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@@ -74,9 +74,9 @@ Performance analysis for one-shot unstructured pruning of SSM modules in Mamba m
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## 🙏 Acknowledgements
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This source code is derived from the famous PyTorch reimplementation of [SparseGPT](https://github.com/IST-DASLab/sparsegpt) and [mamba-minimal](https://github.com/johnma2006/mamba-minimal).
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We use [Mamba checkpoints](https://huggingface.co/state-spaces) to test our method.
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The README file is inspired by [LLM-pruner](https://github.com/horseee/LLM-Pruner).
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-This source code is derived from the famous PyTorch reimplementation of [SparseGPT](https://github.com/IST-DASLab/sparsegpt) and [mamba-minimal](https://github.com/johnma2006/mamba-minimal).
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-We use [Mamba checkpoints](https://huggingface.co/state-spaces) to test our method.
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-The README file is inspired by [LLM-pruner](https://github.com/horseee/LLM-Pruner).
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