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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 |
|---|---|---|---|
.dockerignore | 710 B | November 5, 2019 UTC | |
bert_config.json | 314 B | November 5, 2019 UTC | |
bind_pyt.py | 5.52 KB | November 5, 2019 UTC | |
configurations.yml | 3.3 KB | November 5, 2019 UTC | |
create_pretraining_data.py | 17.04 KB | November 5, 2019 UTC | |
Dockerfile | 1.02 KB | November 5, 2019 UTC | |
extract_features.py | 11.87 KB | November 5, 2019 UTC | |
file_utils.py | 8.7 KB | November 5, 2019 UTC | |
LICENSE | 11.15 KB | November 5, 2019 UTC | |
modeling.py | 62.18 KB | November 5, 2019 UTC | |
NOTICE | 148 B | November 5, 2019 UTC | |
optimization.py | 16.44 KB | November 5, 2019 UTC | |
README.md | 56.41 KB | November 5, 2019 UTC | |
requirements.txt | 208 B | November 5, 2019 UTC | |
run_glue.py | 27.5 KB | November 5, 2019 UTC | |
run_pretraining_inference.py | 13.1 KB | November 5, 2019 UTC | |
run_pretraining.py | 26.5 KB | November 5, 2019 UTC | |
run_squad.py | 51.92 KB | November 5, 2019 UTC | |
run_swag.py | 24.04 KB | November 5, 2019 UTC | |
run.sub | 2.6 KB | November 5, 2019 UTC | |
schedulers.py | 3.95 KB | November 5, 2019 UTC | |
tokenization.py | 14.79 KB | November 5, 2019 UTC | |
utils.py | 847 B | November 5, 2019 UTC |