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 checkpoint-400/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/2a2618e52c7420dadd88e2cb7b9b49e1aaa3a40e/checkpoint-400/training_args.bin
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification@2a2618e52c7420dadd88e2cb7b9b49e1aaa3a40e/checkpoint-400/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/2a2618e52c7420dadd88e2cb7b9b49e1aaa3a40e/checkpoint-400/training_args.bin
5.84 kB
- Xet hash:
- 4159a609f6f17160a21319c185ae87f43cb8c038ef80fee6d46bedcb6b0594cf
- Size of remote file:
- 5.84 kB
- SHA256:
- d6ab3d3f08d9426eb9807e9630113e3f0e0c4e53931f1d94a0019c3b5e996465
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