTForImageClassification
en en.classify_image.occupation_prediction image_classifier_vit_occupation_prediction ViTForImageClassification
en en.classify_image.opencampus_age_detection image_classifier_vit_opencampus_age_detection ViTForImageClassification
en en.classify_image.orcs_and_friends image_classifier_vit_orcs_and_friends ViTForImageClassification
en en.classify_image.oz_fauna image_classifier_vit_oz_fauna ViTForImageClassification
en en.classify_image.pasta_pizza_ravioli image_classifier_vit_pasta_pizza_ravioli ViTForImageClassification
en en.classify_image.pasta_shapes image_classifier_vit_pasta_shapes ViTForImageClassification
en en.classify_image.places image_classifier_vit_places ViTForImageClassification
en en.classify_image.planes_airlines image_classifier_vit_planes_airlines ViTForImageClassification
en en.classify_image.planes_trains_automobiles image_classifier_vit_planes_trains_automobiles ViTForImageClassification
en en.classify_image.puppies_classify image_classifier_vit_puppies_classify ViTForImageClassification
en en.classify_image.rare_bottle image_classifier_vit_rare_bottle ViTForImageClassification
en en.classify_image.roomclassifier image_classifier_vit_roomclassifier ViTForImageClassification
en en.classify_image.rust_image_classification_1 image_classifier_vit_rust_image_classification_1 ViTForImageClassification
en en.classify_image.skin_type image_classifier_vit_skin_type ViTForImageClassification
en en.classify_image.snacks image_classifier_vit_snacks ViTForImageClassification
en en.classify_image.south_indian_foods image_classifier_vit_south_indian_foods ViTForImageClassification
en en.classify_image.string_instrument_detector image_classifier_vit_string_instrument_detector ViTForImageClassification
en en.classify_image.vc_bantai__withoutAMBI_adunest image_classifier_vit_vc_bantai__withoutAMBI_adunest ViTForImageClassification
en en.classify_image.trainer_rare_puppers image_classifier_vit_trainer_rare_puppers ViTForImageClassification
en en.classify_image.world_landmarks image_classifier_vit_world_landmarks ViTForImageClassification


NLU Version 4.1.0

Approximately 1000 new state-of-the-art transformer models for Question Answering (QA) for over 10 languages, up to 700% speedup on GPU, 100+ Embeddings such as Bert, Bert Sentence, CamemBert, DistilBert, Roberta, Roberta Sentence, Universal Sentence Encoder, Word, XLM Roberta, XLM Roberta Sentence, 40 sequence classification models, +400 token classification odels for over 10 languages various Spark NLP helper methods and much more in 1 line of code with John Snow Labs NLU 4.1.0


NLU 4.1.0 Core Overview

  • On the NLU core side we have over 1000 new state-of-the-art models in over 10 languages.

  • Additionally up to 700% speedup transformer-based Word Embeddings on GPU and up to 97% speedup on CPU for tensorflow operations, support for Apple M1 chips, Pyspark 3.2 and 3.3 support. Ontop of this, we are now supporting Apple M1 based architectures and every Pyspark 3.X version, while deprecating support for Pyspark 2.X.

  • Finally, NLU-Core features various new helper methods for working with Spark NLP and embellishes now the entire universe of Annotators defined by Spark NLP.


NLU captures every Annotator of Spark NLP

The entire universe of Annotators in Spark NLP is now embellished by NLU Components by using generalizable annotation extractors methods and configs internally to support enable the new NLU util methods. The following annotator classes are newly captured:

  • BertEmbeddings
  • BertForQuestionAnswering
  • BertForSequenceClassification
  • BertForTokenClassification
  • BertSentenceEmbeddings
  • CamemBertEmbeddings
  • ClassifierDLModel
  • ContextSpellCheckerModel
  • DistilBertEmbeddings
  • DistilBertForSequenceClassification
  • DistilBertForTokenClassification
  • LemmatizerModel
  • LongformerForTokenClassification
  • NerCrfModel
  • NerDLModel
  • PerceptronModel
  • RoBertaEmbeddings
  • RoBertaForQuestionAnswering
  • RoBertaForSequenceClassification
  • RoBertaForTokenClassification
  • RoBertaSentenceEmbeddings
  • SentenceDetectorDLModel
  • StopWordsCleaner
  • T5Transformer
  • UniversalSentenceEncoder
  • WordEmbeddingsModel
  • XlmRoBertaEmbeddings
  • XlmRoBertaForTokenClassification
  • XlmRoBertaSentenceEmbeddings

Embeddings

Embeddings provides dense vector representations for natural language by using a deep, pre-trained neural network with the Transformer architecture. On the NLU core side we have over 150 new embeddings models. We have new BertEmbeddings, BertSentenceEmbeddings, CamemBertEmbeddings, DistilBertEmbeddings, RoBertaEmbeddings, UniversalSentenceEncoder, XlmRoBertaEmbeddings, XlmRoBertaSentenceEmbeddings for in different languages.

  • German BertEmbeddings

nlu.load("de.embed.electra.base").predict("""Ich liebe Spark NLP""")

token word_embedding_electra
Ich -0.09518987685441971, -0.016133345663547516
liebe -0.07025116682052612, -0.35387516021728516
Spark -0.33390265703201294, 0.08874476701021194
NLP -0.2969835698604584, 0.1980721354484558
  • English BertEmbeddings

text = ["I love NLP"]
df = nlu.load('en.embed_sentence.bert.pubmed').predict(text, output_level='token')
df

token sentence_embedding_bert
I -0.06332794576883316, -0.5097940564155579
love -0.06332794576883316, -0.5097940564155579
NLP -0.06332794576883316, -0.5097940564155579
  • Japan BertEmbeddings

nlu.load("ja.embed.bert.base").predict("""私はSpark NLPを愛しています""")

token word_embedding_bert
私はSpark 0.3989057242870331, -0.20664098858833313
NLPを愛しています 0.05264343321323395, -0.19963961839675903
  • XLM RoBerta Embeddings MultiLanguage

text = ["I love NLP", "Me encanta usar SparkNLP"]
embeddings_df = nlu.load('xx.embed.xlmr_roberta.base_v2').predict(text, output_level='sentence')
embeddings_df

sentence word_embedding_xlmr_roberta
I love NLP -0.07450243085622787, 0.022609828040003777
Me encanta usar SparkNLP 0.0961054190993309, 0.03734250366687775
  • RoBerta Embeddings English

text = ["""I love Spark NLP"""]
embeddings_df = nlu.load('en.embed.roberta').predict(text, output_level='token')
embeddings_df

token word_embedding_roberta
I -0.06406927853822708, 0.16723069548606873
love -0.06369957327842712, 0.21014901995658875
Spark -0.1004200279712677, 0.03312099352478981
NLP -0.09467814117670059, -0.02236207202076912

Question Answering

Question Answering models can retrieve the answer to a question from a given text, which is useful for searching for an answer in a document. On the NLU core side we have over 200+ new question answering models.

  • Bert For Question Answering

nlu.load("answer_question.bert.base_uncased.by_ksabeh").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")

answer_confidence context question
0.3143375 “My name is Clara and I live in Berkeley. What is my name?

Sequence Classification

Sequence classification is the task of predicting a class label given a sequence of observations. On the NLU core side we have over 40 new sequence classification models.

  • Bert For Sequence Classification

nlu.load("classify.bert.by_mrm8488").predict("""Camera - You are awarded a SiPix Digital Camera! call 09061221066 from landline. Delivery within 28 days.""")

classified_sequence classified_sequence_confidence sentence
1 0.89954 Camera - You are awarded a SiPix Digital Camera! call 09061221066 from landline.
0 0.93745 Delivery within 28 days.
  • DistilBert For Sequence Classification

nlu.load("de.classify.distil_bert.base").predict("Natürlich kann ich von zuwanderern mehr erwarten. muss ich sogar. sie müssen die sprache lernen, sie müssen die gepflogenheiten lernen und sich in die gesellschaft einfügen. dass muss ich nicht weil ich mich schon in die gesellschaft eingefügt habe. egal wo du hin ziehst, nirgendwo wird dir soviel zucker in den arsch geblasen wie in deutschland.")

classified_sequence classified_sequence_confidence sentence
non_toxic 0.955292 Natürlich kann ich von zuwanderern mehr erwarten.
non_toxic 0.968591 muss ich sogar.
non_toxic 0.841958 sie müssen die sprache lernen, sie müssen die gepflogenheiten lernen und sich in die gesellschaft einfügen.
non_toxic 0.934119 dass muss ich nicht weil ich mich schon in die gesellschaft eingefügt habe.
non_toxic 0.771795 egal wo du hin ziehst, nirgendwo wird dir soviel zucker in den arsch geblasen wie in deutschland.
  • RoBerta For Sequence Classification

nlu.load("en.classify.roberta.finetuned").predict("I love you very much!")

classified_sequence classified_sequence_confidence sentence
LABEL_0 0.597792 I love you very much!

Lemmatizer

Lemmatization in linguistics is the process of grouping together the inflected forms of a word so they can be analysed as a single item, identified by the word’s lemma, or dictionary form. On the NLU core side we have over 30 new lemmatizer models.

ClassifierDLModel

ClassifierDL for generic Multi-class Text Classification. ClassifierDL uses the state-of-the-art Universal Sentence Encoder as an input for text classifications. The ClassifierDL annotator uses a deep learning model (DNNs) we have built inside TensorFlow and supports up to 100 classes. On the NLU core side we have over 5 new ClassifierDLModel models.

ContextSpellCheckerModel

Spell Checking is a sequence to sequence mapping problem. Given an input sequence, potentially containing a certain number of errors, ContextSpellChecker will rank correction sequences according to three things:

  1. Different correction candidates for each word — word level.
  2. The surrounding text of each word, i.e. it’s context — sentence level.
  3. The relative cost of different correction candidates according to the edit operations at the character level it requires — subword level.

On the NLU core side we have over 5 new ClassifierDLModel models.

Token Classification

Token classification is a natural language understanding task in which a label is assigned to some tokens in a text. Some popular token classification subtasks are Named Entity Recognition (NER) and Part-of-Speech (PoS) tagging. NER models could be trained to identify specific entities in a text, such as dates, individuals and places; and PoS tagging would identify, for example, which words in a text are verbs, nouns, and punctuation marks. We have new 463 models XlmRoBertaForTokenClassification, BertForTokenClassification, DistilBertForTokenClassification, DistilBertEmbeddings, LongformerForTokenClassification, RoBertaForTokenClassification for in different languages.

  • BertForTokenClassification English

nlu.load("en.ner.bc5cdr.biobert.disease").predict("I love you very much!")

index document entities_wikiner_glove_840B_300 entities_wikiner_glove_840B_300_class entities_wikiner_glove_840B_300_confidence entities_wikiner_glove_840B_300_origin_chunk entities_wikiner_glove_840B_300_origin_sentence word_embedding_glove
0 I love you very much! I love you very much! MISC 0.66433334 0 0 [ 0.19410001 0.22603001 -0.43764001 ]
  • BertForTokenClassification German

nlu.load("de.ner.distil_bert.base_cased").predict("Ich liebe Spark NLP")

index classified_token document entities_distil_bert entities_distil_bert_class entities_distil_bert_origin_chunk entities_distil_bert_origin_sentence
0 O,O,B-OTHderiv,O Ich liebe Spark NLP Spark OTHderiv 0 0
  • XlmRoBertaForTokenClassification Igbo

nlu.load("ig.ner.xlmr_roberta.base").predict("Ahụrụ m n'anya na-atọ m ụtọ")

index classified_token document entities_xlmr_roberta entities_xlmr_roberta_class entities_xlmr_roberta_origin_chunk entities_xlmr_roberta_origin_sentence
0 B-ORG,I-ORG,I-ORG,I-ORG,I-ORG,I-ORG Ahụrụ m n’anya na-atọ m ụtọ Ahụrụ m n’anya na-atọ m ụtọ ORG 0 0

NerCrfModel

This Named Entity Recognizer is based on a CRF Algorithm. Conditional random fields (CRFs) are a class of statistical modeling methods often applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label for a single sample without considering “neighbouring” samples, a CRF can take context into account. To do so, the predictions are modelled as a graphical model, which represents the presence of dependencies between the predictions. What kind of graph is used depends on the application. For example, in natural language processing, “linear chain” CRFs are popular, for which each prediction is dependent only on its immediate neighbours. In image processing, the graph typically connects locations to nearby and/or similar locations to enforce that they receive similar predictions.

  • NerCrfModel

nlu.load('en.ner.ner.crf').predict("Donald Trump and Angela Merkel dont share many oppinions")

index document entities_wikiner_glove_840B_300 entities_wikiner_glove_840B_300_class entities_wikiner_glove_840B_300_confidence entities_wikiner_glove_840B_300_origin_chunk entities_wikiner_glove_840B_300_origin_sentence word_embedding_glove
0 Donald Trump and Angela Merkel dont share many oppinions Donald Trump PER 0.78524995 0 0 [-0.074014 -0.23684999 0.17772 ]
0 Donald Trump and Angela Merkel dont share many oppinions Angela Merkel PER 0.7701 1 0 [-0.074014 -0.23684999 0.17772 ]

NerDLModel

This Named Entity recognition annotator is a generic NER model based on Neural Networks. Neural Network architecture is Char CNNs - BiLSTM - CRF that achieves state-of-the-art in most datasets. This is the instantiated model of the NerDLApproach. For training your own model, please see the documentation of that class. We have new 6 models.

  • NerDLModel Japanese

nlu.load('ja.ner.ner.base').predict("宮本茂氏は、日本の任天堂のゲームプロデューサーです。")

index document entities_xtreme_glove_840B_300 word_embedding_glove
0 宮本茂氏は、日本の任天堂のゲームプロデューサーです。 NaN [0. 0. ]
  • NerDLModel English

text = ["My name is John!"]

nlu.load('en.ner.conll.ner.large').predict(text, output_level='token')

index entities_wikiner_glove_840B_300 entities_wikiner_glove_840B_300_class entities_wikiner_glove_840B_300_confidence entities_wikiner_glove_840B_300_origin_chunk entities_wikiner_glove_840B_300_origin_sentence token word_embedding_glove
0 My name is John! MISC 0.63266003 0 0 My [-2.19990000e-01 2.57800013e-01 -4.25859988e-01 ]
0 My name is John! MISC 0.63266003 0 0 name [ 2.32309997e-01 -2.41020005e-02]
0 My name is John! MISC 0.63266003 0 0 is [-8.49609971e-02 5.01999974e-01 2.38230010e-03]
0 My name is John! MISC 0.63266003 0 0 John [-2.96090007e-01 -8.18260014e-02 9.67490021e-03 ]
0 My name is John! MISC 0.63266003 0 0 ! [-2.65540004e-01 3.35310012e-01 2.18600005e-01 ]

PerceptronModel

We have new 26 models.

