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-rdrop/checkpoint-2000/scheduler.pt from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-rdrop/checkpoint-2000/scheduler.pt
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-rdrop/checkpoint-2000/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/26476e0af80ba0a4d10bb107e7ddbfeef1d6b225/graphcodebert-rdrop/checkpoint-2000/scheduler.pt
1.47 kB
- Xet hash:
- 485f4cc97bcce0c1eb1fe2481fc68f559431b78a27c9ee0b11faea0e0af19466
- Size of remote file:
- 1.47 kB
- SHA256:
- 01081971fcef9864330db7d66449f3eacfc8bb4dd72c7f7888470931d0a4d9ae
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