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
graphcodebert-code-classification / graphcodebert-swa-from-epoch-1 /checkpoint-1300 /training_args.bin
- Xet hash:
- 4b1ee537a67e0cc32ff060ecf9cb7c0f2e1c4159b03a846adef515a6e2b97938
- Size of remote file:
- 5.84 kB
- SHA256:
- 2212b57ced9fbe3464bd23d4ac0f4d8e75b4b021597f160058a4a19990d9f0d3
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