StopWordsCleaner

This model removes ‘stop words’ from text. Stop words are words so common that they can be removed without significantly altering the meaning of a text. Removing stop words is useful when one wants to deal with only the most semantically important words in a text, and ignore words that are rarely semantically relevant, such as articles and prepositions. We have new 33 models.



NLU Version 4.0.0

OCR Visual Tables into Pandas DataFrames from PDF/DOC(X)/PPT files, 1000+ new state-of-the-art transformer models for Question Answering (QA) for over 30 languages, up to 700% speedup on GPU, 20 Biomedical models for over 8 languages, 50+ Terminology Code Mappers between RXNORM, NDC, UMLS,ICD10, ICDO, UMLS, SNOMED and MESH, Deidentification in Romanian, various Spark NLP helper methods and much more in 1 line of code with John Snow Labs NLU 4.0.0


NLU 4.0 for OCR Overview

On the OCR side, we now support extracting tables from PDF/DOC(X)/PPT files into structured pandas dataframe, making it easier than ever before to analyze bulks of files visually!

Checkout the OCR Tutorial for extracting Tables from Image/PDF/DOC(X) files Open In Colab to see this in action

These models grab all Table data from the files detected and return a list of Pandas DataFrames,
containing Pandas DataFrame for every table detected

NLU Spell Transformer Class
nlu.load(pdf2table) PdfToTextTable
nlu.load(ppt2table) PptToTextTable
nlu.load(doc2table) DocToTextTable

This is powerd by John Snow Labs Spark OCR Annotataors for PdfToTextTable, DocToTextTable, PptToTextTable


NLU 4.0 Core Overview

  • On the NLU core side we have over 1000+ new state-of-the-art models in over 30 languages for modern extractive transformer-based Question Answering problems powerd by the ALBERT/BERT/DistilBERT/DeBERTa/RoBERTa/Longformer Spark NLP Annotators trained on various SQUAD-like QA datasets for domains like Twitter, Tech, News, Biomedical COVID-19 and in various model subflavors like sci_bert, electra, mini_lm, covid_bert, bio_bert, indo_bert, muril, sapbert, bioformer, link_bert, mac_bert

  • Additionally up to 700% speedup transformer-based Word Embeddings on GPU and up to 97% speedup on CPU for tensorflow operations, support for Apple M1 chips, Pyspark 3.2 and 3.3 support. Ontop of this, we are now supporting Apple M1 based architectures and every Pyspark 3.X version, while deprecating support for Pyspark 2.X.

  • Finally, NLU-Core features various new helper methods for working with Spark NLP and embellishes now the entire universe of Annotators defined by Spark NLP and Spark NLP for healthcare.


NLU 4.0 for Healthcare Overview

  • On the healthcare side NLU features 20 Biomedical models for over 8 languages (English, French, Italian, Portuguese, Romanian, Catalan and Galician) detect entities like HUMAN and SPECIES based on LivingNER corpus

  • Romanian models for Deidentification and extracting Medical entities like MeasurementsFormSymptomRouteProcedureDisease_Syndrome_DisorderScoreDrug_IngredientPulseFrequencyDateBody_PartDrug_Brand_NameTimeDirectionDosageMedical_DeviceImaging_TechniqueTestImaging_FindingsImaging_TestTest_ResultWeightClinical_Dept and Units with SPELL and SPELL respectively

  • English NER models for parsing entities in Clinical Trial Abstracts like Age, AllocationRatio, Author, BioAndMedicalUnit, CTAnalysisApproach, CTDesign, Confidence, Country, DisorderOrSyndrome, DoseValue, Drug, DrugTime, Duration, Journal, NumberPatients, PMID, PValue, PercentagePatients, PublicationYear, TimePoint, Value using en.med_ner.clinical_trials_abstracts.pipe and also Pathogen NER models for PathogenMedicalConditionMedicine with en.med_ner.pathogen and GENE_PROTEIN with en.med_ner.biomedical_bc2gm.pipeline

  •  First Public Health Model for Emotional Stress classification It is a PHS-BERT-based model and trained with the Dreaddit dataset using en.classify.stress

  • 50 + new Entity Mappers for problems like :

    • Extract section headers in scientific articles and normalize them with en.map_entity.section_headers_normalized
    • Map medical abbreviates to their definitions with en.map_entity.abbreviation_to_definition
    • Map drugs to action and treatments with en.map_entity.drug_to_action_treatment
    • Map drug brand to their National Drug Code (NDC) with en.map_entity.drug_brand_to_ndc
    • Convert between terminologies using en.<START_TERMINOLOGY>_to_<TARGET_TERMINOLOGY>
      • This works for the terminologies rxnorm, ndc, umls, icd10cm, icdo, umls, snomed, mesh
        • snomed_to_icdo
        • snomed_to_icd10cm
        • rxnorm_to_umls
    • powerd by Spark NLP for Healthcares ChunkMapper Annotator

Extract Tables from PDF files as Pandas DataFrames

Sample PDF: Sample PDF

nlu.load('pdf2table').predict('/path/to/sample.pdf')  

Output of PDF Table OCR :

mpg cyl disp hp drat wt qsec vs am gear
21 6 160 110 3.9 2.62 16.46 0 1 4
21 6 160 110 3.9 2.875 17.02 0 1 4
22.8 4 108 93 3.85 2.32 18.61 1 1 4
21.4 6 258 110 3.08 3.215 19.44 1 0 3
18.7 8 360 175 3.15 3.44 17.02 0 0 3
13.3 8 350 245 3.73 3.84 15.41 0 0 3
19.2 8 400 175 3.08 3.845 17.05 0 0 3
27.3 4 79 66 4.08 1.935 18.9 1 1 4
26 4 120.3 91 4.43 2.14 16.7 0 1 5
30.4 4 95.1 113 3.77 1.513 16.9 1 1 5
15.8 8 351 264 4.22 3.17 14.5 0 1 5
19.7 6 145 175 3.62 2.77 15.5 0 1 5
15 8 301 335 3.54 3.57 14.6 0 1 5
21.4 4 121 109 4.11 2.78 18.6 1 1 4

Extract Tables from DOC/DOCX files as Pandas DataFrames

Sample DOCX: Sample DOCX

nlu.load('doc2table').predict('/path/to/sample.docx')  

Output of DOCX Table OCR :

Screen Reader Responses Share
JAWS 853 49%
NVDA 238 14%
Window-Eyes 214 12%
System Access 181 10%
VoiceOver 159 9%

Extract Tables from PPT files as Pandas DataFrame

Sample PPT with two tables: Sample PPT with two tables

nlu.load('ppt2table').predict('/path/to/sample.docx')  

Output of PPT Table OCR :

Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa

and

Sepal.Length Sepal.Width Petal.Length Petal.Width Species
6.7 3.3 5.7 2.5 virginica
6.7 3 5.2 2.3 virginica
6.3 2.5 5 1.9 virginica
6.5 3 5.2 2 virginica
6.2 3.4 5.4 2.3 virginica
5.9 3 5.1 1.8 virginica

Span Classifiers for question answering

Albert, Bert, DeBerta, DistilBert, LongFormer, RoBerta, XlmRoBerta based Transformer Architectures are now avaiable for question answering with almost 1000 models avaiable for 35 unique languages powerd by their corrosponding Spark NLP XXXForQuestionAnswering Annotator Classes and in various tuning and dataset flavours.

<lang>.answer_question.<domain>.<datasets>.<annotator_class><tune info>.by_<username> If multiple datasets or tune parameters are defined , they are connected with a _ .

These substrings define up the <domain> part of the NLU reference

These substrings define up the <dataset> part of the NLU reference

These substrings define up the <dataset> part of the NLU reference

These substrings define the <annotator_class> substring, if it does not map to a sparknlp annotator

These substrings define the <tune_info> substring, if it does not map to a sparknlp annotator

  • Train tweaks : multilingual,mini_lm,xtremedistiled,distilled,xtreme,augmented,zero_shot
  • Size tweaks xl, xxl, large, base, medium, base, small, tiny, cased, uncased
  • Dimension tweaks : 1024d,768d,512d,256d,128d,64d,32d

QA DataFormat

You need to use one of the Data formats below to pass context and question correctly to the model.


# use ||| to seperate question||context
data = 'What is my name?|||My name is Clara and I live in Berkeley'

# pass a tuple (question,context)
data = ('What is my name?','My name is Clara and I live in Berkeley')

# use pandas Dataframe, one column = question, one column=context
data = pd.DataFrame({
					 'question': ['What is my name?'],
					 'context': ["My name is Clara and I live in Berkely"]
					 })


# Get your answers with any of above formats 
nlu.load("en.answer_question.squadv2.deberta").predict(data)

returns :

answer answer_confidence context question
Clara 0.994931 My name is Clara and I live in Berkely What is my name?

New NLU helper Methods

You can see all features showcased in the Open In Colab notebook or on the new docs page for Spark NLP utils

nlu.viz(pipe,data)

Visualize input data with an already configured Spark NLP pipeline,
for Algorithms of type (Ner,Assertion, Relation, Resolution, Dependency)
using Spark NLP Display
Automatically infers applicable viz type and output columns to use for visualization.
Example:

# works with Pipeline, LightPipeline, PipelineModel,PretrainedPipeline List[Annotator]
ade_pipeline = PretrainedPipeline('explain_clinical_doc_ade', 'en', 'clinical/models')

text = """I have an allergic reaction to vancomycin.
My skin has be itchy, sore throat/burning/itchy, and numbness in tongue and gums.
I would not recommend this drug to anyone, especially since I have never had such an adverse reaction to any other medication."""

nlu.viz(ade_pipeline, text)

returns:

If a pipeline has multiple models candidates that can be used for a viz,
the first Annotator that is vizzable will be used to create viz.
You can specify which type of viz to create with the viz_type parameter

Output columns to use for the viz are automatically deducted from the pipeline, by using the first annotator that provides the correct output type for a specific viz.
You can specify which columns to use for a viz by using the
corresponding ner_col, pos_col, dep_untyped_col, dep_typed_col, resolution_col, relation_col, assertion_col, parameters.

nlu.autocomplete_pipeline(pipe)

Auto-Complete a pipeline or single annotator into a runnable pipeline by harnessing NLU’s DAG Autocompletion algorithm and returns it as NLU pipeline. The standard Spark pipeline is avaiable on the .vanilla_transformer_pipe attribute of the returned nlu pipe

Every Annotator and Pipeline of Annotators defines a DAG of tasks, with various dependencies that must be satisfied in topoligical order. NLU enables the completion of an incomplete DAG by finding or creating a path between the very first input node which is almost always is DocumentAssembler/MultiDocumentAssembler and the very last node(s), which is given by the topoligical sorting the iterable annotators parameter. Paths are created by resolving input features of annotators to the corrrosponding providers with matching storage references.

Example:

# Lets autocomplete the pipeline for a RelationExtractionModel, which as many input columns and sub-dependencies.
from sparknlp_jsl.annotator import RelationExtractionModel
re_model = RelationExtractionModel().pretrained("re_ade_clinical", "en", 'clinical/models').setOutputCol('relation')

text = """I have an allergic reaction to vancomycin.
My skin has be itchy, sore throat/burning/itchy, and numbness in tongue and gums.
I would not recommend this drug to anyone, especially since I have never had such an adverse reaction to any other medication."""

nlu_pipe = nlu.autocomplete_pipeline(re_model)
nlu_pipe.predict(text)

returns :

relation relation_confidence relation_entity1 relation_entity2 relation_entity2_class
1 1 allergic reaction vancomycin Drug_Ingredient
1 1 skin itchy Symptom
1 0.99998 skin sore throat/burning/itchy Symptom
1 0.956225 skin numbness Symptom
1 0.999092 skin tongue External_body_part_or_region
0 0.942927 skin gums External_body_part_or_region
1 0.806327 itchy sore throat/burning/itchy Symptom
1 0.526163 itchy numbness Symptom
1 0.999947 itchy tongue External_body_part_or_region
0 0.994618 itchy gums External_body_part_or_region
0 0.994162 sore throat/burning/itchy numbness Symptom
1 0.989304 sore throat/burning/itchy tongue External_body_part_or_region
0 0.999969 sore throat/burning/itchy gums External_body_part_or_region
1 1 numbness tongue External_body_part_or_region
1 1 numbness gums External_body_part_or_region
1 1 tongue gums External_body_part_or_region

nlu.to_pretty_df(pipe,data)

Annotates a Pandas Dataframe/Pandas Series/Numpy Array/Spark DataFrame/Python List strings /Python String
with given Spark NLP pipeline, which is assumed to be complete and runnable and returns it in a pythonic pandas dataframe format.

Example:

# works with Pipeline, LightPipeline, PipelineModel,PretrainedPipeline List[Annotator]
ade_pipeline = PretrainedPipeline('explain_clinical_doc_ade', 'en', 'clinical/models')

text = """I have an allergic reaction to vancomycin.
My skin has be itchy, sore throat/burning/itchy, and numbness in tongue and gums.
I would not recommend this drug to anyone, especially since I have never had such an adverse reaction to any other medication."""

# output is same as nlu.autocomplete_pipeline(re_model).nlu_pipe.predict(text)
nlu.to_pretty_df(ade_pipeline,text)

returns :

assertion asserted_entitiy entitiy_class assertion_confidence
present allergic reaction ADE 0.998
present itchy ADE 0.8414
present sore throat/burning/itchy ADE 0.9019
present numbness in tongue and gums ADE 0.9991

Annotators are grouped internally by NLU into output levels token,sentence, document,chunk and relation Same level annotators output columns are zipped and exploded together to create the final output df. Additionally, most keys from the metadata dictionary in the result annotations will be collected and expanded into their own columns in the resulting Dataframe, with special handling for Annotators that encode multiple metadata fields inside of one, seperated by strings like ||| or :::. Some columns are omitted from metadata to reduce total amount of output columns, these can be re-enabled by setting metadata=True

For a given pipeline output level is automatically set to the last anntators output level by default. This can be changed by defining to_preddty_df(pipe,text,output_level='my_level' for levels token,sentence, document,chunk and relation .

nlu.to_nlu_pipe(pipe)

Convert a pipeline or list of annotators into a NLU pipeline making .predict() and .viz() avaiable for every Spark NLP pipeline. Assumes the pipeline is already runnable.

