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:
- c70148b8d6ed901c501c1a2d2986b29f2e419f88751b7fadd9965d8691b0e121
- Size of remote file:
- 499 MB
- SHA256:
- 2800d2a3c0e50047644191270159eb624f6b52017ba169c0c5ec647b10b9e14b
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