Image Classification
Transformers
PyTorch
TensorFlow
TensorBoard
Safetensors
timm_wrapper
vision
Generated from Trainer
Instructions to use amyeroberts/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amyeroberts/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amyeroberts/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("amyeroberts/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("amyeroberts/vit-base-beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2207000b3e06108e8d2e246ce3f5f9f54a3e10b9d34150df7c53fdac8a69286
- Size of remote file:
- 343 MB
- SHA256:
- 18021ad88123e1bc72d90dc4ece816d67f3041e0795a9667c39073a904a20a9d
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