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 codebert-base/checkpoint-50/training_args.bin from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/d660c9981472f36590b0115c49c2ec266fccb364/codebert-base/checkpoint-50/training_args.bin
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@d660c9981472f36590b0115c49c2ec266fccb364/codebert-base/checkpoint-50/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/d660c9981472f36590b0115c49c2ec266fccb364/codebert-base/checkpoint-50/training_args.bin
5.84 kB
- Xet hash:
- 683b8ef0f602ebeeb82e803e258ac5ff35ce5e35570076b0da1255aefd45bb47
- Size of remote file:
- 5.84 kB
- SHA256:
- 716747561b45f935ce7bd12c1883ff0618d3af217eb0ce2bf14bba6f805506ea
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