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:
- 316852c86d62f8437554c86514c6470cb181c4417901cd720e61869efa2415ee
- Size of remote file:
- 4.74 MB
- SHA256:
- 8df0daec4efa812ba208cd0dc90879540bae0bc13e657a311777d25929b1aea1
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