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:
- 5838e6544e4c460db4ba9aade0b32101c70ae935864aba9cdfc71a059a747de0
- Size of remote file:
- 499 MB
- SHA256:
- 5ce9efb0838c3bb940be1057d74141678c8cc0e3a6a330ef621cf8aad644b455
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