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File checksum: a7022d92223e2212eb7d736f4f8cdcdd17059fff51ddc94d535b406edf0027c0

Provides weights and configuration for the pretrained transformer model bert-base-uncased, published by Google Research. The package uses HuggingFace's pytorch-transformers implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.

Requires the spacy-pytorch-transformers package to be installed. A CUDA-compatible GPU is advised for reasonable performance.

Feature Description
Name en_pytt_bertbaseuncased_lg
Version 2.1.0
spaCy >=2.1.7
Model size 406 MB
Pipeline sentencizer, pytt_wordpiecer, pytt_tok2vec
Sources bert-base-uncased
License MIT
Author Google Research (repackaged by Explosion)


pip install spacy
spacy download en_pytt_bertbaseuncased_lg
Assets 3
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