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")# 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
- Xet hash:
- 25230a7fe9b23e5f21ba150c7e3ddbc5a3d77833857687864f10ea54e8c66c2b
- Size of remote file:
- 88.3 MB
- SHA256:
- 6d6c9050f8249d5eaa4d4d5e4da4c4a2e2195b0d3abf79315d49edff05aca92f
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