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:
- d9bee0e42a1ef3e26de27e3ea4a7e066d98d7deb1962784851f1f0fa028bb940
- Size of remote file:
- 4.74 MB
- SHA256:
- b722cecb86725f9e176547eea1fa82aaf7883c091259493a9743214cfe3e4807
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