Instructions to use dzungpham/graphcodebert-code-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzungpham/graphcodebert-code-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzungpham/graphcodebert-code-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15f752ec57756d19cdf46584500e004f472119dd75518931107d1bc79fa55afa
- Size of remote file:
- 499 MB
- SHA256:
- 4959ac49df25d850e0647dc016dfaa25f8e9d95e4c1a7dfa21d2dfb4d297221f
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