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:
- d18aed1889337926ed3ed8babf9264d2484ffe51fba2245b6ac3c5ee6aa9be87
- Size of remote file:
- 1.01 GB
- SHA256:
- 53bf52cb642b51369e0a95075a5b756e85921ef6f4dc7f444e6cfe7fe2a5900c
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