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:
- 13003f4178e99eaac702b42ee79d87886c0c42e220dcaa3d29642a27b4fcf577
- Size of remote file:
- 499 MB
- SHA256:
- 77ef8b30f9d2d2e1ee145cf5902f638aed3b40960b6adbc29b7ae3619d721d15
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