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-350 /model.safetensors
- Xet hash:
- c8f9bfb8f42ccef1c1e3db6b54cf9956715479aa0ad7e7e81c31ac0394427d12
- Size of remote file:
- 499 MB
- SHA256:
- fef80ac3319fc044bd5ed974ce634130ad50dd3891109eedb8d138f19c9ac974
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