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-850 /model.safetensors
- Xet hash:
- 46c89f39cc21b1ba7f9f34c8841837482e99ed3c05d32aa7fc95b9419527b144
- Size of remote file:
- 499 MB
- SHA256:
- 23fc0a49f14d9c3ac275c51cb0281f89df63a96f1370307127916a3c1975b161
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