Spanish RoBERTa Embeddings (Bertin Base)

Description

Pretrained RoBERTa Embeddings model for Spanish Language, trained within the Bertin project. Other non-base Bertin models can be found here. The model was uploaded to Hugging Face, adapted and imported into Spark NLP. bertin-roberta-base-spanish is a Spanish model orginally trained by bertin-project.

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")

tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")

embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_bertin_roberta_base_spanish","es") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["Me encanta chispa nlp"]]).toDF("text")

result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler() 
.setInputCol("text") 
.setOutputCol("document")

val tokenizer = new Tokenizer() 
.setInputCols(Array("document"))
.setOutputCol("token")

val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_bertin_roberta_base_spanish","es") 
.setInputCols(Array("document", "token")) 
.setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))

val data = Seq("Me encanta chispa nlp").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("es.embed.bertin_roberta_base_spanish").predict("""Me encanta chispa nlp""")

Model Information

Model Name: roberta_embeddings_bertin_roberta_base_spanish
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [bert]
Language: es
Size: 234.7 MB
Case sensitive: true

References

  • https://huggingface.co/bertin-project/bertin-roberta-base-spanish
  • https://github.com/google/flax
  • https://en.wikipedia.org/wiki/List_of_languages_by_total_number_of_speakers
  • https://arxiv.org/pdf/2107.07253.pdf
  • https://arxiv.org/abs/1907.11692
  • https://www.wired.com/2017/04/courts-using-ai-sentence-criminals-must-stop-now/
  • https://www.washingtonpost.com/technology/2019/05/16/police-have-used-celebrity-lookalikes-distorted-images-boost-facial-recognition-results-research-finds/
  • https://www.wired.com/story/ai-college-exam-proctors-surveillance/
  • https://www.eff.org/deeplinks/2020/09/students-are-pushing-back-against-proctoring-surveillance-apps
  • https://www.washingtonpost.com/technology/2019/10/22/ai-hiring-face-scanning-algorithm-increasingly-decides-whether-you-deserve-job/
  • https://www.technologyreview.com/2021/07/21/1029860/disability-rights-employment-discrimination-ai-hiring/
  • https://www.insider.com/china-is-testing-ai-recognition-on-the-uighurs-bbc-2021-5
  • https://www.health.harvard.edu/blog/anti-asian-racism-breaking-through-stereotypes-and-silence-2021041522414
  • https://discord.com/channels/858019234139602994/859113060068229190