# works with Pipeline, LightPipeline, PipelineModel,PretrainedPipeline List[Annotator]
ade_pipeline = PretrainedPipeline('explain_clinical_doc_ade', 'en', 'clinical/models')

text = """I have an allergic reaction to vancomycin.
My skin has be itchy, sore throat/burning/itchy, and numbness in tongue and gums.
I would not recommend this drug to anyone, especially since I have never had such an adverse reaction to any other medication."""

nlu_pipe = nlu.to_nlu_pipe(ade_pipeline)

# Same output as nlu.to_pretty_df(pipe,text) 
nlu_pipe.predict(text)

# same output as nlu.viz(pipe,text)
nlu_pipe.viz(text)

# Acces auto-completed Spark NLP big data pipeline,
nlu_pipe.vanilla_transformer_pipe.transform(spark_df)

returns :

assertion asserted_entitiy entitiy_class assertion_confidence
present allergic reaction ADE 0.998
present itchy ADE 0.8414
present sore throat/burning/itchy ADE 0.9019
present numbness in tongue and gums ADE 0.9991

and


NLU captures every Annotator of Spark NLP and Spark NLP for healthcare

The entire universe of Annotators in Spark NLP and Spark-NLP for healthcare is now embellished by NLU Components by using generalizable annotation extractors methods and configs internally to support enable the new NLU util methods. The following annotator classes are newly captured:

  • AssertionFilterer
  • ChunkConverter
  • ChunkKeyPhraseExtraction
  • ChunkSentenceSplitter
  • ChunkFiltererApproach
  • ChunkFilterer
  • ChunkMapperApproach
  • ChunkMapperFilterer
  • DocumentLogRegClassifierApproach
  • DocumentLogRegClassifierModel
  • ContextualParserApproach
  • ReIdentification
  • NerDisambiguator
  • NerDisambiguatorModel
  • AverageEmbeddings
  • EntityChunkEmbeddings
  • ChunkMergeApproach
  • ChunkMergeApproach
  • IOBTagger
  • NerChunker
  • NerConverterInternalModel
  • DateNormalizer
  • PosologyREModel
  • RENerChunksFilter
  • ResolverMerger
  • AnnotationMerger
  • Router
  • Word2VecApproach
  • WordEmbeddings
  • EntityRulerApproach
  • EntityRulerModel
  • TextMatcherModel
  • BigTextMatcher
  • BigTextMatcherModel
  • DateMatcher
  • MultiDateMatcher
  • RegexMatcher
  • TextMatcher
  • NerApproach
  • NerCrfApproach
  • NerOverwriter
  • DependencyParserApproach
  • TypedDependencyParserApproach
  • SentenceDetectorDLApproach
  • SentimentDetector
  • ViveknSentimentApproach
  • ContextSpellCheckerApproach
  • NorvigSweetingApproach
  • SymmetricDeleteApproach
  • ChunkTokenizer
  • ChunkTokenizerModel
  • RecursiveTokenizer
  • RecursiveTokenizerModel
  • Token2Chunk
  • WordSegmenterApproach
  • GraphExtraction
  • Lemmatizer
  • Normalizer

All NLU 4.0 for Healthcare Models

Some examples:

en.rxnorm.umls.mapping

Code:

nlu.load('en.rxnorm.umls.mapping').predict('1161611 315677')

mapped_entity_umls_code_origin_entity mapped_entity_umls_code
1161611 C3215948
315677 C0984912
en.ner.clinical_trials_abstracts

Code:

nlu.load('en.ner.clinical_trials_abstracts').predict('A one-year, randomised, multicentre trial comparing insulin glargine with NPH insulin in combination with oral agents in patients with type 2 diabetes.')

Results:

  entities_clinical_trials_abstracts entities_clinical_trials_abstracts_class entities_clinical_trials_abstracts_confidence
0 randomised CTDesign 0.9996
0 multicentre CTDesign 0.9998
0 insulin glargine Drug 0.99135
0 NPH insulin Drug 0.96875
0 type 2 diabetes DisorderOrSyndrome 0.999933

Code:

nlu.load('en.ner.clinical_trials_abstracts').viz('A one-year, randomised, multicentre trial comparing insulin glargine with NPH insulin in combination with oral agents in patients with type 2 diabetes.')

Results:

en.med_ner.pathogen

Code:

nlu.load('en.med_ner.pathogen').predict('Racecadotril is an antisecretory medication and it has better tolerability than loperamide. Diarrhea is the condition of having loose, liquid or watery bowel movements each day. Signs of dehydration often begin with loss of the normal stretchiness of the skin. While it has been speculated that rabies virus, Lyssavirus and Ephemerovirus could be transmitted through aerosols, studies have concluded that this is only feasible in limited conditions.')

Results:

  entities_pathogen entities_pathogen_class entities_pathogen_confidence
0 Racecadotril Medicine 0.9468
0 loperamide Medicine 0.9987
0 Diarrhea MedicalCondition 0.9848
0 dehydration MedicalCondition 0.6307
0 rabies virus Pathogen 0.95685
0 Lyssavirus Pathogen 0.9694
0 Ephemerovirus Pathogen 0.6917

Code:

nlu.load('en.med_ner.pathogen').viz('Racecadotril is an antisecretory medication and it has better tolerability than loperamide. Diarrhea is the condition of having loose, liquid or watery bowel movements each day. Signs of dehydration often begin with loss of the normal stretchiness of the skin. While it has been speculated that rabies virus, Lyssavirus and Ephemerovirus could be transmitted through aerosols, studies have concluded that this is only feasible in limited conditions.')

Results:

es.med_ner.living_species.roberta

Code:

nlu.load('es.med_ner.living_species.roberta').predict('Lactante varón de dos años. Antecedentes familiares sin interés. Antecedentes personales: Embarazo, parto y periodo neonatal normal. En seguimiento por alergia a legumbres, diagnosticado con diez meses por reacción urticarial generalizada con lentejas y garbanzos, con dieta de exclusión a legumbres desde entonces. En ésta visita la madre describe episodios de eritema en zona maxilar derecha con afectación ocular ipsilateral que se resuelve en horas tras la administración de corticoides. Le ha ocurrido en 5-6 ocasiones, en relación con la ingesta de alimentos previamente tolerados. Exploración complementaria: Cacahuete, ac(ige)19.2 Ku.arb/l. Resultados: Ante la sospecha clínica de Síndrome de Frey, se tranquiliza a los padres, explicándoles la naturaleza del cuadro y se cita para revisión anual.')

Results:

  entities_living_species entities_living_species_class entities_living_species_confidence
0 Lactante varón HUMAN 0.93175
0 familiares HUMAN 1
0 personales HUMAN 1
0 neonatal HUMAN 0.9997
0 legumbres SPECIES 0.9962
0 lentejas SPECIES 0.9988
0 garbanzos SPECIES 0.9901
0 legumbres SPECIES 0.9976
0 madre HUMAN 1
0 Cacahuete SPECIES 0.998
0 padres HUMAN 1

Code:

nlu.load('es.med_ner.living_species.roberta').viz('Lactante varón de dos años. Antecedentes familiares sin interés. Antecedentes personales: Embarazo, parto y periodo neonatal normal. En seguimiento por alergia a legumbres, diagnosticado con diez meses por reacción urticarial generalizada con lentejas y garbanzos, con dieta de exclusión a legumbres desde entonces. En ésta visita la madre describe episodios de eritema en zona maxilar derecha con afectación ocular ipsilateral que se resuelve en horas tras la administración de corticoides. Le ha ocurrido en 5-6 ocasiones, en relación con la ingesta de alimentos previamente tolerados. Exploración complementaria: Cacahuete, ac(ige)19.2 Ku.arb/l. Resultados: Ante la sospecha clínica de Síndrome de Frey, se tranquiliza a los padres, explicándoles la naturaleza del cuadro y se cita para revisión anual.')

Results:

All healthcare models added in NLU 4.0 :

Language NLU Reference Spark NLP Reference Task Annotator Class model_id
en en.map_entity.abbreviation_to_definition abbreviation_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.abbreviation_to_definition
en en.map_entity.abbreviation_to_definition abbreviation_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.abbreviation_to_definition
en en.map_entity.drug_to_action_treatment drug_action_treatment_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.drug_to_action_treatment
en en.map_entity.drug_to_action_treatment drug_action_treatment_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.drug_to_action_treatment
en en.map_entity.drug_to_action_treatment drug_action_treatment_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.drug_to_action_treatment
en en.map_entity.drug_brand_to_ndc drug_brandname_ndc_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.drug_brand_to_ndc
en en.map_entity.drug_brand_to_ndc drug_brandname_ndc_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.drug_brand_to_ndc
en en.map_entity.icd10cm_to_snomed icd10cm_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icd10cm_to_snomed
en en.map_entity.icd10cm_to_umls icd10cm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icd10cm_to_umls
en en.map_entity.icdo_to_snomed icdo_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icdo_to_snomed
en en.map_entity.mesh_to_umls mesh_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.mesh_to_umls
en en.map_entity.rxnorm_to_action_treatment rxnorm_action_treatment_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_action_treatment
en en.map_entity.rxnorm_to_action_treatment rxnorm_action_treatment_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_action_treatment
en en.map_entity.rxnorm_resolver rxnorm_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_resolver
en en.map_entity.rxnorm_resolver rxnorm_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_resolver
en en.map_entity.rxnorm_to_ndc rxnorm_ndc_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_ndc
en en.map_entity.rxnorm_to_ndc rxnorm_ndc_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_ndc
en en.map_entity.rxnorm_to_ndc rxnorm_ndc_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_ndc
en en.map_entity.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_umls
en en.map_entity.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_umls
en en.map_entity.snomed_to_icd10cm snomed_icd10cm_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_icd10cm
en en.map_entity.snomed_to_icdo snomed_icdo_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_icdo
en en.map_entity.snomed_to_umls snomed_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_umls
en en.map_entity.snomed_to_icd10cm snomed_icd10cm_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_icd10cm
en en.map_entity.icd10cm_to_snomed icd10cm_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icd10cm_to_snomed
en en.map_entity.snomed_to_icdo snomed_icdo_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_icdo
en en.map_entity.icdo_to_snomed icdo_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icdo_to_snomed
en en.map_entity.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_umls
en en.map_entity.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.rxnorm_to_umls
en en.map_entity.icd10cm_to_umls icd10cm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.icd10cm_to_umls
en en.map_entity.mesh_to_umls mesh_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.mesh_to_umls
en en.map_entity.snomed_to_umls snomed_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.map_entity.snomed_to_umls
en en.map_entity.section_headers_normalized normalized_section_header_mapper Chunk Mapping PretrainedPipeline Chunk Mappingen.map_entity.section_headers_normalized
en en.map_entity.section_headers_normalized normalized_section_header_mapper Chunk Mapping PretrainedPipeline Chunk Mappingen.map_entity.section_headers_normalized
en en.map_entity.section_headers_normalized normalized_section_header_mapper Chunk Mapping PretrainedPipeline Chunk Mappingen.map_entity.section_headers_normalized
en en.icd10cm_to_snomed icd10cm_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.icd10cm_to_snomed
en en.icd10cm_to_umls icd10cm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.icd10cm_to_umls
en en.icdo_to_snomed icdo_snomed_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.icdo_to_snomed
en en.mesh_to_umls mesh_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.mesh_to_umls
en en.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.rxnorm_to_umls
en en.rxnorm_to_umls rxnorm_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.rxnorm_to_umls
en en.snomed_to_icd10cm snomed_icd10cm_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.snomed_to_icd10cm
en en.snomed_to_icdo snomed_icdo_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.snomed_to_icdo
en en.snomed_to_umls snomed_umls_mapper Chunk Mapping ChunkMapperModel Chunk Mappingen.snomed_to_umls
en en.map_entity.icd10cm_to_snomed.pipe icd10cm_snomed_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.icd10cm_to_snomed.pipe
en en.map_entity.snomed_to_icd10cm.pipe snomed_icd10cm_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.snomed_to_icd10cm.pipe
en en.map_entity.snomed_to_icd10cm.pipe snomed_icd10cm_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.snomed_to_icd10cm.pipe
en en.map_entity.icdo_to_snomed.pipe icdo_snomed_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.icdo_to_snomed.pipe
en en.map_entity.snomed_to_icdo.pipe snomed_icdo_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.snomed_to_icdo.pipe
en en.map_entity.rxnorm_to_ndc.pipe rxnorm_ndc_mapping Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.map_entity.rxnorm_to_ndc.pipe
en en.med_ner.pathogen.pipeline ner_pathogen_pipeline Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.med_ner.pathogen.pipeline
en en.med_ner.biomedical_bc2gm.pipeline ner_biomedical_bc2gm_pipeline Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.med_ner.biomedical_bc2gm.pipeline
ro ro.deid.clinical clinical_deidentification Pipeline Healthcare MedicalNerModel Pipeline Healthcarero.deid.clinical
en en.med_ner.clinical_trials_abstracts.pipe ner_clinical_trials_abstracts_pipeline Pipeline Healthcare PretrainedPipeline Pipeline Healthcareen.med_ner.clinical_trials_abstracts.pipe
en en.ner.clinical_trials_abstracts ner_clinical_trials_abstracts Named Entity Recognition MedicalNerModel Named Entity Recognitionen.ner.clinical_trials_abstracts
en en.med_ner.clinical_trials_abstracts bert_token_classifier_ner_clinical_trials_abstracts Named Entity Recognition MedicalBertForTokenClassifier Named Entity Recognitionen.med_ner.clinical_trials_abstracts
en en.med_ner.pathogen ner_pathogen Named Entity Recognition MedicalNerModel Named Entity Recognitionen.med_ner.pathogen
en en.med_ner.living_species.token_bert bert_token_classifier_ner_living_species Named Entity Recognition MedicalBertForTokenClassifier Named Entity Recognitionen.med_ner.living_species.token_bert
en en.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionen.med_ner.living_species
en en.med_ner.living_species.biobert ner_living_species_biobert Named Entity Recognition MedicalNerModel Named Entity Recognitionen.med_ner.living_species.biobert
en en.classify.stress bert_sequence_classifier_stress Text Classification MedicalBertForSequenceClassification Text Classificationen.classify.stress
es es.embed.scielo300d embeddings_scielo_300d Embeddings WordEmbeddingsModel Embeddingses.embed.scielo300d
es es.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitiones.med_ner.living_species
es es.med_ner.living_species.bert ner_living_species_bert Named Entity Recognition MedicalNerModel Named Entity Recognitiones.med_ner.living_species.bert
es es.med_ner.living_species.roberta ner_living_species_roberta Named Entity Recognition MedicalNerModel Named Entity Recognitiones.med_ner.living_species.roberta
es es.med_ner.living_species.300 ner_living_species_300 Named Entity Recognition MedicalNerModel Named Entity Recognitiones.med_ner.living_species.300
es es.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitiones.med_ner.living_species
fr fr.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionfr.med_ner.living_species
fr fr.med_ner.living_species.bert ner_living_species_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionfr.med_ner.living_species.bert
pt pt.med_ner.living_species.token_bert bert_token_classifier_ner_living_species Named Entity Recognition MedicalBertForTokenClassifier Named Entity Recognitionpt.med_ner.living_species.token_bert
pt pt.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionpt.med_ner.living_species
pt pt.med_ner.living_species.roberta ner_living_species_roberta Named Entity Recognition MedicalNerModel Named Entity Recognitionpt.med_ner.living_species.roberta
pt pt.med_ner.living_species.bert ner_living_species_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionpt.med_ner.living_species.bert
it it.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionit.med_ner.living_species
it it.med_ner.living_species.bert ner_living_species_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionit.med_ner.living_species.bert
it it.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionit.med_ner.living_species
ca ca.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitionca.med_ner.living_species
gl gl.med_ner.living_species ner_living_species Named Entity Recognition MedicalNerModel Named Entity Recognitiongl.med_ner.living_species
ro ro.med_ner.living_species.bert ner_living_species_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionro.med_ner.living_species.bert
ro ro.med_ner.clinical ner_clinical Named Entity Recognition MedicalNerModel Named Entity Recognitionro.med_ner.clinical
ro ro.embed.clinical.bert.base_cased ner_clinical_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionro.embed.clinical.bert.base_cased
ro ro.med_ner.deid.subentity ner_deid_subentity Named Entity Recognition MedicalNerModel Named Entity Recognitionro.med_ner.deid.subentity
ro ro.med_ner.deid.subentity.bert ner_deid_subentity_bert Named Entity Recognition MedicalNerModel Named Entity Recognitionro.med_ner.deid.subentity.bert

