Image Classification
Transformers
PyTorch
TensorBoard
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use shubhangikarade/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhangikarade/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="shubhangikarade/vit-base-beans") 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("shubhangikarade/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("shubhangikarade/vit-base-beans") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f49111e124d002bf672ecae41a23d863082a6de70e731b0e1a030fba0ee2a2e9
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size 343227052
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