Instructions to use kinghoon/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kinghoon/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kinghoon/vit-base-beans-demo-v5") 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("kinghoon/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("kinghoon/vit-base-beans-demo-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0fc14f1332b5d809216d9a68aa002f01d55d96e071b7e76ba7fb223e50c045b
- Size of remote file:
- 343 MB
- SHA256:
- 8d05624b032612a27db57530b657aa96926922f6ef0b6d679d511b3993996feb
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