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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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Improve model card: add usage example, fix preprocessing details, expand limitations

1
#7 opened 3 months ago by
RamadhanZome

Iphone

#6 opened about 1 year ago by
jonathanprocter

test vit face expression

#4 opened over 1 year ago by
avishekhraj
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