English Bert Embeddings Cased model (from Shafin)

Description

Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. chemical-bert-uncased-finetuned-cust-c1-cust is a English model originally trained by Shafin.

Download Copy S3 URI

How to use

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

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

embeddings = BertEmbeddings.pretrained("bert_embeddings_chemical_uncased_finetuned_cust_c1_cust","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings") \
    .setCaseSensitive(True)

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

data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler()
    .setInputCol("text")
    .setOutputCol("document")

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

val embeddings = BertEmbeddings.pretrained("bert_embeddings_chemical_uncased_finetuned_cust_c1_cust","en")
    .setInputCols(Array("document", "token"))
    .setOutputCol("embeddings")
    .setCaseSensitive(True)

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

val data = Seq("I love Spark NLP").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

Model Name:	bert_embeddings_chemical_uncased_finetuned_cust_c1_cust
Compatibility:	Spark NLP 4.3.0+
License:	Open Source
Edition:	Official
Input Labels:	[sentence, token]
Output Labels:	[bert]
Language:	en
Size:	412.1 MB
Case sensitive:	true

References

https://huggingface.co/shafin/chemical-bert-uncased-finetuned-cust-c1-cust

PREVIOUSKorean Bert Embeddings Cased model (from onlydj96)

NEXTEnglish Bert Embeddings Cased model (from Shafin)