All NLU 4.0 Core Models

All core models added in NLU 4.0 : Can be found on the NLU website because of Github Limitations

NLU Reference Spark NLP Reference Task Language Name(s) Annotator Class
bn.answer_question.tydiqa.multi_lingual_bert bert_qa_mbert_bengali_tydiqa_qa Question Answering Bengali BertForQuestionAnswering
es.answer_question.squadv2.electra.small electra_qa_biomedtra_small_es_squad2 Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squad_sqac.bert.base_cased bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squadv2.bert.base_cased.by_MMG bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_MMG Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squadv2.bert.base_cased.by_mrm8488 bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488 Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squadv2.bert.distilled_base_cased bert_qa_distill_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_mrm8488 Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squad.ruperta.base.by_mrm8488 roberta_qa_RuPERTa_base_finetuned_squadv1 Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squadv2.roberta.base roberta_qa_roberta_base_bne_squad2_hackathon_pln Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squadv2_sqac.bert.base_cased_spa.by_MMG bert_qa_bert_base_spanish_wwm_cased_finetuned_spa_squad2_es_finetuned_sqac Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squadv2_bio_medical.roberta.base roberta_qa_roberta_base_biomedical_es_squad2_hackathon_pln Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squadv2_clinical_bio_medical.roberta.base roberta_qa_roberta_base_biomedical_clinical_es_squad2_hackathon_pln Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squadv2_sqac.bert.base_cased.by_MMG bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac_finetuned_squad2_es_MMG Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squadv2_sqac.bert.base_cased_v2.by_MMG bert_qa_bert_base_spanish_wwm_cased_finetuned_squad2_es_finetuned_sqac Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_spanish Question Answering Castilian, Spanish XlmRoBertaForQuestionAnswering
es.answer_question.xlm_roberta.multilingual_large xlm_roberta_qa_xlm_roberta_large_qa_multilingual_finedtuned_ru_ru_AlexKay Question Answering Castilian, Spanish XlmRoBertaForQuestionAnswering
es.answer_question.squad.roberta.large.by_stevemobs roberta_qa_roberta_large_fine_tuned_squad_es_stevemobs Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squadv2.roberta.base_v2 roberta_qa_RuPERTa_base_finetuned_squadv2 Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squad.roberta.large.by_jamarju roberta_qa_roberta_large_bne_squad_2.0_es_jamarju Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.large.by_BSC-TeMU roberta_qa_BSC_TeMU_roberta_large_bne_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squad.roberta.base.by_jamarju roberta_qa_roberta_base_bne_squad_2.0_es_jamarju Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squad.roberta.base_4096.by_mrm8488 roberta_qa_longformer_base_4096_spanish_finetuned_squad Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.distil_bert.base_uncased distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_tar Question Answering Castilian, Spanish DistilBertForQuestionAnswering
es.answer_question.mlqa.distil_bert.base_uncased distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_mlqa Question Answering Castilian, Spanish DistilBertForQuestionAnswering
es.answer_question.sqac.bert.base bert_qa_beto_base_spanish_sqac Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.sqac.distil_bert.base_uncased distilbert_qa_distillbert_base_spanish_uncased_finetuned_qa_sqac Question Answering Castilian, Spanish DistilBertForQuestionAnswering
es.answer_question.sqac.roberta.base.by_BSC-TeMU roberta_qa_BSC_TeMU_roberta_base_bne_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.base.by_IIC roberta_qa_roberta_base_spanish_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.bert.base_cased bert_qa_bert_base_spanish_wwm_cased_finetuned_sqac Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.sqac.roberta.base.by_mrm8488 roberta_qa_mrm8488_roberta_base_bne_finetuned_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.base.by_nlp-en-es roberta_qa_nlp_en_es_roberta_base_bne_finetuned_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.large.by_PlanTL-GOB-ES roberta_qa_PlanTL_GOB_ES_roberta_large_bne_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.large.by_nlp-en-es roberta_qa_bertin_large_finetuned_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.squad.electra.small electra_qa_electricidad_small_finetuned_squadv1 Question Answering Castilian, Spanish BertForQuestionAnswering
es.answer_question.squad.roberta.base.by_IIC roberta_qa_roberta_base_spanish_squades Question Answering Castilian, Spanish RoBertaForQuestionAnswering
es.answer_question.sqac.roberta.base.by_PlanTL-GOB-ES roberta_qa_PlanTL_GOB_ES_roberta_base_bne_sqac Question Answering Castilian, Spanish RoBertaForQuestionAnswering
ch.answer_question.xlm_roberta xlm_roberta_qa_ADDI_CH_XLM_R Question Answering Chamorro XlmRoBertaForQuestionAnswering
da.answer_question.squad.bert bert_qa_danish_bert_botxo_qa_squad Question Answering Danish BertForQuestionAnswering
da.answer_question.squad.xlmr_roberta.base xlm_roberta_qa_xlmr_base_texas_squad_da_da_saattrupdan Question Answering Danish XlmRoBertaForQuestionAnswering
nl.answer_question.squadv2.bert.multilingual_base_cased bert_qa_bert_base_multilingual_cased_finetuned_dutch_squad2 Question Answering Dutch, Flemish BertForQuestionAnswering
en.answer_question.squad.roberta.large.by_csarron roberta_qa_roberta_large_squad_v1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.large.by_rahulchakwate roberta_qa_roberta_large_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.scibert.by_amoux bert_qa_scibert_nli_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.scibert.by_ixa-ehu bert_qa_SciBERT_SQuAD_QuAC Question Answering English BertForQuestionAnswering
en.answer_question.squad.scibert.uncased bert_qa_scibert_scivocab_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert bert_qa_spanbert_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_0 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_2 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_2 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_4 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_4 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_8 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_6 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_128d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_128d_seed_4 bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_128d_seed_6 bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_128d_seed_8 bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_256d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_32d_seed_0 bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_32d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_32d_seed_2 bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.distilled_base roberta_qa_distilroberta_base_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_1024d_seed_42 bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.distilled roberta_qa_distilroberta_finetuned_squadv1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_sq.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_5_new Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.by_sunitha roberta_qa_Roberta_Custom_Squad_DS Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_6 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_8 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_8 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_deletion_10.by_huxxx657 roberta_qa_roberta_base_finetuned_deletion_squad_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_deletion_15.by_huxxx657 roberta_qa_roberta_base_finetuned_deletion_squad_15 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_sae.by_jgammack roberta_qa_SAE_roberta_base_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_10.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_10_new.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_10_new Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_15.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_15 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_15_v2.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_15_new Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_scrambled_5.by_huxxx657 roberta_qa_roberta_base_finetuned_scrambled_squad_5 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.by_vuiseng9 roberta_qa_roberta_l_squadv1.1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_32d_seed_6 bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base_seed_10 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_2 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_4 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_42 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_42 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_6 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_8 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_8 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_v1.by_huxxx657 roberta_qa_roberta_base_finetuned_squad_1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_v2.by_huxxx657 roberta_qa_roberta_base_finetuned_squad_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_v3.by_huxxx657 roberta_qa_roberta_base_finetuned_squad_3 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.by_cgou roberta_qa_fin_RoBERTa_v1_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_seed_0 roberta_qa_roberta_base_few_shot_k_16_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_512d_seed_0 bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_0 Question Answering English BertForQuestionAnswering
en.answer_question.squad_battery.bert.cased.by_batterydata bert_qa_batterybert_cased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_512d_seed_6 bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_6 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.albert.xxl.by_replydotai albert_qa_xxlarge_v1_finetuned_squad2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.xxl.by_sultan albert_qa_BioM_xxlarge_SQuAD2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.xxl_512d albert_qa_xxlargev1_squad2_512 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.xxl_v2 albert_qa_xxlarge_v2_squad2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.bert.base bert_qa_bert_base_finetuned_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_cased.by_deepset bert_base_cased_qa_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_cased.by_vumichien bert_qa_tf_bert_base_cased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_cased.by_ydshieh bert_qa_ydshieh_bert_base_cased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_uncased.by_Vasanth bert_qa_bert_base_uncased_qa_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_uncased.by_deepset bert_qa_deepset_bert_base_uncased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_uncased.by_twmkn9 bert_qa_twmkn9_bert_base_uncased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_uncased_v2 bert_qa_bert_base_uncased_finetuned_squad_v2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_v2.by_mrm8488 bert_qa_bert_mini_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.base_v2_5.by_mrm8488 bert_qa_bert_mini_5_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.by_augustoortiz bert_qa_bert_finetuned_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.by_maroo93 bert_qa_squad2.0 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.by_pinecone bert_qa_bert_reader_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.distilled bert_qa_xdistil_l12_h384_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.distilled_medium bert_qa_bert_medium_squad2_distilled Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large.by_Sindhu bert_qa_muril_large_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large.by_phiyodr bert_qa_bert_large_finetuned_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.albert.xxl.by_elgeish albert_qa_cs224n_squad2.0_xxlarge_v1 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.xl_v2 albert_qa_xlarge_v2_squad_v2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.large_v2 albert_qa_cs224n_squad2.0_large_v2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2.albert.base_v2.by_vumichien albert_qa_vumichien_base_v2_squad2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_512d_seed_8 bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_64d_seed_0 bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_64d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_64d_seed_2 bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_64d_seed_4 bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_64d_seed_6 bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_seed_42 bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42 Question Answering English BertForQuestionAnswering
en.answer_question.squad.xlm_roberta.by_jakobwes xlm_roberta_qa_xlm_roberta_squad_v1.1 Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squad.xlm_roberta.by_meghana xlm_roberta_qa_hitalmqa_finetuned_squad Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squad_battery.bert.base_uncased bert_qa_batterydata_bert_base_uncased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.span_bert.base_cased_512d_seed_10 bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_4 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad_battery.bert.uncased.by_batterydata bert_qa_batterybert_uncased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad_battery.bert.uncased_only_bert.by_batterydata bert_qa_batteryonlybert_uncased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad_battery.scibert.cased bert_qa_batteryscibert_cased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad_battery.scibert.uncased bert_qa_batteryscibert_uncased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad_ben_tel.bert.by_krinal214 bert_qa_bert_all_squad_ben_tel_context Question Answering English BertForQuestionAnswering
en.answer_question.squad_covid.bert bert_qa_covid_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad_pubmed.biobert bert_qa_biobert_v1.1_pubmed_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad_translated.bert.by_krinal214 bert_qa_bert_all_squad_all_translated Question Answering English BertForQuestionAnswering
en.answer_question.squad_translated.bert.que.by_krinal214 bert_qa_bert_all_squad_que_translated Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.albert.base_v2.by_elgeish albert_qa_cs224n_squad2.0_base_v2 Question Answering English AlbertForQuestionAnswering
en.answer_question.squad_battery.bert.cased_only_bert.by_batterydata bert_qa_batteryonlybert_cased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_2 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_32d_seed_10 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_0 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_mtl.by_jgammack distilbert_qa_MTL_base_uncased_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_sae.by_jgammack distilbert_qa_SAE_base_uncased_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_v2.by_arvalinno distilbert_qa_base_uncased_finetuned_indosquad_v2 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_v2.by_ericRosello distilbert_qa_base_uncased_finetuned_squad_frozen_v2 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_v2.by_holtin distilbert_qa_holtin_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_v2.by_huxxx657 distilbert_qa_base_uncased_finetuned_jumbling_squad_15 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_v3.by_anurag0077 distilbert_qa_anurag0077_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_AyushPJ distilbert_qa_test_squad_trained_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_ZYW distilbert_qa_test_squad_trained Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_abhilash1910 distilbert_qa_squadv1 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_rowan1224 distilbert_qa_squad_slp Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_sunitha distilbert_qa_AQG_CV_Squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.by_tabo distilbert_qa_checkpoint_500_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.electra electra_qa_squad_slp Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.base.by_Palak electra_qa_google_base_discriminator_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.base.by_mrm8488 electra_qa_base_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.base.by_usami electra_qa_base_discriminator_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.base.by_valhalla electra_qa_base_discriminator_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.large.by_howey electra_qa_large_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.small.by_Palak electra_qa_google_small_discriminator_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.electra.small.by_bdickson electra_qa_small_discriminator_finetuned_squad_1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_full.by_holtin distilbert_qa_base_uncased_holtin_finetuned_full_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased_colab.by_Adrian distilbert_qa_base_uncased_finetuned_squad_colab Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_vkrishnamoorthy distilbert_qa_vkrishnamoorthy_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_vkmr distilbert_qa_vkmr_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_gokulkarthik distilbert_qa_gokulkarthik_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_graviraja distilbert_qa_graviraja_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_guhuawuli distilbert_qa_guhuawuli_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_hark99 distilbert_qa_hark99_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_hcy11 distilbert_qa_hcy11_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_hiiii23 distilbert_qa_hiiii23_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_holtin distilbert_qa_base_uncased_holtin_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_huggingfaceepita distilbert_qa_huggingfaceepita_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_huxxx657 distilbert_qa_huxxx657_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_jgammack distilbert_qa_jgammack_base_uncased_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.electra.small.by_hankzhong electra_qa_hankzhong_small_discriminator_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_jhoonk distilbert_qa_jhoonk_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_kaggleodin distilbert_qa_kaggleodin_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_lewtun distilbert_qa_base_uncased_finetuned_squad_v1 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_machine2049 distilbert_qa_base_uncased_finetuned_squad_ Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_manudotc distilbert_qa_transformers_base_uncased_finetuneQA_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_sunitha distilbert_qa_base_uncased_3feb_2022_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_tli8hf distilbert_qa_unqover_base_uncased_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_tucan9389 distilbert_qa_tucan9389_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_uploaded by huggingface distilbert_qa_base_uncased_distilled_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_usami distilbert_qa_usami_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_vitusya distilbert_qa_vitusya_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_jsunster distilbert_qa_jsunster_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.roberta.base_64d_seed_10 roberta_qa_roberta_base_few_shot_k_64_finetuned_squad_seed_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.electra.small.by_mrm8488 electra_qa_small_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.ixam_bert.by_MarcBrun bert_qa_ixambert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base_128d_seed_42 roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_42 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_128d_seed_6 roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_128d_seed_8 roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_8 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_256d_seed_0 roberta_qa_roberta_base_few_shot_k_256_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_256d_seed_10 roberta_qa_roberta_base_few_shot_k_256_finetuned_squad_seed_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_256d_seed_2 roberta_qa_roberta_base_few_shot_k_256_finetuned_squad_seed_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_256d_seed_4 roberta_qa_roberta_base_few_shot_k_256_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_256d_seed_6 roberta_qa_roberta_base_few_shot_k_256_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
