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:
- 048758f305b55c4907b9ff72f8cf72300710481411aa27d17852e9cd20c9c2bf
- Size of remote file:
- 499 MB
- SHA256:
- 9a938d5016a359936007454fcb9fc6ee62fbf9e6d6d3cd161afb8837cb13dd09
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