BERT Large Uncased

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”.

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How to use


embeddings = BertEmbeddings.pretrained("bert_large_uncased", "en") \
      .setInputCols("sentence", "token") \
      .setOutputCol("embeddings")

val embeddings = BertEmbeddings.pretrained("bert_large_uncased", "en")
      .setInputCols("sentence", "token")
      .setOutputCol("embeddings")

Model Information

Model Name: bert_large_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: 1024
Case sensitive: false

Data Source

The model is imported from https://tfhub.dev/google/bert_uncased_L-24_H-1024_A-16/1