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
graphcodebert-code-classification / fourier-spectral-norm-classifier /checkpoint-1500 /model.safetensors
- Xet hash:
- c4ee14b74b81dfccd62f56ab39f839abdd9ddb86d827373922f1e4a8831701d1
- Size of remote file:
- 499 MB
- SHA256:
- 5e4bc60c5b8f6a36e32e0d39d6e8298433aad8375eb96017225baf2ef95e07ce
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