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:
- caf95fbc5b4956d510887947cb742cba4c9b164eefbc327d6ee60ca99ca417ca
- Size of remote file:
- 5.3 kB
- SHA256:
- 15c6975d22c1fbaef774b8d87f3a9ce454a4951a9ba9333093626322e9867bd0
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