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en.answer_question.squad.roberta.base_32d_seed_0 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.bert.large_tiny_768d.by_MichelBartels bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base_32d_seed_2 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_32d_seed_4 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_32d_seed_6 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_32d_seed_8 roberta_qa_roberta_base_few_shot_k_32_finetuned_squad_seed_8 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_0 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_10 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_10 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_2 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_4 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_6 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_6 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_512d_seed_8 roberta_qa_roberta_base_few_shot_k_512_finetuned_squad_seed_8 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_128d_seed_4 roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
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en.answer_question.squad.roberta.base_128d_seed_0 roberta_qa_roberta_base_few_shot_k_128_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.ixam_bert.eu_en_tunedby_MarcBrun bert_qa_ixambert_finetuned_squad_eu_en_MarcBrun Question Answering English BertForQuestionAnswering
en.answer_question.squad.ixam_bert.eu_tuned.by_MarcBrun bert_qa_ixambert_finetuned_squad_eu_MarcBrun Question Answering English BertForQuestionAnswering
en.answer_question.squad.link_bert.large bert_qa_linkbert_large_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.multi_lingual_bert.by_ZYW bert_qa_squad_mbert_model Question Answering English BertForQuestionAnswering
en.answer_question.squad.multi_lingual_bert.en_de_es.by_ZYW bert_qa_squad_mbert_en_de_es_model Question Answering English BertForQuestionAnswering
en.answer_question.squad.multi_lingual_bert.en_de_es_vi_zh.by_ZYW bert_qa_squad_mbert_en_de_es_vi_zh_model Question Answering English BertForQuestionAnswering
en.answer_question.squad.multi_lingual_bert.v2.by_ZYW bert_qa_squad_mbert_model_2 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base.by_Firat roberta_qa_Firat_roberta_base_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base.by_ahmedattia143 roberta_qa_roberta_squadv1_base Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base.by_csarron roberta_qa_roberta_base_squad_v1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.electra.small_v2.by_bdickson electra_qa_small_discriminator_finetuned_squad_2 Question Answering English BertForQuestionAnswering
en.answer_question.squad.roberta.base.by_huxxx657 roberta_qa_huxxx657_roberta_base_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base.by_mrm8488 roberta_qa_roberta_base_1B_1_finetuned_squadv1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base.by_rahulchakwate roberta_qa_rahulchakwate_roberta_base_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base.by_tli8hf roberta_qa_unqover_roberta_base_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.roberta.base_1024d_seed_0 roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_0 Question Answering English RoBertaForQuestionAnswering
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en.answer_question.squad.roberta.base_1024d_seed_4 roberta_qa_roberta_base_few_shot_k_1024_finetuned_squad_seed_4 Question Answering English RoBertaForQuestionAnswering
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en.answer_question.squad.roberta.base.by_jgammack roberta_qa_roberta_base_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.bert.large_tiny_768d_v2.by_MichelBartels bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_768d bert_qa_tinybert_6l_768d_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large_uncased.by_andi611 bert_qa_bert_large_uncased_whole_word_masking_squad2_with_ner_mit_restaurant_with_neg_with_repeat Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.uncased_4l_256d_a4a_256d bert_qa_bert_uncased_L_4_H_256_A_4_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.uncased_4l_512d_a8a_512d bert_qa_bert_uncased_L_4_H_512_A_8_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.uncased_4l_768d_a12a_768d bert_qa_bert_uncased_L_4_H_768_A_12_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.uncased_6l_128d_a2a_128d bert_qa_bert_uncased_L_6_H_128_A_2_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.distil_bert.base_uncased distilbert_qa_base_uncased_squad2_covid_qa_deepset Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2_covid.electra.base electra_qa_base_squad2_covid_deepset Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.roberta.base.by_armageddon roberta_qa_roberta_base_squad2_covid_qa_deepset Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2_covid.roberta.base.by_deepset roberta_qa_roberta_base_squad2_covid Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2_covid.roberta.large roberta_qa_roberta_large_squad2_covid_qa_deepset Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2_covid_cord19.bert.uncased_10l_512d_a8a_512d bert_qa_bert_uncased_L_10_H_512_A_8_cord19_200616_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid_cord19.bert.uncased_4l_256d_a4a_256d bert_qa_bert_uncased_L_4_H_256_A_4_cord19_200616_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid_cord19.bert.uncased_4l_512d_a8a_512d bert_qa_bert_uncased_L_4_H_512_A_8_cord19_200616_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid_cord19.bert.uncased_4l_768d_a12a_768d bert_qa_bert_uncased_L_4_H_768_A_12_cord19_200616_squad2_covid_qna Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_pubmed.bert.v2 bert_qa_pubmed_bert_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_pubmed.biobert.v2 bert_qa_biobert_v1.1_pubmed_squad_v2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_pubmed.sapbert bert_qa_sapbert_from_pubmedbert_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.synqa.electra.large electra_qa_large_synqa Question Answering English BertForQuestionAnswering
en.answer_question.synqa.roberta.large.by_mbartolo roberta_qa_roberta_large_synqa Question Answering English RoBertaForQuestionAnswering
en.answer_question.synqa_ext.roberta.large.by_mbartolo roberta_qa_roberta_large_synqa_ext Question Answering English RoBertaForQuestionAnswering
en.answer_question.tquad.bert.xtremedistiled_uncased bert_qa_xtremedistil_l6_h256_uncased_TQUAD_finetuned_lr_2e_05_epochs_9 Question Answering English BertForQuestionAnswering
en.answer_question.trial.bert.by_sunitha bert_qa_Trial_3_Results Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.uncased_2l_512d_a8a_512d bert_qa_bert_uncased_L_2_H_512_A_8_squad2_covid_qna Question Answering English BertForQuestionAnswering
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en.answer_question.squadv2_covid.bert.large_uncased bert_qa_bert_large_uncased_squad2_covid_qa_deepset Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_covid.bert.base_uncased bert_qa_bert_base_uncased_squad2_covid_qa_deepset Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.xlm_roberta.distilled_base xlm_roberta_qa_xlm_roberta_base_squad2_distilled Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squadv2.xlm_roberta.large xlm_roberta_qa_xlm_roberta_large_squad2 Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squadv2_bioasq8b.electra.base electra_qa_BioM_Base_SQuAD2_BioASQ8B Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_bioasq8b.electra.large electra_qa_BioM_Large_SQuAD2_BioASQ8B Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_chaii.xlm_roberta.distilled_base xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squadv2_chaii.xlm_roberta.distilled_base_small xlm_roberta_qa_xlm_roberta_base_squad2_distilled_finetuned_chaii_small Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squadv2_chemical.bert.uncased bert_qa_chemical_bert_uncased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_conll.bert.large_uncased.by_andi611 bert_qa_bert_large_uncased_whole_word_masking_squad2_with_ner_conll2003_with_neg_with_repeat Question Answering English BertForQuestionAnswering
en.answer_question.squadv2_conll.bert.large_uncased_pistherea.by_andi611 bert_qa_bert_large_uncased_whole_word_masking_squad2_with_ner_Pistherea_conll2003_with_neg_with_repeat Question Answering English BertForQuestionAnswering
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en.answer_question.trivia.albert.xxl albert_qa_xxlarge_tweetqa Question Answering English AlbertForQuestionAnswering
en.answer_question.squadv2_conll.distil_bert.base_uncased.by_andi611 distilbert_qa_base_uncased_squad2_with_ner Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2_conll.distil_bert.base_uncased_with_neg_with_multi.by_andi611 distilbert_qa_base_uncased_squad2_with_ner_with_neg_with_multi Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2_conll.distil_bert.base_uncased_with_neg_with_multi_with_repeat.by_andi611 distilbert_qa_base_uncased_squad2_with_ner_with_neg_with_multi_with_repeat Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squadv2_cord19.bert.small bert_qa_bert_small_cord19_squad2 Question Answering English BertForQuestionAnswering
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en.answer_question.squadv2.xlm_roberta.base_v2 xlm_roberta_qa_squadv2_xlm_roberta_base Question Answering English XlmRoBertaForQuestionAnswering
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en.answer_question.xlm_roberta.fr_tuned.by_Gantenbein roberta_qa_ADDI_FR_XLM_R Question Answering English RoBertaForQuestionAnswering
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en.answer_question.xquad.bert.multilingual_base bert_qa_bert_base_multilingual_xquad Question Answering English BertForQuestionAnswering
en.answer_question.xquad.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_xquad Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.xquad.xlm_roberta.large xlm_roberta_qa_xlm_roberta_large_xquad Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.xquad_chaii.bert.cased bert_qa_bert_multi_cased_finedtuned_xquad_chaii Question Answering English BertForQuestionAnswering
en.answer_question.xquad_squad.bert.cased bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab Question Answering English BertForQuestionAnswering
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en.answer_question.trivia.bert.base_512d bert_qa_bert_base_512_full_trivia Question Answering English BertForQuestionAnswering
en.answer_question.trivia.bert.by_Danastos bert_qa_triviaqa_bert_el_Danastos Question Answering English BertForQuestionAnswering
en.answer_question.trivia.bert.by_Kutay bert_qa_fine_tuned_tweetqa_aip Question Answering English BertForQuestionAnswering
en.answer_question.trivia.distil_bert.base_uncased distilbert_qa_base_uncased_finetuned_triviaqa Question Answering English DistilBertForQuestionAnswering
en.answer_question.trivia.longformer.large longformer_qa_large_4096_finetuned_triviaqa Question Answering English LongformerForQuestionAnswering
en.answer_question.trivia.roberta roberta_qa_roberta_fine_tuned_tweet_sentiment_extractor Question Answering English RoBertaForQuestionAnswering
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en.answer_question.trivia.bert.base_2048.by_MrAnderson bert_qa_bert_base_2048_full_trivia_copied_embeddings Question Answering English BertForQuestionAnswering
en.answer_question.tydiqa.bert.multilingual bert_qa_Part_2_BERT_Multilingual_Dutch_Model_E1 Question Answering English BertForQuestionAnswering
en.answer_question.tydiqa.multi_lingual_bert bert_qa_Part_2_mBERT_Model_E2 Question Answering English BertForQuestionAnswering
en.answer_question.tydiqa.roberta roberta_qa_roberta_tydiqa Question Answering English RoBertaForQuestionAnswering
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en.answer_question.tydiqa.xlm_roberta.by_krinal214 xlm_roberta_qa_xlm_all Question Answering English XlmRoBertaForQuestionAnswering
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en.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_finetune_qa Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.xlm_roberta.by_Dongjae xlm_roberta_qa_mrc2reader Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.xlm_roberta.by_Srini99 xlm_roberta_qa_TQA Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.xlm_roberta.by_anukaver xlm_roberta_qa_xlm_roberta_est_qa Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.tydiqa.distil_bert distilbert_qa_multi_finetuned_for_xqua_on_tydiqa Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.bert.large_uncased.by_Salesforce bert_qa_qaconv_bert_large_uncased_whole_word_masking_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.xlm_roberta.base_24465525.by_teacookies xlm_roberta_qa_autonlp_roberta_base_squad2_24465525 Question Answering English XlmRoBertaForQuestionAnswering
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en.answer_question.squadv2.distil_bert.base_uncased.by_andi611 distilbert_qa_base_uncased_squad2_with_ner_mit_restaurant_with_neg_with_repeat Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squadv2.distil_bert.base_uncased.by_tabo distilbert_qa_tabo_base_uncased_finetuned_squad2 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.distil_bert.base_uncased.by_twmkn9 distilbert_qa_base_uncased_squad2 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.distil_bert.by_threem distilbert_qa_mysquadv2_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.distil_bert.v2.by_threem distilbert_qa_mysquadv2_8Jan22_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.electra.base.by_PremalMatalia electra_qa_base_best_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.base.by_navteca electra_qa_base_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.base.by_sultan electra_qa_BioM_Base_SQuAD2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.base_v2 electra_qa_base_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.large.by_sultan electra_qa_BioM_Large_SQuAD2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.large.by_superspray electra_qa_large_discriminator_squad2_custom_dataset Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.large_512d electra_qa_large_discriminator_squad2_512 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.electra.small_v2 electra_qa_small_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.longformer.base longformer_base_base_qa_squad2 Question Answering English LongformerForQuestionAnswering
en.answer_question.squadv2.longformer.base_v2 longformer_qa_base_4096_finetuned_squadv2 Question Answering English LongformerForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_21iridescent roberta_qa_RoBERTa_base_finetuned_squad2_lwt Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_AnonymousSub roberta_qa_roberta_base_squad2.0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_PremalMatalia roberta_qa_roberta_base_best_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_Shappey roberta_qa_roberta_base_QnA_squad2_trained Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.distil_bert.base_cased distilbert_base_cased_qa_squad2 Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.distil_bert.base distilbert_qa_base_squad2_custom_dataset Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squadv2.biobert.cased.by_ptnv-s bert_qa_biobert_squad2_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large_uncased.by_deepset bert_qa_bert_large_uncased_whole_word_masking_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large_uncased_v2.by_madlag bert_qa_bert_large_uncased_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.large_uncased_v2_x2.15_f83.2_d25_hybrid.by_madlag bert_qa_bert_large_uncased_wwm_squadv2_x2.15_f83.2_d25_hybrid_v1 Question Answering English BertForQuestionAnswering
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en.answer_question.squadv2.bert.medium_v2 bert_qa_bert_medium_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.mini_lm_base_uncased bert_qa_minilm_uncased_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.small.by_mrm8488 bert_qa_bert_small_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.small_v2.by_mrm8488 bert_qa_bert_small_2_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_.by_mrm8488 bert_qa_bert_tiny_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_Teepika roberta_qa_roberta_base_squad2_finetuned_selqa Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_fadhilarkan distilbert_qa_fadhilarkan_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_v3.by_mrm8488 bert_qa_bert_tiny_3_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_v4.by_mrm8488 bert_qa_bert_tiny_4_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_v5.by_mrm8488 bert_qa_bert_tiny_5_finetuned_squadv2 Question Answering English BertForQuestionAnswering
