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:
- a1829d62ba5a544c270b226e0384a1c40c371df980204c0e91c404ae4e405293
- Size of remote file:
- 4.74 MB
- SHA256:
- 1f64c2c0e1b29de4a5ec23b8a9224125754d5065716f507f30ef50d435132915
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