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:
- 9177af6b75652209ab1b95e41f74da58c3de6ee2afe78cf4067f0836837423e7
- Size of remote file:
- 4.74 MB
- SHA256:
- a83a04a97cc63d010ee0194538f8c07493223183d14eab2d89cd2b4303321ee2
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