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en.answer_question.squadv2.bert.uncased_2l_512d_a8a_512d bert_qa_bert_uncased_L_2_H_512_A_8_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.uncased_4l_256d_a4a_256d bert_qa_bert_uncased_L_4_H_256_A_4_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.uncased_4l_512d_a8a_512d bert_qa_bert_uncased_L_4_H_512_A_8_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.uncased_4l_768d_a12a_768d bert_qa_bert_uncased_L_4_H_768_A_12_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.uncased_6l_128d_a2a_128d bert_qa_bert_uncased_L_6_H_128_A_2_squad2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.biobert.cased.by_clagator bert_qa_biobert_squad2_cased Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.bert.tiny_v2.by_mrm8488 bert_qa_bert_tiny_2_finetuned_squadv2 Question Answering English BertForQuestionAnswering
en.answer_question.squadv2.xlm_roberta.base_24465524.by_teacookies xlm_roberta_qa_autonlp_roberta_base_squad2_24465524 Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_avioo1 roberta_qa_avioo1_roberta_base_squad2_finetuned_squad Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.base.by_deepset roberta_base_qa_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.distilled_base_128d_32d_v2 roberta_qa_distilrobert_base_squadv2_328seq_128stride_test Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.distilled_base_v2 roberta_qa_distilroberta_base_squad_v2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.emanuals.by_AnonymousSub roberta_qa_EManuals_RoBERTa_squad2.0 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.large.by_Salesforce roberta_qa_qaconv_roberta_large_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.large.by_deepset roberta_qa_roberta_large_squad2_hp Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.large.by_navteca roberta_qa_roberta_large_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.large.by_phiyodr roberta_qa_roberta_large_finetuned_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.tiny.by_deepset roberta_qa_tinyroberta_squad2 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.roberta.tiny.v2.by_deepset roberta_qa_tinyroberta_squad2_step1 Question Answering English RoBertaForQuestionAnswering
en.answer_question.squadv2.scibert.uncased_v2 bert_qa_scibert_scivocab_uncased_squad_v2 Question Answering English BertForQuestionAnswering
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en.answer_question.bert.by_manav bert_qa_causal_qa Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_mezes bert_qa_eauction_section_parsing_from_pretrained Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_motiondew bert_qa_bert_finetuned_lr2_e5_b16_ep2 Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_mrm8488 bert_qa_ManuERT_for_xqua Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_nlpunibo bert_qa_bert Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_nvkha bert_qa_bert_qa_vi_nvkha Question Answering English BertForQuestionAnswering
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en.answer_question.bert.by_voidful bert_qa_question_answering_zh_voidful Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_z-uo bert_qa_bert_qasper Question Answering English BertForQuestionAnswering
en.answer_question.bert.distilled_base_uncased bert_qa_distilbert_base_uncased_finetuned_custom Question Answering English BertForQuestionAnswering
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en.answer_question.bert.large.by_atharvamundada99 bert_qa_bert_large_question_answering_finetuned_legal Question Answering English BertForQuestionAnswering
en.answer_question.bert.large.by_ricardo-filho bert_qa_bert_large_faquad Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_Rocketknight1 bert_qa_bert_finetuned_qa Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_LenaSchmidt bert_qa_no_need_to_name_this Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_HankyStyle bert_qa_Multi_ling_BERT Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_ForutanRad bert_qa_bert_fa_QA_v1 Question Answering English BertForQuestionAnswering
en.answer_qu estion.mqa_cls.bert.by_xraychen bert_qa_mqa_cls Question Answering English BertForQuestionAnswering
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en.answer_question.albert.by_SalmanMo albert_qa_QA_1e Question Answering English AlbertForQuestionAnswering
en.answer_question.albert.by_nlpunibo albert_qa_nlpunibo Question Answering English AlbertForQuestionAnswering
en.answer_question.albert.by_rowan1224 albert_qa_slp Question Answering English AlbertForQuestionAnswering
en.answer_question.albert.by_saburbutt albert_qa_generic Question Answering English AlbertForQuestionAnswering
en.answer_question.albert.xl albert_qa_xlarge_finetuned Question Answering English AlbertForQuestionAnswering
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en.answer_question.bert.base.by_peggyhuang bert_qa_finetune_bert_base_v1 Question Answering English BertForQuestionAnswering
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en.answer_question.bert.base_cased.by_nntadotzip bert_qa_bert_base_cased_IUChatbot_ontologyDts Question Answering English BertForQuestionAnswering
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en.answer_question.bert.base_uncased.by_machine2049 bert_qa_bert_base_uncased_finetuned_duorc_bert Question Answering English BertForQuestionAnswering
en.answer_question.bert.base_uncased.by_peggyhuang bert_qa_bert_base_uncased_coqa Question Answering English BertForQuestionAnswering
en.answer_question.bert.base_uncased.by_vanadhi bert_qa_bert_base_uncased_fiqa_flm_sq_flit Question Answering English BertForQuestionAnswering
en.answer_question.bert.base_v2 bert_qa_finetune_bert_base_v2 Question Answering English BertForQuestionAnswering
en.answer_question.bert.base_v3.by_peggyhuang bert_qa_finetune_bert_base_v3 Question Answering English BertForQuestionAnswering
en.answer_question.bert.by_Danastos bert_qa_nq_bert_el_Danastos Question Answering English BertForQuestionAnswering
en.answer_question.bert.base.by_xraychen bert_qa_mqa_baseline Question Answering English BertForQuestionAnswering
en.answer_question.distil_bert.base.by_leemii18 distilbert_qa_robustqa_baseline_02 Question Answering English DistilBertForQuestionAnswering
en.answer_question.bert.large_uncased bert_qa_bert_large_uncased_finetuned_docvqa Question Answering English BertForQuestionAnswering
en.answer_question.bert.multilingual_english_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_english Question Answering English BertForQuestionAnswering
en.answer_question.chaii.xlm_roberta.base.by_SauravMaheshkar xlm_roberta_qa_xlm_roberta_base_chaii Question Answering English XlmRoBertaForQuestionAnswering
en.answer_question.chaii.xlm_roberta.base.by_tyqiangz xlm_roberta_qa_xlm_roberta_base_finetuned_chaii Question Answering English XlmRoBertaForQuestionAnswering
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en.answer_question.conll.distil_bert.base_uncased distilbert_qa_base_uncased_qa_with_ner Question Answering English DistilBertForQuestionAnswering
en.answer_question.cord19.bert.by_JAlexis bert_qa_Bertv1_fine Question Answering English BertForQuestionAnswering
en.answer_question.cord19.bert.small bert_qa_bert_small_cord19qa Question Answering English BertForQuestionAnswering
en.answer_question.cord19.prueba_bert.by_JAlexis bert_qa_PruebaBert Question Answering English BertForQuestionAnswering
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en.answer_question.covid.distil_bert.b.by_rahulkuruvilla distilbert_qa_COVID_DistilBERTb Question Answering English DistilBertForQuestionAnswering
en.answer_question.covid.distil_bert.c.by_rahulkuruvilla distilbert_qa_COVID_DistilBERTc Question Answering English DistilBertForQuestionAnswering
en.answer_question.covid.longformer longformer_qa_covid Question Answering English LongformerForQuestionAnswering
en.answer_question.covid_bert.a.by_rahulkuruvilla bert_qa_COVID_BERTa Question Answering English BertForQuestionAnswering
en.answer_question.covid_bert.b.by_rahulkuruvilla bert_qa_COVID_BERTb Question Answering English BertForQuestionAnswering
en.answer_question.covid_bert.c.by_rahulkuruvilla bert_qa_COVID_BERTc Question Answering English BertForQuestionAnswering
en.answer_question.cuad.roberta.base.by_Gam roberta_qa_roberta_base_finetuned_cuad Question Answering English RoBertaForQuestionAnswering
en.answer_question.cuad.roberta.base.by_Rakib roberta_qa_roberta_base_on_cuad Question Answering English RoBertaForQuestionAnswering
en.answer_question.cuad.roberta.base.by_akdeniz27 roberta_qa_akdeniz27_roberta_base_cuad Question Answering English RoBertaForQuestionAnswering
en.answer_question.cuad.roberta.base.by_marshmellow77 roberta_qa_marshmellow77_roberta_base_cuad Question Answering English RoBertaForQuestionAnswering
en.answer_question.cuad.roberta.large roberta_qa_roberta_large_cuad Question Answering English RoBertaForQuestionAnswering
en.answer_question.chaii.roberta.base roberta_qa_roberta_base_chaii Question Answering English RoBertaForQuestionAnswering
en.answer_question.chaii.electra.base electra_qa_base_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.distil_bert.base_uncased distilbert_qa_base_uncased_distilled_chaii Question Answering English DistilBertForQuestionAnswering
en.answer_question.chaii.distil_bert.base_cased distilbert_qa_base_cased_distilled_chaii Question Answering English DistilBertForQuestionAnswering
en.answer_question.bert.multilingual_german_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_german Question Answering English BertForQuestionAnswering
en.answer_question.bert.multilingual_hindi_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_hindi Question Answering English BertForQuestionAnswering
en.answer_question.bert.multilingual_spanish_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_spanish Question Answering English BertForQuestionAnswering
en.answer_question.bert.multilingual_vietnamese_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_vietnamese Question Answering English BertForQuestionAnswering
en.answer_question.bert.sim.by_xraychen bert_qa_mqa_sim Question Answering English BertForQuestionAnswering
en.answer_question.bert.unsupsim.by_xraychen bert_qa_mqa_unsupsim Question Answering English BertForQuestionAnswering
en.answer_question.bert.vi_infovqa.base_uncased.by_tiennvcs bert_qa_bert_base_uncased_finetuned_vi_infovqa Question Answering English BertForQuestionAnswering
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en.answer_question.bert.zero_shot.by_fractalego bert_qa_fewrel_zero_shot Question Answering English BertForQuestionAnswering
en.answer_question.bert.multilingual_arabic_tuned_base_cased.by_bhavikardeshna bert_qa_multilingual_bert_base_cased_arabic Question Answering English BertForQuestionAnswering
en.answer_question.bert.zero_shot.by_krinal214 bert_qa_zero_shot Question Answering English BertForQuestionAnswering
en.answer_question.bio_medical.bert.base bert_qa_biomedical_slot_filling_reader_base Question Answering English BertForQuestionAnswering
en.answer_question.bio_medical.bert.large bert_qa_biomedical_slot_filling_reader_large Question Answering English BertForQuestionAnswering
en.answer_question.biobert bert_qa_biobert_bioasq Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.base_cased bert_qa_bert_base_cased_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.cased bert_qa_bert_multi_cased_finetuned_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.large_uncased_uncased_whole_word_masking.by_SauravMaheshkar bert_qa_bert_large_uncased_whole_word_masking_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.large_uncased_uncased_whole_word_masking_finetuned.by_SauravMaheshkar bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.multilingual_base_cased bert_qa_bert_base_multilingual_cased_finetuned_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.bert.uncased bert_qa_bert_multi_uncased_finetuned_chaii Question Answering English BertForQuestionAnswering
en.answer_question.chaii.distil_bert distilbert_qa_multi_finetuned_for_xqua_on_chaii Question Answering English DistilBertForQuestionAnswering
en.answer_question.bio_clinical.bert bert_qa_sagemaker_BioclinicalBERT_ADR Question Answering English BertForQuestionAnswering
en.answer_question.roberta.by_LucasS roberta_qa_robertaBaseABSA Question Answering English RoBertaForQuestionAnswering
en.answer_question.korquad.bert.multilingual_base_cased.by_eliza-dukim bert_qa_bert_base_multilingual_cased_korquad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.roberta.by_Nakul24 roberta_qa_RoBERTa_emotion_extraction Question Answering English RoBertaForQuestionAnswering
en.answer_question.squad.bert.large.by_rsvp-ai bert_qa_bertserini_bert_large_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large.by_ruselkomp bert_qa_sbert_large_nlu_ru_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_cased bert_qa_bert_large_cased_whole_word_masking_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_Graphcore bert_qa_Graphcore_bert_large_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_haddadalwi bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_howey bert_qa_howey_bert_large_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_internetoftim bert_qa_internetoftim_bert_large_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_ofirzaf bert_qa_ofirzaf_bert_large_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased.by_uploaded by huggingface bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased_sparse_80_1x4_block_pruneofa.by_Intel bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.large_uncased_sparse_90_unstructured.by_Intel bert_qa_bert_large_uncased_squadv1.1_sparse_90_unstructured Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.medium.by_anas-awadalla bert_qa_bert_medium_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.medium.by_mrm8488 bert_qa_bert_medium_wrslb_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.medium_finetuned.by_anas-awadalla bert_qa_bert_medium_pretrained_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.mini_lm_base_uncased bert_qa_MiniLM_L12_H384_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.ms_tuned.base.by_zhufy bert_qa_squad_ms_bert_base Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.multilingual_base_cased.by_Paul-Vinh bert_qa_Paul_Vinh_bert_base_multilingual_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.multilingual_base_cased.by_salti bert_qa_salti_bert_base_multilingual_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.multilingual_base_cased.by_vanichandna bert_qa_bert_base_multilingual_cased_finetuned_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.multilingual_base_uncased bert_qa_bert_base_multilingual_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.sl256.by_vuiseng9 bert_qa_bert_l_squadv1.1_sl256 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.distilled_base_uncased.by_kamilali bert_qa_kamilali_distilbert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.distilled_base_uncased.by_juliusco bert_qa_juliusco_distilbert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.distilled_base_uncased.by_huggingface bert_qa_prunebert_base_uncased_6_finepruned_w_distil_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.cased bert_qa_bert_multi_cased_squad_sv_marbogusz Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Ghost1 bert_qa_bert_finetuned_squad1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Harsit bert_qa_Harsit_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_KevinChoi bert_qa_KevinChoi_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Kutay bert_qa_fine_tuned_squad_aip Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Laikokwei bert_qa_Laikokwei_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Neulvo bert_qa_Neulvo_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_andresestevez bert_qa_andresestevez_bert_finetuned_squad_accelerate Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_ankitkupadhyay bert_qa_ankitkupadhyay_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_datauma bert_qa_datauma_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_hendrixcosta bert_qa_bertimbau_squad1.1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.sl384.by_vuiseng9 bert_qa_bert_l_squadv1.1_sl384 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_huggingface-course bert_qa_huggingface_course_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_maroo93 bert_qa_squad1.1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_mrbalazs5 bert_qa_mrbalazs5_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_mrp bert_qa_mrp_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_nickmuchi bert_qa_nickmuchi_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_peterhsu bert_qa_tf_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_ruselkomp bert_qa_tests_finetuned_squad_test_bert Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_spacemanidol bert_qa_neuralmagic_bert_squad_12layer_0sparse Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_stevemobs bert_qa_bert_finetuned_squad_pytorch Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_vanichandna bert_qa_muril_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_youngjae bert_qa_youngjae_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_jatinshah bert_qa_jatinshah_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_FardinSaboori bert_qa_FardinSaboori_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.small.by_anas-awadalla bert_qa_bert_small_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.small_finetuned.by_anas-awadalla bert_qa_bert_small_pretrained_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_ParulChaudhari distilbert_qa_ParulChaudhari_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Plimpton distilbert_qa_Plimpton_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Raphaelg9 distilbert_qa_Raphaelg9_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Rocketknight1 distilbert_qa_Rocketknight1_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_SEISHIN distilbert_qa_SEISHIN_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Shashidhar distilbert_qa_Shashidhar_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Sourabh714 distilbert_qa_Sourabh714_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_SupriyaArun distilbert_qa_SupriyaArun_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Thitaree distilbert_qa_Thitaree_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Tianle distilbert_qa_Tianle_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_V3RX2000 distilbert_qa_V3RX2000_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Wiam distilbert_qa_Wiam_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squad.distil_bert.base_uncased.by_andi611 distilbert_qa_andi611_base_uncased_squad Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squad.distil_bert.base_uncased.by_arvalinno distilbert_qa_arvalinno_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
