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:
- e948c43ffc47782e68bbab224584f29cd2372eb298a6d8d755f141e098be5b7c
- Size of remote file:
- 499 MB
- SHA256:
- 3af72d54aa03a8ac53999721bb148b3845cb67d18cc8965830efb8a0cf195740
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