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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
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  • 3 contributors
History: 8 commits
trpakov's picture
trpakov
Update README.md
ef0bc6f verified about 1 year ago
  • onnx
    Adding ONNX file of this model (#2) over 2 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    1.6 kB
    Update README.md about 1 year ago
  • config.json
    915 Bytes
    Upload ViTForImageClassification over 3 years ago
  • model.safetensors
    343 MB
    xet
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • preprocessor_config.json
    228 Bytes
    Upload feature extractor over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict"

    What is a pickle import?

    343 MB
    xet
    Upload ViTForImageClassification over 3 years ago