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:
- df2d0768ef02b30ee3693b43dbd6b0599a0bb66bc978b43393378a3635068f13
- Size of remote file:
- 4.74 MB
- SHA256:
- 761c23060e28359071290c62124dfb044d0a38ac5d9e8e3b1a604a5b25c74779
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