Instructions to use initial01/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use initial01/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="initial01/vit-base-beans") 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("initial01/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("initial01/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from initial01/vit-base-beans: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/initial01/vit-base-beans/resolve/main/model.safetensors
- Command line
-
hf download hf://initial01/vit-base-beans/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/initial01/vit-base-beans/resolve/main/model.safetensors
343 MB
- Xet hash:
- 3bd93c7d617d70a541001f1a6276b5fa993b41d7ff58b3f98d0563123f1b7aae
- Size of remote file:
- 343 MB
- SHA256:
- 056b090d3f0bb978226b0902f2493ea8d8a54519087e88267f57940eae056edd
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