Description
Pretrained BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-large-portuguese-cased-legal-mlm-sts-v0.4 is a model originally trained by stjiris.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = BertSentenceEmbeddings.pretrained("sbert_bert_large_portuguese_cased_legal_mlm_sts_v0.4","pt") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["Eu amo Spark NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
import nlu
nlu.load("pt.embed_sentence.bert.legal.cased_large_mlm_sts_v0.4.by_stjiris").predict("""Eu amo Spark NLP""")
Model Information
| Model Name: | sbert_bert_large_portuguese_cased_legal_mlm_sts_v0.4 |
| Compatibility: | Spark NLP 4.2.4+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence] |
| Output Labels: | [bert_sentence] |
| Language: | pt |
| Size: | 1.3 GB |
| Case sensitive: | true |
| Max sentence length: | 128 |
References
- https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm-sts-v0.4
- https://www.SBERT.net