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:
- 2f76039fd85ceba0274c29a95ab421958fea684d124a6b6efedde30bc804a2b9
- Size of remote file:
- 499 MB
- SHA256:
- 7db5571849e8e089f270ef2e4cf5cb4d9ef5cccb044fbe784913f0b02e58151b
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