Instructions to use sdhed/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdhed/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sdhed/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("sdhed/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("sdhed/vit-base-beans-demo-v5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02c2a2af5400e72122bee59deedfd31af09fa13fb57c94eeee1f3755c637448c
- Size of remote file:
- 5.11 kB
- SHA256:
- 42b8ea4a157ad46787dc52cb1096acedd9ba8582e8e95b476c8f0f8c19887346
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