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@@ -21,7 +21,7 @@ Below we share some code snippets on how to get quickly started with running the
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  ### Sparse Transfer
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- You can adapt pruned large language models (LLMs) to new domains and tasks using sparse transfer learning. By leveraging a pre-sparsified model's structure, you can efficiently fine-tune on new data, leading to reduced hyperparameter tuning, training times, and computational costs. Learn about this process [here](https://neuralmagic.github.io/docs-v2/get-started/transfer).
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  ### Running the model
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  ### Sparse Transfer
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+ By leveraging a pre-sparsified model's structure, you can efficiently fine-tune on new data, leading to reduced hyperparameter tuning, training times, and computational costs. Learn about this process [here](https://neuralmagic.github.io/docs-v2/get-started/transfer).
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  ### Running the model
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