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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzungpham/graphcodebert-code-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download graphcodebert-robust/checkpoint-200/scaler.pt from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 1.38 kB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-robust/checkpoint-200/scaler.pt
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-robust/checkpoint-200/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-robust/checkpoint-200/scaler.pt
1.38 kB
- Xet hash:
- 879e74f8df86c6203409cd86fc9ee0f3cdde56663cf6d22ca2ee58c13e418c69
- Size of remote file:
- 1.38 kB
- SHA256:
- b21c5349d5e7d02de630ebc1cb53ade1d9c6079eeb8594d223bb786011a0428b
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