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
graphcodebert-code-classification / graphcodebert-swa-from-epoch-1 /checkpoint-1400 /model.safetensors
- Xet hash:
- e4993e2fb85d083d32a6643d7097b143593a511a54e69792d8ae1dc0790db21e
- Size of remote file:
- 499 MB
- SHA256:
- 44ffaa0bb66889175547889af7dceab487d4d9d6631533c70e0d45526ad4d0b2
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