Description
Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. alberti-bert-base-multilingual-cased is a Spanish model orginally trained by flax-community.
Predicted Entities
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = BertEmbeddings.pretrained("bert_embeddings_alberti_bert_base_multilingual_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: | bert_embeddings_alberti_bert_base_multilingual_cased |
| Compatibility: | Spark NLP 5.0.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [bert] |
| Language: | es |
| Size: | 664.3 MB |
| Case sensitive: | true |