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MLLabIISc
/
ModHiFi-ResNet50-ImageNet-Tiny

Image Classification
Transformers
Safetensors
English
resnet
vision
pruning
sparse
custom_code
Model card Files Files and versions
xet
Community

Instructions to use MLLabIISc/ModHiFi-ResNet50-ImageNet-Tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MLLabIISc/ModHiFi-ResNet50-ImageNet-Tiny with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="MLLabIISc/ModHiFi-ResNet50-ImageNet-Tiny", trust_remote_code=True)
    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("MLLabIISc/ModHiFi-ResNet50-ImageNet-Tiny", trust_remote_code=True)
    model = AutoModelForImageClassification.from_pretrained("MLLabIISc/ModHiFi-ResNet50-ImageNet-Tiny", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
ModHiFi-ResNet50-ImageNet-Tiny
33.8 MB
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  • 1 contributor
History: 4 commits
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Dhruva-hf
Update README.md
69ebf84 verified 3 months ago
  • .gitattributes
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    initial commit 3 months ago
  • README.md
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    Update README.md 3 months ago
  • config.json
    71.3 kB
    Initial Commit 3 months ago
  • model.safetensors
    33.7 MB
    xet
    Initial Commit 3 months ago
  • modelling_pruned_resnet50.py
    4.86 kB
    Initial Commit 3 months ago
  • preprocessor_config.json
    440 Bytes
    Initial Commit 3 months ago