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:
- 4b25d7a52b7901f739763b5bb9409362ff34a4fddfd38a636c7905ee5305f01d
- Size of remote file:
- 4.74 MB
- SHA256:
- 78242f3b36c02c4ea7862a3f30665f7dabb9d0541c792048a92db69abafa08df
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