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nateraw
/
vit-base-beans

Image Classification
Transformers
PyTorch
TensorBoard
English
vit
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
7

Instructions to use nateraw/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nateraw/vit-base-beans with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="nateraw/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("nateraw/vit-base-beans")
    model = AutoModelForImageClassification.from_pretrained("nateraw/vit-base-beans")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Librarian Bot: Update Hugging Face dataset ID

#7 opened about 2 years ago by
librarian-bot

Librarian Bot: Add base_model information to model

#6 opened over 2 years ago by
librarian-bot

Adding `safetensors` variant of this model

#5 opened about 3 years ago by
SFconvertbot

Make Predictions?

10
#1 opened almost 4 years ago by
sudo-s
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