Instructions to use Brightmzb/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Brightmzb/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Brightmzb/vit-base-beans-demo-v5") 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("Brightmzb/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("Brightmzb/vit-base-beans-demo-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Brightmzb/vit-base-beans-demo-v5: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Brightmzb/vit-base-beans-demo-v5/resolve/main/training_args.bin
- Command line
-
hf download hf://Brightmzb/vit-base-beans-demo-v5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Brightmzb/vit-base-beans-demo-v5/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 2ec25615722bbf99b011d0818d8b991e498191d30dfbdf69cf9e445ae0b1100b
- Size of remote file:
- 5.37 kB
- SHA256:
- 3bba2b92d37eb326877b864bf07dcc346368cbdb126a7d48f50a3383e75587b3
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