Instructions to use mrm8488/codeBERTaJS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/codeBERTaJS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/codeBERTaJS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/codeBERTaJS") model = AutoModelForMaskedLM.from_pretrained("mrm8488/codeBERTaJS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
upload flax model
2d18abf -
allow flax
f330e31
-
Update README.md
f75c7e7
-
Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/mrm8488/codeBERTaJS/README.mdc0a8824
-
Update config.json
31046d3
-
Update config.json
d273ac2
-
Update config.json
04c2974 -
Update special_tokens_map.json
6da5a08 -
Update tokenizer_config.json
c989d2a -
Update training_args.bin
e5d543c -
Update merges.txt
4ffc871 -
Update vocab.json
447de61 -
Update pytorch_model.bin
a80f8e2 -
initial commit
f36863d