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:
- db61146d41c06ee91a52e4c18c78c31d6c012b59822e7c862d217e637d62d593
- Size of remote file:
- 499 MB
- SHA256:
- cb004030b417087d9b64cc619b04cd237979a2d778adc3d15ee5d99f51943936
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