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BERT is a method of pre-training language representations which obtains state-of-the-art results on a wide array of NLP tasks.
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| Name | Size | Updated | Actions |
|---|---|---|---|
__init__.py | 616 B | October 2, 2019 UTC | |
.dockerignore | 58 B | October 2, 2019 UTC | |
CONTRIBUTING.md | 1.29 KB | October 2, 2019 UTC | |
create_pretraining_data.py | 14.88 KB | October 2, 2019 UTC | |
Dockerfile | 476 B | October 2, 2019 UTC | |
extract_features.py | 13.57 KB | October 2, 2019 UTC | |
gpu_environment.py | 1.53 KB | October 2, 2019 UTC | |
LICENSE | 11.09 KB | October 2, 2019 UTC | |
modeling_test.py | 8.98 KB | October 2, 2019 UTC | |
modeling.py | 37.34 KB | October 2, 2019 UTC | |
multilingual.md | 11.03 KB | October 2, 2019 UTC | |
NOTICE | 158 B | October 2, 2019 UTC | |
optimization_test.py | 1.68 KB | October 2, 2019 UTC | |
optimization.py | 7.72 KB | October 2, 2019 UTC | |
predicting_movie_reviews_with_bert_on_tf_hub.ipynbView Notebook | 64.93 KB | October 2, 2019 UTC | |
README.md | 30.2 KB | October 2, 2019 UTC | |
requirements.txt | 110 B | October 2, 2019 UTC | |
run_classifier_with_tfhub.py | 9.33 KB | October 2, 2019 UTC | |
run_classifier.py | 34.39 KB | October 2, 2019 UTC | |
run_pretraining.py | 22.93 KB | October 2, 2019 UTC | |
run_squad.py | 50.8 KB | October 2, 2019 UTC | |
sample_text.txt | 4.29 KB | October 2, 2019 UTC |