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 BAugust 4, 2021 UTC
bert_config.json
314 BAugust 4, 2021 UTC
bind_pyt.py
5.52 KBAugust 4, 2021 UTC
bind.sh
7.17 KBAugust 4, 2021 UTC
configurations.yml
3.3 KBAugust 4, 2021 UTC
create_pretraining_data.py
17.2 KBAugust 4, 2021 UTC
Dockerfile
1.58 KBAugust 4, 2021 UTC
extract_features.py
11.87 KBAugust 4, 2021 UTC
file_utils.py
8.7 KBAugust 4, 2021 UTC
inference.py
14.48 KBAugust 4, 2021 UTC
LICENSE
11.15 KBAugust 4, 2021 UTC
modeling.py
59.34 KBAugust 4, 2021 UTC
NOTICE
147 BAugust 4, 2021 UTC
optimization.py
7 KBAugust 4, 2021 UTC
README.md
70.64 KBAugust 4, 2021 UTC
requirements.txt
268 BAugust 4, 2021 UTC
run_glue.py
28.85 KBAugust 4, 2021 UTC
run_pretraining.py
31.75 KBAugust 4, 2021 UTC
run_squad.py
54.09 KBAugust 4, 2021 UTC
run_swag.py
24.35 KBAugust 4, 2021 UTC
run.sub
2.71 KBAugust 4, 2021 UTC
schedulers.py
4.71 KBAugust 4, 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.