Instructions to use OhST/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OhST/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="OhST/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("OhST/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("OhST/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from OhST/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/OhST/cppe5_use_data_finetuning/resolve/df3f893eebc75008ccdc64ac2dfdaa50bbb5b3f3/pytorch_model.bin
- Command line
-
hf download hf://OhST/cppe5_use_data_finetuning@df3f893eebc75008ccdc64ac2dfdaa50bbb5b3f3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/OhST/cppe5_use_data_finetuning/resolve/df3f893eebc75008ccdc64ac2dfdaa50bbb5b3f3/pytorch_model.bin
167 MB
- Xet hash:
- b15533e01df4a697af46a600b8ef1b39b982aff60886c9ca666cf3b0502f27ec
- Size of remote file:
- 167 MB
- SHA256:
- 5af3ffcaddbfa94b83c5f74fa5bc9a81a042cb73ef65cc0c79beee17fd2d41b3
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