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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 | September 13, 2019 UTC | |
.dockerignore | 759 B | September 13, 2019 UTC | |
.gitmodules | 156 B | September 13, 2019 UTC | |
configurations.yml | 4.15 KB | September 13, 2019 UTC | |
CONTRIBUTING.md | 1.29 KB | September 13, 2019 UTC | |
Dockerfile | 949 B | September 13, 2019 UTC | |
extract_features.py | 13.57 KB | September 13, 2019 UTC | |
fp16_utils.py | 1.47 KB | September 13, 2019 UTC | |
fused_layer_norm.py | 5.49 KB | September 13, 2019 UTC | |
gpu_environment.py | 1.53 KB | September 13, 2019 UTC | |
LICENSE | 11.09 KB | September 13, 2019 UTC | |
modeling_test.py | 8.98 KB | September 13, 2019 UTC | |
modeling.py | 37.83 KB | September 13, 2019 UTC | |
multilingual.md | 11.03 KB | September 13, 2019 UTC | |
NOTICE | 158 B | September 13, 2019 UTC | |
optimization_test.py | 1.68 KB | September 13, 2019 UTC | |
optimization.py | 17.2 KB | September 13, 2019 UTC | |
predicting_movie_reviews_with_bert_on_tf_hub.ipynbView Notebook | 64.93 KB | September 13, 2019 UTC | |
README.md | 84.47 KB | September 13, 2019 UTC | |
requirements.txt | 110 B | September 13, 2019 UTC | |
run_classifier_with_tfhub.py | 11.16 KB | September 13, 2019 UTC | |
run_classifier.py | 28.27 KB | September 13, 2019 UTC | |
run.sub | 3.11 KB | September 13, 2019 UTC |