Description
This is the pre-trained BERT model trained on the Portuguese language. BERT-Base and BERT-Large Cased variants were trained on the BrWaC (Brazilian Web as Corpus), a large Portuguese corpus, for 1,000,000 steps, using whole-word mask.
How to use
...
embeddings = BertEmbeddings.pretrained("bert_portuguese_large_cased", "pt") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
pipeline_model = nlp_pipeline.fit(spark.createDataFrame([[""]]).toDF("text"))
result = pipeline_model.transform(spark.createDataFrame([['Eu amo PNL']], ["text"]))
...
val embeddings = BertEmbeddings.pretrained("bert_portuguese_large_cased", "pt")
.setInputCols("sentence", "token")
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
val data = Seq("Eu amo PNL").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["Eu amo PNL"]
embeddings_df = nlu.load('pt.bert.cased.large').predict(text, output_level='token')
embeddings_df
Results
token pt_bert_cased_large_embeddings
Eu [0.6893012523651123, 0.18436528742313385, 0.14...
amo [0.6536692976951599, 0.17582201957702637, -0.5...
PNL [-0.1397203803062439, 0.5698696374893188, -0.3...
Model Information
| Model Name: | bert_portuguese_large_cased |
| Type: | embeddings |
| Compatibility: | Spark NLP 2.6.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [word_embeddings] |
| Language: | [pt] |
| Dimension: | 1024 |
| Case sensitive: | true |
Data Source
The model is imported from https://github.com/neuralmind-ai/portuguese-bert