Instructions to use AMindToThink/code-detection-confound-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMindToThink/code-detection-confound-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AMindToThink/code-detection-confound-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download python_raw_ce/model.bin from AMindToThink/code-detection-confound-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/AMindToThink/code-detection-confound-checkpoints/resolve/f670cc8033c17e8755ce774f2e51012aa91bf9f5/python_raw_ce/model.bin
- Command line
-
hf download hf://AMindToThink/code-detection-confound-checkpoints@f670cc8033c17e8755ce774f2e51012aa91bf9f5/python_raw_ce/model.bin
-
curl -L -o model.bin https://huggingface.co/AMindToThink/code-detection-confound-checkpoints/resolve/f670cc8033c17e8755ce774f2e51012aa91bf9f5/python_raw_ce/model.bin
504 MB
- Xet hash:
- 709aa9d9abb73ebb7d1db11565e623a6e051504a060327b410a5471dbb8ec55c
- Size of remote file:
- 504 MB
- SHA256:
- d9afd8bed482d844b20ae8bfafe5c765305af4cddd28bec4604f3eb0e0da11e9
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