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:
- cbf908662fae5390f6e065ba9e6c10d24db705a021a27571331161823955a407
- Size of remote file:
- 499 MB
- SHA256:
- 15639f8eb940de785a10f57f414930caabaeb707d1eef4957c41efa3088bdd21
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