Description
This model contains a deep bidirectional transformer trained on Wikipedia and the BookCorpus. The details are described in the paper “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”.
How to use
embeddings = BertEmbeddings.pretrained("bert_base_uncased", "en") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
val embeddings = BertEmbeddings.pretrained("bert_base_uncased", "en")
.setInputCols("sentence", "token")
.setOutputCol("embeddings")
Model Information
| Model Name: | bert_base_uncased |
| Type: | embeddings |
| Compatibility: | Spark NLP 2.4.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [word_embeddings] |
| Language: | [en] |
| Dimension: | 768 |
| Case sensitive: | false |
Data Source
The model is imported from https://tfhub.dev/google/bert_uncased_L-12_H-768_A-12/1