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-mixcode-fft/checkpoint-300/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/4f8c4ed3d9cf9cdc213702412916e71be9634c88/graphcodebert-mixcode-fft/checkpoint-300/scaler.pt
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@4f8c4ed3d9cf9cdc213702412916e71be9634c88/graphcodebert-mixcode-fft/checkpoint-300/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/4f8c4ed3d9cf9cdc213702412916e71be9634c88/graphcodebert-mixcode-fft/checkpoint-300/scaler.pt
1.38 kB
- Xet hash:
- 239b74a6337fd8a6e8ed4909fa81665e2566715164e6718401fe54307ea1dbb4
- Size of remote file:
- 1.38 kB
- SHA256:
- 30af866df24edce708e1eb20700878b402fa05707fa9bc5f332496baf440dbbb
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