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en.answer_question.squad.distil_bert.base_uncased.by_FOFer distilbert_qa_FOFer_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
en.answer_question.squad.distil_bert.base_uncased.by_Firat distilbert_qa_Firat_base_uncased_finetuned_squad Question Answering English DistilBertForQuestionAnswering
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en.answer_question.span_bert.by_Nakul24 bert_qa_Spanbert_emotion_extraction Question Answering English BertForQuestionAnswering
en.answer_question.span_bert.by_manishiitg bert_qa_spanbert_recruit_qa Question Answering English BertForQuestionAnswering
en.answer_question.span_bert.large bert_qa_spanbert_large_recruit_qa Question Answering English BertForQuestionAnswering
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en.answer_question.squad.bert.accelerate.by_peterhsu bert_qa_peterhsu_bert_finetuned_squad_accelerate Question Answering English BertForQuestionAnswering
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en.answer_question.squad.bert.base.by_rsvp-ai bert_qa_bertserini_bert_base_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_vuiseng9 bert_qa_vuiseng9_bert_base_uncased_squad Question Answering English BertForQuestionAnswering
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en.answer_question.squad.bert.base_uncased.by_victoraavila bert_qa_victoraavila_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased_l3.by_howey bert_qa_bert_base_uncased_squad_L3 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased_seed_42 bert_qa_bert_base_uncased_few_shot_k_16_finetuned_squad_seed_42 Question Answering English BertForQuestionAnswering
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en.answer_question.squad.bert.base_uncased_x1.96_f88.3_d27_hybrid_filled_opt_v1.by_madlag bert_qa_bert_base_uncased_squadv1_x2.01_f89.2_d30_hybrid_rewind_opt_v1 Question Answering English BertForQuestionAnswering
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en.answer_question.squad.bert.base_uncased_x2.32_f86.6_d15_hybrid_v1.by_madlag bert_qa_bert_base_uncased_squadv1_x2.44_f87.7_d26_hybrid_filled_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased_x2.44_f87.7_d26_hybrid_filled_v1.by_madlag bert_qa_bert_base_uncased_squad1.1_block_sparse_0.07_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.by_Alexander-Learn bert_qa_Alexander_Learn_bert_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased_l6.by_howey bert_qa_bert_base_uncased_squad_L6 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_tli8hf bert_qa_unqover_bert_base_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased_1_block_sparse_0.13_v1.by_madlag bert_qa_bert_base_uncased_squadv1_x1.84_f88.7_d36_hybrid_filled_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_madlag bert_qa_bert_base_uncased_squad_v1_sparse0.25 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base.by_vuiseng9 bert_qa_bert_base_squadv1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base.by_xraychen bert_qa_squad_baseline Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base.by_zhufy bert_qa_squad_en_bert_base Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_srmukundb bert_qa_srmukundb_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_Seongkyu bert_qa_Seongkyu_bert_base_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_SreyanG-NVIDIA bert_qa_SreyanG_NVIDIA_bert_base_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_andresestevez bert_qa_andresestevez_bert_base_cased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_batterydata bert_qa_bert_base_cased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_ncduy bert_qa_bert_base_cased_finetuned_squad_test Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.1.1_block_sparse_0.32_v1.by_madlag bert_qa_bert_base_uncased_squad1.1_block_sparse_0.32_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_cased.by_KB bert_qa_bert_base_swedish_cased_squad_experimental Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_Intel bert_qa_bert_base_uncased_squadv1.1_sparse_80_1x4_block_pruneofa Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_lewtun bert_qa_bert_base_uncased_finetuned_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_HomayounSadri bert_qa_HomayounSadri_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_kaporter bert_qa_kaporter_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_jgammack bert_qa_MTL_bert_base_uncased_ww_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_csarron bert_qa_csarron_bert_base_uncased_squad_v1 Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_jimypbr bert_qa_jimypbr_bert_base_uncased_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_bdickson bert_qa_bdickson_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_Tianle bert_qa_Tianle_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_SupriyaArun bert_qa_SupriyaArun_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
en.answer_question.squad.bert.base_uncased.by_SreyanG-NVIDIA bert_qa_SreyanG_NVIDIA_bert_base_uncased_finetuned_squad Question Answering English BertForQuestionAnswering
fi.answer_question.xlm_roberta xlm_roberta_qa_ADDI_FI_XLM_R Question Answering Finnish XlmRoBertaForQuestionAnswering
fr.answer_question.squad.xlmr_roberta.base xlm_roberta_qa_xlmr_base_texas_squad_fr_fr_saattrupdan Question Answering French XlmRoBertaForQuestionAnswering
de.answer_question.squad_spanish_tuned.xlmr_roberta.base.by_saattrupdan xlm_roberta_qa_xlmr_base_texas_squad_es_es_saattrupdan Question Answering German XlmRoBertaForQuestionAnswering
de.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_german Question Answering German XlmRoBertaForQuestionAnswering
de.answer_question.squadv2.electra.base electra_qa_base_squad2 Question Answering German BertForQuestionAnswering
de.answer_question.squadv2.bert bert_qa_bert_multi_english_german_squad2 Question Answering German BertForQuestionAnswering
de.answer_question.squad_de_tuned.xlmr_roberta.base.by_saattrupdan xlm_roberta_qa_xlmr_base_texas_squad_de_de_saattrupdan Question Answering German XlmRoBertaForQuestionAnswering
de.answer_question.xlm_roberta xlm_roberta_qa_ADDI_DE_XLM_R Question Answering German XlmRoBertaForQuestionAnswering
de.answer_question.electra.distilled_base electra_qa_g_base_germanquad_distilled Question Answering German BertForQuestionAnswering
de.answer_question.electra.base electra_qa_g_base_germanquad Question Answering German BertForQuestionAnswering
de.answer_question.electra electra_qa_German_question_answer Question Answering German BertForQuestionAnswering
de.answer_question.bert bert_qa_GBERTQnA Question Answering German BertForQuestionAnswering
de.answer_question.electra.large electra_qa_g_large_germanquad Question Answering German BertForQuestionAnswering
he.answer_question.squad.bert bert_qa_hebert_finetuned_hebrew_squad Question Answering Hebrew BertForQuestionAnswering
hi.answer_question.xlm_roberta xlm_roberta_qa_autonlp_hindi_question_answering_23865268 Question Answering Hindi XlmRoBertaForQuestionAnswering
hi.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_hindi Question Answering Hindi XlmRoBertaForQuestionAnswering
hu.answer_question.squad.bert bert_qa_huBert_fine_tuned_hungarian_squadv1 Question Answering Hungarian BertForQuestionAnswering
is.answer_question.squad.roberta roberta_qa_icebert_texas_squad_is_saattrupdan Question Answering Icelandic RoBertaForQuestionAnswering
is.answer_question.squad.xlmr_roberta.base xlm_roberta_qa_xlmr_base_texas_squad_is_is_saattrupdan Question Answering Icelandic XlmRoBertaForQuestionAnswering
is.answer_question.xlmr_roberta xlm_roberta_qa_XLMr_ENIS_QA_Is Question Answering Icelandic XlmRoBertaForQuestionAnswering
id.answer_question.indo_bert bert_qa_Indobert_QA Question Answering Indonesian BertForQuestionAnswering
it.answer_question.squad.bert bert_qa_bert_italian_finedtuned_squadv1_it_alfa Question Answering Italian BertForQuestionAnswering
it.answer_question.squad.bert.base_uncased bert_qa_bert_base_italian_uncased_squad_it_antoniocappiello Question Answering Italian BertForQuestionAnswering
it.answer_question.squad.bert.xxl_cased bert_qa_squad_xxl_cased_hub1 Question Answering Italian BertForQuestionAnswering
it.answer_question.xlm_roberta xlm_roberta_qa_ADDI_IT_XLM_R Question Answering Italian XlmRoBertaForQuestionAnswering
ja.answer_question.wikipedia.bert.base bert_qa_base_japanese_wikipedia_ud_head Question Answering Japanese BertForQuestionAnswering
ja.answer_question.wikipedia.bert.large bert_qa_large_japanese_wikipedia_ud_head Question Answering Japanese BertForQuestionAnswering
ko.answer_question.korquad.electra.small electra_qa_small_v3_finetuned_korquad Question Answering Korean BertForQuestionAnswering
ko.answer_question.korquad.electra.base_v2_384.by_monologg electra_qa_base_v2_finetuned_korquad_384 Question Answering Korean BertForQuestionAnswering
ko.answer_question.korquad.electra.base_v2.by_monologg electra_qa_base_v2_finetuned_korquad Question Answering Korean BertForQuestionAnswering
ko.answer_question.korquad.electra.base electra_qa_base_v3_finetuned_korquad Question Answering Korean BertForQuestionAnswering
ko.answer_question.klue.electra.base.by_seongju electra_qa_klue_mrc_base Question Answering Korean BertForQuestionAnswering
ko.answer_question.klue.bert.base.by_bespin-global bert_qa_bespin_global_klue_bert_base_mrc Question Answering Korean BertForQuestionAnswering
ko.answer_question.klue.bert.base_aihub.by_bespin-global bert_qa_klue_bert_base_aihub_mrc Question Answering Korean BertForQuestionAnswering
ko.answer_question.klue.bert.base.by_ainize bert_qa_ainize_klue_bert_base_mrc Question Answering Korean BertForQuestionAnswering
ko.answer_question.electra electra_qa_long Question Answering Korean BertForQuestionAnswering
ko.answer_question.klue.electra.base.by_obokkkk electra_qa_base_v3_discriminator_finetuned_klue_v4 Question Answering Korean BertForQuestionAnswering
el.answer_question.bert bert_qa_qacombination_bert_el_Danastos Question Answering Modern Greek (1453-) BertForQuestionAnswering
pl.answer_question.squad.bert.multilingual_base_cased bert_qa_bert_base_multilingual_cased_finetuned_polish_squad1 Question Answering Polish BertForQuestionAnswering
pl.answer_question.squadv2.bert.multilingual_base_cased bert_qa_bert_base_multilingual_cased_finetuned_polish_squad2 Question Answering Polish BertForQuestionAnswering
pt.answer_question.squad.distil_bert distilbert_qa_multi_finedtuned_squad Question Answering Portuguese DistilBertForQuestionAnswering
pt.answer_question.squad.bert.large_cased bert_qa_bert_large_cased_squad_v1.1_portuguese Question Answering Portuguese BertForQuestionAnswering
pt.answer_question.squad.biobert bert_qa_bioBERTpt_squad_v1.1_portuguese Question Answering Portuguese BertForQuestionAnswering
pt.answer_question.squad.bert.base_cased.by_mrm8488 bert_qa_bert_base_portuguese_cased_finetuned_squad_v1_pt_mrm8488 Question Answering Portuguese BertForQuestionAnswering
pt.answer_question.squad.bert.base_cased.by_pierreguillou bert_qa_bert_base_cased_squad_v1.1_portuguese Question Answering Portuguese BertForQuestionAnswering
ru.answer_question.distil_bert distilbert_qa_model_QA_5_epoch_RU Question Answering Russian DistilBertForQuestionAnswering
si.answer_question.bert.base bert_qa_bert_base_sinhala_qa Question Answering Sinhala, Sinhalese BertForQuestionAnswering
sv.answer_question.squadv2.bert.base bert_qa_bert_base_swedish_squad2 Question Answering Swedish BertForQuestionAnswering
sv.answer_question.xlmr_roberta.large xlm_roberta_qa_xlmr_large_qa_sv_sv_m3hrdadfi Question Answering Swedish XlmRoBertaForQuestionAnswering
ta.answer_question.squad.xlm_roberta xlm_roberta_qa_xlm_roberta_squad_tamil Question Answering Tamil XlmRoBertaForQuestionAnswering
th.answer_question.xquad_squad.bert.cased bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad Question Answering Thai BertForQuestionAnswering
th.answer_question.xquad.multi_lingual_bert.base bert_qa_xquad_th_mbert_base Question Answering Thai BertForQuestionAnswering
th.answer_question.bert.multilingual_base_cased bert_qa_bert_base_multilingual_cased_finetune_qa Question Answering Thai BertForQuestionAnswering
th.answer_question.squadv2.xlm_roberta.base xlm_roberta_qa_thai_xlm_roberta_base_squad2 Question Answering Thai XlmRoBertaForQuestionAnswering
tr.answer_question.squad.electra electra_qa_enelpi_squad Question Answering Turkish BertForQuestionAnswering
tr.answer_question.xlm_roberta xlm_roberta_qa_XLM_Turkish Question Answering Turkish XlmRoBertaForQuestionAnswering
tr.answer_question.squadv2.electra.base_v2 electra_qa_base_discriminator_finetuned_squadv2 Question Answering Turkish BertForQuestionAnswering
tr.answer_question.squad.electra.base electra_qa_base_discriminator_finetuned_squadv1 Question Answering Turkish BertForQuestionAnswering
tr.answer_question.squad.bert.base bert_qa_bert_base_turkish_squad Question Answering Turkish BertForQuestionAnswering
tr.answer_question.bert.base_uncased bert_qa_loodos_bert_base_uncased_QA_fine_tuned Question Answering Turkish BertForQuestionAnswering
tr.answer_question.electra electra_qa_turkish Question Answering Turkish BertForQuestionAnswering
tr.answer_question.bert.distilled bert_qa_distilbert_tr_q_a Question Answering Turkish BertForQuestionAnswering
tr.answer_question.bert.by_yunusemreemik bert_qa_logo_qna_model Question Answering Turkish BertForQuestionAnswering
tr.answer_question.bert.by_lserinol bert_qa_bert_turkish_question_answering Question Answering Turkish BertForQuestionAnswering
tr.answer_question.electra.small_uncased electra_qa_small_turkish_uncased_discriminator_finetuned Question Answering Turkish BertForQuestionAnswering
uk.answer_question.xlmr_roberta xlmroberta_qa_ukrainian Question Answering Ukrainian XlmRoBertaForQuestionAnswering
vi.answer_question.xlm_roberta.large xlm_roberta_qa_xlm_roberta_large_vi_qa Question Answering Vietnamese XlmRoBertaForQuestionAnswering
ar.answer_question.bert bert_qa_arap_qa_bert Question Answering Arabic BertForQuestionAnswering
ar.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_arabic Question Answering Arabic XlmRoBertaForQuestionAnswering
ar.answer_question.tydiqa.electra.base electra_qa_ara_base_artydiqa Question Answering Arabic BertForQuestionAnswering
ar.answer_question.squad_arcd.electra.base electra_qa_AraElectra_base_finetuned_ARCD Question Answering Arabic BertForQuestionAnswering
ar.answer_question.squad_arcd.electra.768d electra_qa_araElectra_SQUAD_ARCD_768 Question Answering Arabic BertForQuestionAnswering
ar.answer_question.xlm_roberta.large xlm_roberta_qa_xlm_roberta_large_arabic_qa Question Answering Arabic XlmRoBertaForQuestionAnswering
ar.answer_question.electra electra_qa_AraELECTRA_discriminator_SOQAL Question Answering Arabic BertForQuestionAnswering
ar.answer_question.bert.v2 bert_qa_arap_qa_bert_v2 Question Answering Arabic BertForQuestionAnswering
ar.answer_question.bert.large_v2 bert_qa_arap_qa_bert_large_v2 Question Answering Arabic BertForQuestionAnswering
ar.answer_question.squad_arcd.electra electra_qa_araElectra_SQUAD_ARCD Question Answering Arabic BertForQuestionAnswering
zh.answer_question.mac_bert.large bert_qa_chinese_pretrain_mrc_macbert_large Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.multilingual_base_cased bert_qa_multilingual_bert_base_cased_chinese Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.large.by_qalover bert_qa_chinese_pert_large_open_domain_mrc Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.large.by_luhua bert_qa_chinese_pretrain_mrc_roberta_wwm_ext_large Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.large.by_hfl bert_qa_chinese_pert_large_mrc Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.base.by_uer bert_qa_roberta_base_chinese_extractive_qa Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.by_jackh1995 bert_qa_bert_chinese_finetuned Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.base.by_liam168 bert_qa_qa_roberta_base_chinese_extractive Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.base.by_jackh1995 bert_qa_roberta_base_chinese_extractive_qa_scratch Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.base.by_hfl bert_qa_chinese_pert_base_mrc Question Answering Chinese BertForQuestionAnswering
zh.answer_question.squad.bert.base bert_qa_bert_base_chinese_finetuned_squad_colab Question Answering Chinese BertForQuestionAnswering
zh.answer_question.bert.by_yechen bert_qa_question_answering_chinese Question Answering Chinese BertForQuestionAnswering
zh.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_chinese Question Answering Chinese XlmRoBertaForQuestionAnswering
fa.answer_question.bert.base bert_qa_bert_base_fa_qa Question Answering Persian BertForQuestionAnswering
fa.answer_question.xlm_roberta.large xlm_roberta_qa_xlm_roberta_large_fa_qa Question Answering Persian XlmRoBertaForQuestionAnswering
fa.answer_question.xlmr_roberta.large xlmroberta_qa_xlmr_large Question Answering Persian XlmRoBertaForQuestionAnswering
sw.answer_question.tydiqa.xlm_roberta.base xlm_roberta_qa_afriberta_base_finetuned_tydiqa Question Answering Swahili (macrolanguage) XlmRoBertaForQuestionAnswering
vn.answer_question.xlm_roberta.base xlm_roberta_qa_xlm_roberta_base_vietnamese Question Answering nan XlmRoBertaForQuestionAnswering
xx.answer_question.chaii.xlm_roberta xlm_roberta_qa_xlm_roberta_qa_chaii Question Answering nan XlmRoBertaForQuestionAnswering
xx.answer_question.xquad.bert.uncased bert_qa_bert_multi_uncased_finetuned_xquadv1 Question Answering nan BertForQuestionAnswering
xx.answer_question.xquad.bert.cased bert_qa_bert_multi_cased_finetuned_xquadv1 Question Answering nan BertForQuestionAnswering
xx.answer_question.xlm_roberta.distilled xlm_roberta_qa_distill_xlm_mrc Question Answering nan XlmRoBertaForQuestionAnswering
xx.answer_question.tydiqa.multi_lingual_bert bert_qa_Part_1_mBERT_Model_E1 Question Answering nan BertForQuestionAnswering
xx.answer_question.tydiqa.bert bert_qa_telugu_bertu_tydiqa Question Answering nan BertForQuestionAnswering
xx.answer_question.xquad_tydiqa.bert.cased bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp Question Answering nan BertForQuestionAnswering
xx.answer_question.squad.distil_bert._en_de_es_vi_zh_tuned.by_ZYW distilbert_qa_squad_en_de_es_vi_zh_model Question Answering nan DistilBertForQuestionAnswering
xx.answer_question.roberta roberta_qa_ft_lr_cu_leolin12345 Question Answering nan RoBertaForQuestionAnswering
xx.answer_question.distil_bert.vi_zh_es_tuned.by_ZYW distilbert_qa_en_de_vi_zh_es_model Question Answering nan DistilBertForQuestionAnswering
xx.answer_question.distil_bert.en_de_tuned.by_ZYW distilbert_qa_en_de_model Question Answering nan DistilBertForQuestionAnswering
xx.answer_question.distil_bert.en_de_es_tuned.by_ZYW distilbert_qa_en_de_es_model Question Answering nan DistilBertForQuestionAnswering
xx.answer_question.squad.distil_bert.en_de_es_tuned.by_ZYW distilbert_qa_squad_en_de_es_model Question Answering nan DistilBertForQuestionAnswering

