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:
- 3a0d5213c6336bc053794ec5318c9afe2a69f54cecd001c6fce867be70144932
- Size of remote file:
- 499 MB
- SHA256:
- 51808bd23f6f3b2694c4effdb372be4beda8d4cd21d7e03a6ce4216bad7a01e7
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