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README.md

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 # Visual Informatics Group @ University of Texas at Austin
 
 At VITA group, we have unusually broad, and forever-evolving research interests spanning from the theory to the application aspects of machine learning (ML). Our current "research keywords" include, but are not limited to: sparsity (from classical optimization to modern neural networks); efficient training, inference or transfer (especially, of large foundation models); robustness and trustworthiness; learning to optimize (L2O); generative AI; graph learning, and more. 
+
+
+## Compressed LLM Model Zone
+
+The models are prepared by [Visual Informatics Group @ University of Texas at Austin (VITA-group)](https://vita-group.github.io/).
+
+License: [MIT License](https://opensource.org/license/mit/)
+
+
+|    | Base Model   | Model Size   | Compression Method     | Compression Degree                                                                    |
+|---:|:-------------|:-------------|:-----------------------|:--------------------------------------------------------------------------------------|
+|  0 | Llama-2      | 7b           | magnitude_unstructured | [s0.1](https://huggingface.co/vita-group/comp-llama-2-7b_magnitude_unstructured_s0.1) |
+|  1 | Llama-2      | 7b           | magnitude_unstructured | [s0.2](https://huggingface.co/vita-group/comp-llama-2-7b_magnitude_unstructured_s0.2) |
+|  2 | Llama-2      | 7b           | magnitude_unstructured | [s0.3](https://huggingface.co/vita-group/comp-llama-2-7b_magnitude_unstructured_s0.3) |
+|  3 | Llama-2      | 7b           | magnitude_unstructured | [s0.5](https://huggingface.co/vita-group/comp-llama-2-7b_magnitude_unstructured_s0.5) |
+|  4 | Llama-2      | 7b           | magnitude_unstructured | [s0.6](https://huggingface.co/vita-group/comp-llama-2-7b_magnitude_unstructured_s0.6) |
+|  5 | Llama-2      | 7b           | sparsegpt_unstructured | [s0.1](https://huggingface.co/vita-group/comp-llama-2-7b_sparsegpt_unstructured_s0.1) |
+|  6 | Llama-2      | 7b           | sparsegpt_unstructured | [s0.2](https://huggingface.co/vita-group/comp-llama-2-7b_sparsegpt_unstructured_s0.2) |
+|  7 | Llama-2      | 7b           | sparsegpt_unstructured | [s0.3](https://huggingface.co/vita-group/comp-llama-2-7b_sparsegpt_unstructured_s0.3) |
+|  8 | Llama-2      | 7b           | sparsegpt_unstructured | [s0.5](https://huggingface.co/vita-group/comp-llama-2-7b_sparsegpt_unstructured_s0.5) |
+|  9 | Llama-2      | 7b           | sparsegpt_unstructured | [s0.6](https://huggingface.co/vita-group/comp-llama-2-7b_sparsegpt_unstructured_s0.6) |
+| 10 | Llama-2      | 7b           | wanda_unstructured     | [s0.1](https://huggingface.co/vita-group/comp-llama-2-7b_wanda_unstructured_s0.1)     |
+| 11 | Llama-2      | 7b           | wanda_unstructured     | [s0.2](https://huggingface.co/vita-group/comp-llama-2-7b_wanda_unstructured_s0.2)     |
+| 12 | Llama-2      | 7b           | wanda_unstructured     | [s0.3](https://huggingface.co/vita-group/comp-llama-2-7b_wanda_unstructured_s0.3)     |
+| 13 | Llama-2      | 7b           | wanda_unstructured     | [s0.5](https://huggingface.co/vita-group/comp-llama-2-7b_wanda_unstructured_s0.5)     |
+| 14 | Llama-2      | 7b           | wanda_unstructured     | [s0.6](https://huggingface.co/vita-group/comp-llama-2-7b_wanda_unstructured_s0.6)     |
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+