Update README.md (#1)
Browse files- Update README.md (fadd1b9553fff6392b85c52b07c3ab6dac477a0c)
Co-authored-by: Chris Wendler <wendlerc@users.noreply.huggingface.co>
README.md
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tags:
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- deepsparse
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This is a [SparseML](https://github.com/neuralmagic/sparseml) quantized version of https://huggingface.co/laion/CLIP-ViT-B-32-256x256-DataComp-s34B-b86K that is ready to use with [DeepSparse](https://github.com/neuralmagic/deepsparse).
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Notebook for basic usage: [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ZvU9ZSHJKSeJyH5bgxo_A-GSVIUcSt2E?usp=sharing)
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Notebook for Imagenette evaluation: [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1-Duq0YNtjzOnmuXCYo-5DDiOzeCItXpN?usp=sharing)
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tags:
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- deepsparse
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---
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This is a [SparseML](https://github.com/neuralmagic/sparseml) quantized version of https://huggingface.co/laion/CLIP-ViT-B-32-256x256-DataComp-s34B-b86K that is ready to use with [DeepSparse](https://github.com/neuralmagic/deepsparse).
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It achieves **71.1%** zero-shot top-1 accuracy on ImageNet and **95.6%** zero-shot top-1 accuracy on Imagenette.
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For comparison the dense version (the original model) achieves **72.8%** on ImageNet and **95.7%** on Imagenette.
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Notebook for basic usage: [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ZvU9ZSHJKSeJyH5bgxo_A-GSVIUcSt2E?usp=sharing)
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Notebook for Imagenette evaluation: [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1-Duq0YNtjzOnmuXCYo-5DDiOzeCItXpN?usp=sharing)
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