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:
- 8c7e3385312881970e112683d14d1f2e5feda20d1d308d60490f1bb8f03ffd20
- Size of remote file:
- 4.74 MB
- SHA256:
- 41ff1d1389d831b2bc7715b986dcf40f64372807ce80b3368515da1fcaa1cb7a
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