NVIDIA Deep Learning Examples
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NVIDIA Deep Learning Examples
BERT for PyTorchBERT 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 | March 31, 2021 UTC | |
bert_config.json | 314 B | March 31, 2021 UTC | |
bind_pyt.py | 5.52 KB | March 31, 2021 UTC | |
bind.sh | 7.17 KB | March 31, 2021 UTC | |
configurations.yml | 3.3 KB | March 31, 2021 UTC | |
create_pretraining_data.py | 17.2 KB | March 31, 2021 UTC | |
Dockerfile | 1.58 KB | March 31, 2021 UTC | |
extract_features.py | 11.87 KB | March 31, 2021 UTC | |
file_utils.py | 8.7 KB | March 31, 2021 UTC | |
inference.py | 14.48 KB | March 31, 2021 UTC | |
LICENSE | 11.15 KB | March 31, 2021 UTC | |
modeling.py | 59.34 KB | March 31, 2021 UTC | |
NOTICE | 147 B | March 31, 2021 UTC | |
optimization.py | 7 KB | March 31, 2021 UTC | |
README.md | 70.28 KB | March 31, 2021 UTC | |
requirements.txt | 268 B | March 31, 2021 UTC | |
run_glue.py | 28.85 KB | March 31, 2021 UTC | |
run_pretraining.py | 31.75 KB | March 31, 2021 UTC | |
run_squad.py | 54.09 KB | March 31, 2021 UTC | |
run_swag.py | 24.35 KB | March 31, 2021 UTC | |
run.sub | 2.71 KB | March 31, 2021 UTC | |
schedulers.py | 4.71 KB | March 31, 2021 UTC |