Description
Pretrained DistilBERT Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. distilbert-base-es-cased
is a Spanish model orginally trained by Geotrend
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = DistilBertEmbeddings.pretrained("distilbert_embeddings_distilbert_base_es_cased","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)
Model Information
Model Name: | distilbert_embeddings_distilbert_base_es_cased |
Compatibility: | Spark NLP 3.4.2+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [bert] |
Language: | es |
Size: | 237.0 MB |
Case sensitive: | true |
References
- https://huggingface.co/Geotrend/distilbert-base-es-cased
- https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf
- https://github.com/Geotrend-research/smaller-transformers