Minor Improvements

  • IOB Schema Detection for Tokenclassifiers and adding NER Converting in those cases
  • Tweaks in column name generation of most annotators

Bug Fixes

  • fixed bug in multi lang parsing
  • fixed bug for Normalizers
  • fixed bug in fetching metadata for resolvers
  • fixed bug in deducting outputlevel and inferring output columns
  • fixed broken nlp_refs

NLU Version 3.4.4

600 new models with over 75 new languages including Ancient,Dead and Extinct languages, 155 languages total covered, 400% Tokenizer Speedup, 18x USE-Embeddings GPU speedup in John Snow Labs NLU 3.4.4

We are very excited to announce NLU 3.4.4 has been released with over 600 new model, over 75 new languages and 155 languages covered in total, 400% speedup for tokenizers and 18x speedup of UniversalSentenceEncoder on GPU. On the general NLP side we have transformer based Embeddings and Token Classifiers powered by state of the art CamemBertEmbeddings and DeBertaForTokenClassification based architectures as well as various new models for
Historical, Ancient,Dead, Extinct, Genetic and Constructed languages like Old Church Slavonic, Latin, Sanskrit, Esperanto, Volapük, Coptic, Nahuatl, Ancient Greek (to 1453), Old Russian. On the healthcare side we have Portuguese De-identification Models, have NER models for Gene detection and finally RxNorm Sentence resolution model for mapping and extracting pharmaceutical actions (e.g. analgesic, hypoglycemic) as well as treatments (e.g. backache, diabetes).

General NLP Models

All general NLP models

First time language models covered

The languages for these models are covered for the very first time ever by NLU.

Number Language Name(s) NLU Reference Spark NLP Reference Task Annotator Class ISO-639-1 ISO-639-2/639-5 ISO-639-3 Scope Language Type
0 Sanskrit sa.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel sa san san Individual Ancient
1 Sanskrit sa.lemma lemma_vedic Lemmatization LemmatizerModel sa san san Individual Ancient
2 Sanskrit sa.pos pos_vedic Part of Speech Tagging PerceptronModel sa san san Individual Ancient
3 Sanskrit sa.stopwords stopwords_iso Stop Words Removal StopWordsCleaner sa san san Individual Ancient
4 Volapük vo.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel vo vol vol Individual Constructed
5 Nahuatl languages nah.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nah nan Collective Genetic
6 Aragonese an.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel an arg arg Individual Living
7 Assamese as.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel as asm asm Individual Living
8 Asturian, Asturleonese, Bable, Leonese ast.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan ast ast Individual Living
9 Bashkir ba.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel ba bak bak Individual Living
10 Bavarian bar.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan bar Individual Living
11 Bishnupriya bpy.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan bpy Individual Living
12 Burmese my.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel my 639-2/T: mya639-2/B: bur mya Individual Living
13 Cebuano ceb.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan ceb ceb Individual Living
14 Central Bikol bcl.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan bcl Individual Living
15 Chechen ce.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel ce che che Individual Living
16 Chuvash cv.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel cv chv chv Individual Living
17 Corsican co.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel co cos cos Individual Living
18 Dhivehi, Divehi, Maldivian dv.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel dv div div Individual Living
19 Egyptian Arabic arz.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan arz Individual Living
20 Emiliano-Romagnolo eml.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel eml nan nan Individual Living
21 Erzya myv.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan myv myv Individual Living
22 Georgian ka.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel ka 639-2/T: kat639-2/B: geo kat Individual Living
23 Goan Konkani gom.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan gom Individual Living
24 Javanese jv.embed.distilbert distilbert_embeddings_javanese_distilbert_small Embeddings DistilBertEmbeddings jv jav jav Individual Living
25 Javanese jv.embed.javanese_distilbert_small_imdb distilbert_embeddings_javanese_distilbert_small_imdb Embeddings DistilBertEmbeddings jv jav jav Individual Living
26 Javanese jv.embed.javanese_roberta_small roberta_embeddings_javanese_roberta_small Embeddings RoBertaEmbeddings jv jav jav Individual Living
27 Javanese jv.embed.javanese_roberta_small_imdb roberta_embeddings_javanese_roberta_small_imdb Embeddings RoBertaEmbeddings jv jav jav Individual Living
28 Javanese jv.embed.javanese_bert_small_imdb bert_embeddings_javanese_bert_small_imdb Embeddings BertEmbeddings jv jav jav Individual Living
29 Javanese jv.embed.javanese_bert_small bert_embeddings_javanese_bert_small Embeddings BertEmbeddings jv jav jav Individual Living
30 Kirghiz, Kyrgyz ky.stopwords stopwords_iso Stop Words Removal StopWordsCleaner ky kir kir Individual Living
31 Letzeburgesch, Luxembourgish lb.stopwords stopwords_iso Stop Words Removal StopWordsCleaner lb ltz ltz Individual Living
32 Letzeburgesch, Luxembourgish lb.lemma lemma_spacylookup Lemmatization LemmatizerModel lb ltz ltz Individual Living
33 Letzeburgesch, Luxembourgish lb.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel lb ltz ltz Individual Living
34 Ligurian lij.stopwords stopwords_iso Stop Words Removal StopWordsCleaner nan nan lij Individual Living
35 Lombard lmo.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan lmo Individual Living
36 Low German, Low Saxon nds.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nds nds Individual Living
37 Macedonian mk.stopwords stopwords_iso Stop Words Removal StopWordsCleaner mk 639-2/T: mkd639-2/B: mac mkd Individual Living
38 Macedonian mk.lemma lemma_spacylookup Lemmatization LemmatizerModel mk 639-2/T: mkd639-2/B: mac mkd Individual Living
39 Macedonian mk.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel mk 639-2/T: mkd639-2/B: mac mkd Individual Living
40 Maithili mai.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan mai mai Individual Living
41 Manx gv.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel gv glv glv Individual Living
42 Mazanderani mzn.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan mzn Individual Living
43 Minangkabau min.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan min min Individual Living
44 Mingrelian xmf.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan xmf Individual Living
45 Mirandese mwl.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan mwl mwl Individual Living
46 Neapolitan nap.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nap nap Individual Living
47 Nepal Bhasa, Newari new.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan new new Individual Living
48 Northern Frisian frr.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan frr frr Individual Living
49 Northern Sami sme.lemma lemma_giella Lemmatization LemmatizerModel se sme sme Individual Living
50 Northern Sami sme.pos pos_giella Part of Speech Tagging PerceptronModel se sme sme Individual Living
51 Northern Sotho, Pedi, Sepedi nso.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nso nso Individual Living
52 Occitan (post 1500) oc.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel oc oci oci Individual Living
53 Ossetian, Ossetic os.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel os oss oss Individual Living
54 Pfaelzisch pfl.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan pfl Individual Living
55 Piemontese pms.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan pms Individual Living
56 Romansh rm.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel rm roh roh Individual Living
57 Scots sco.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan sco sco Individual Living
58 Sicilian scn.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan scn scn Individual Living
59 Sinhala, Sinhalese si.stopwords stopwords_iso Stop Words Removal StopWordsCleaner si sin sin Individual Living
60 Sinhala, Sinhalese si.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel si sin sin Individual Living
61 Sundanese su.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel su sun sun Individual Living
62 Sundanese su.embed.sundanese_roberta_base roberta_embeddings_sundanese_roberta_base Embeddings RoBertaEmbeddings su sun sun Individual Living
63 Tagalog tl.lemma lemma_spacylookup Lemmatization LemmatizerModel tl tgl tgl Individual Living
64 Tagalog tl.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel tl tgl tgl Individual Living
65 Tagalog tl.stopwords stopwords_iso Stop Words Removal StopWordsCleaner tl tgl tgl Individual Living
66 Tagalog tl.embed.roberta_tagalog_large roberta_embeddings_roberta_tagalog_large Embeddings RoBertaEmbeddings tl tgl tgl Individual Living
67 Tagalog tl.embed.roberta_tagalog_base roberta_embeddings_roberta_tagalog_base Embeddings RoBertaEmbeddings tl tgl tgl Individual Living
68 Tajik tg.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel tg tgk tgk Individual Living
69 Tatar tt.stopwords stopwords_iso Stop Words Removal StopWordsCleaner tt tat tat Individual Living
70 Tatar tt.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel tt tat tat Individual Living
71 Tigrinya ti.stopwords stopwords_iso Stop Words Removal StopWordsCleaner ti tir tir Individual Living
72 Tosk Albanian als.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan als Individual Living
73 Tswana tn.stopwords stopwords_iso Stop Words Removal StopWordsCleaner tn tsn tsn Individual Living
74 Turkmen tk.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel tk tuk tuk Individual Living
75 Upper Sorbian hsb.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan hsb hsb Individual Living
76 Venetian vec.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan vec Individual Living
77 Vlaams vls.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan vls Individual Living
78 Walloon wa.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel wa wln wln Individual Living
79 Waray (Philippines) war.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan war war Individual Living
80 Western Armenian hyw.pos pos_armtdp Part of Speech Tagging PerceptronModel nan nan hyw Individual Living
81 Western Armenian hyw.lemma lemma_armtdp Lemmatization LemmatizerModel nan nan hyw Individual Living
82 Western Frisian fy.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel fy fry fry Individual Living
83 Western Panjabi pnb.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan pnb Individual Living
84 Yakut sah.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan sah sah Individual Living
85 Zeeuws zea.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel nan nan zea Individual Living
86 Albanian sq.stopwords stopwords_iso Stop Words Removal StopWordsCleaner sq 639-2/T: sqi639-2/B: alb sqi Macrolanguage Living
87 Albanian sq.embed.w2v_cc_300d w2v_cc_300d Embeddings WordEmbeddingsModel sq 639-2/T: sqi639-2/B: alb sqi Macrolanguage Living
88