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:
- 1277ac950a5a98a37d146d1e342a1c661e294b2a5db0034aa9fd031a71472870
- Size of remote file:
- 4.74 MB
- SHA256:
- b8f476a2c19c4968158ab6f57a56ebc00379989e25d491797ef5b2caf3a05888
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