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:
- 3978021892a671834e9b89a1274a866d35e4072b5f29f3d1126ebb7312b45cc3
- Size of remote file:
- 1.98 kB
- SHA256:
- 2f55aca7b64a847467387b78ff8558964def3d2cb5259c8271ce255811645cc2
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