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:
- 96a8db4c2ce9ffd97b06c43e3f3b6cbde4df0056fa30e89bf50d0a56a2a0d602
- Size of remote file:
- 499 MB
- SHA256:
- c038fee615aa3289704b6c8446543a8902b07b09cc79c21ef54c5fe8590f914e
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