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:
- ea317c3d1b18668a69793219581bdacc102d7e36fe19839e9b474f2f98e685c9
- Size of remote file:
- 1.01 GB
- SHA256:
- 6bdf390e9c9e5d555f636219141a77d3bb7ad8de7356aaf171bdfbbbf56a7182
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