Instructions to use suncy13/sample_foot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suncy13/sample_foot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suncy13/sample_foot") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("suncy13/sample_foot") model = AutoModelForImageClassification.from_pretrained("suncy13/sample_foot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from suncy13/sample_foot: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/suncy13/sample_foot/resolve/main/training_args.bin
- Command line
-
hf download hf://suncy13/sample_foot/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/suncy13/sample_foot/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 23d8af46d83e0d95a12d925b491378b0da27d6fbd63ab3f1a2d0750648932983
- Size of remote file:
- 4.6 kB
- SHA256:
- ff9a57435e572c1bcbdcaa1a8504c34e4152d729a06e2bfe761c017aed68f45d
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