Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

microsoft
/
beit-base-patch16-224

Image Classification
Transformers
PyTorch
JAX
Safetensors
beit
vision
Model card Files Files and versions
xet
Community
4

Instructions to use microsoft/beit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/beit-base-patch16-224 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="microsoft/beit-base-patch16-224")
    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("microsoft/beit-base-patch16-224")
    model = AutoModelForImageClassification.from_pretrained("microsoft/beit-base-patch16-224")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
beit-base-patch16-224 / onnx
Ctrl+K
Ctrl+K
  • 4 contributors
History: 1 commit
Steven75's picture
Steven75
Adding ONNX file of this model
c032326 verified 8 months ago
  • config.json
    70.5 kB
    Adding ONNX file of this model 8 months ago
  • model.onnx
    348 MB
    xet
    Adding ONNX file of this model 8 months ago
  • preprocessor_config.json
    440 Bytes
    Adding ONNX file of this model 8 months ago