Instructions to use suncy13/graysacleAugmentedFoot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suncy13/graysacleAugmentedFoot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suncy13/graysacleAugmentedFoot") 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/graysacleAugmentedFoot") model = AutoModelForImageClassification.from_pretrained("suncy13/graysacleAugmentedFoot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from suncy13/graysacleAugmentedFoot: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/suncy13/graysacleAugmentedFoot/resolve/main/training_args.bin
- Command line
-
hf download hf://suncy13/graysacleAugmentedFoot/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/suncy13/graysacleAugmentedFoot/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 7b4d59e06648d54a4fd5488de1ca7b686db90631b54ec86ceb7cd0eb17900a1f
- Size of remote file:
- 4.6 kB
- SHA256:
- 3fb3da95b6affc34dc0811d990364efc93e1829b9d1069de6849c07cf941ebfe
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