Instructions to use MathisKhan/vit-beans-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MathisKhan/vit-beans-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MathisKhan/vit-beans-classifier") 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("MathisKhan/vit-beans-classifier") model = AutoModelForImageClassification.from_pretrained("MathisKhan/vit-beans-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MathisKhan/vit-beans-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/MathisKhan/vit-beans-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://MathisKhan/vit-beans-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MathisKhan/vit-beans-classifier/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 628f80a6ad686255f24a844687e20cf6bffb7a3e302bec27d1eece6741081b23
- Size of remote file:
- 5.27 kB
- SHA256:
- 6bbc6143c2afac4263d453bd9e8ba2f13374c0fffb32d07d434dc47dd313598d
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