NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
BERT for PyTorch
Resource
NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
BERT for PyTorch

BERT is a method of pre-training language representations which obtains state-of-the-art results on a wide array of NLP tasks.

NameSizeUpdatedActions
.dockerignore
710 BNovember 12, 2021 UTC
bert_config.json
314 BNovember 12, 2021 UTC
bind_pyt.py
5.52 KBNovember 12, 2021 UTC
bind.sh
7.17 KBNovember 12, 2021 UTC
configurations.yml
3.3 KBNovember 12, 2021 UTC
create_pretraining_data.py
17.2 KBNovember 12, 2021 UTC
Dockerfile
1.53 KBNovember 12, 2021 UTC
extract_features.py
11.87 KBNovember 12, 2021 UTC
file_utils.py
8.7 KBNovember 12, 2021 UTC
inference.py
14.48 KBNovember 12, 2021 UTC
LICENSE
11.15 KBNovember 12, 2021 UTC
modeling.py
59.34 KBNovember 12, 2021 UTC
NOTICE
147 BNovember 12, 2021 UTC
optimization.py
7 KBNovember 12, 2021 UTC
README.md
70.66 KBNovember 12, 2021 UTC
requirements.txt
258 BNovember 12, 2021 UTC
run_glue.py
28.85 KBNovember 12, 2021 UTC
run_pretraining.py
31.75 KBNovember 12, 2021 UTC
run_squad.py
54.09 KBNovember 12, 2021 UTC
run_swag.py
24.35 KBNovember 12, 2021 UTC
run.sub
2.71 KBNovember 12, 2021 UTC
schedulers.py
4.71 KBNovember 12, 2021 UTC

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.