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 /rng_state.pth
- Xet hash:
- d6479a5bdecb2f6dbd3520a5f72a9ecfdd8a49c3cf94e96616eecb73e68e994a
- Size of remote file:
- 14.6 kB
- SHA256:
- e5909ab7c9c269b6f87c8f78a629bf9a4d31ba187687dd61dda9c2b3eec7a4b6
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