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:
- fe8e753f72f9b43f867ac002a46471650ea064d55c412d42f6dc53cf8244d3af
- Size of remote file:
- 499 MB
- SHA256:
- c0ec4e6a4880c1de365a6b6d8dda360d61aad60c1da028a0dc9a1f782a440b29
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