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:
# 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-200/model.safetensors from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/main/graphcodebert-rdrop/checkpoint-200/model.safetensors
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification/graphcodebert-rdrop/checkpoint-200/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/main/graphcodebert-rdrop/checkpoint-200/model.safetensors
499 MB
- Xet hash:
- 572bd84a0fb99978481b9f70eb78a125103aef270162f762af7bbc6ac780c8df
- Size of remote file:
- 499 MB
- SHA256:
- ac86433275c4c5f90dffc8271cd1029e8abe70a5522abf0e31073eec45c4cc88
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