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-base-lowLR-highBatchSize /checkpoint-1000 /model.safetensors
- Xet hash:
- 1837550911767a0f6da2cc9d692d7b6bda4395a667bbf56740c1976d5c792b84
- Size of remote file:
- 499 MB
- SHA256:
- ce2c655bc88524b2b24a5769ffd30d15b8fb4dadc6531be416f2723b135ae619
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