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:
- 5508632d1cb6167f6a347d69d5409ccd6e304da978915d103421ff9d85c85247
- Size of remote file:
- 4.74 MB
- SHA256:
- c5630152242afd0e6c6c4e2ab8452cd1ed56b7076e9b3c2c1648d7ec31e47aff
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