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:
- a4a04abf35b34755cc774d209feb66a383f7aba09875db63134a50a0d795f10b
- Size of remote file:
- 499 MB
- SHA256:
- 2b92b00ec47c6bcdb02735c9b4793b2bd41fc8ab46ae1ad8f84073f5fbff5110
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