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 unixcoder-base/checkpoint-50/training_args.bin from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/3c8b1b443cedfa8761f5112efca6bc864300a7de/unixcoder-base/checkpoint-50/training_args.bin
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@3c8b1b443cedfa8761f5112efca6bc864300a7de/unixcoder-base/checkpoint-50/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/3c8b1b443cedfa8761f5112efca6bc864300a7de/unixcoder-base/checkpoint-50/training_args.bin
5.91 kB
- Xet hash:
- 76cdaa18b835185eb80d83da9219148e186bfc6de1f1c1597c3d6aa9a63067e2
- Size of remote file:
- 5.91 kB
- SHA256:
- 6a78a2eb6799e96da4580dc622a59464b1e6878a568d917ed75044c6fd0570b8
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