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trpakov
/
vit-face-expression

Image Classification
Transformers
PyTorch
ONNX
Safetensors
vit
Model card Files Files and versions
xet
Community
7

Instructions to use trpakov/vit-face-expression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use trpakov/vit-face-expression with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="trpakov/vit-face-expression")
    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("trpakov/vit-face-expression")
    model = AutoModelForImageClassification.from_pretrained("trpakov/vit-face-expression")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
vit-face-expression / onnx
343 MB
Ctrl+K
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  • 3 contributors
History: 1 commit
trpakov's picture
trpakov
Adding ONNX file of this model (#2)
78ed8d3 over 2 years ago
  • config.json
    881 Bytes
    Adding ONNX file of this model (#2) over 2 years ago
  • model.onnx
    343 MB
    xet
    Adding ONNX file of this model (#2) over 2 years ago
  • preprocessor_config.json
    378 Bytes
    Adding ONNX file of this model (#2) over 2 years ago