Create README.md

README.md

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+---
+license: mit
+---
+
+# 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/)
+
+Setup environment
+```shell
+pip install torch==2.0.0+cu117 torchvision==0.15.1+cu117 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu117
+pip install transformers==4.31.0
+pip install accelerate
+pip install auto-gptq  # for gptq
+```
+
+How to use pruned models
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+base_model = 'llama-2-7b'
+comp_method = 'magnitude_unstructured'
+comp_degree = 0.2
+model_path = f'vita-group/{base_model}_{comp_method}'
+model = AutoModelForCausalLM.from_pretrained(
+        model_path, 
+        revision=f's{comp_degree}',
+        torch_dtype=torch.float16, 
+        low_cpu_mem_usage=True, 
+        device_map="auto"
+    )
+tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-7b-hf')
+input_ids = tokenizer('Hello! I am a VITA-compressed-LLM chatbot!', return_tensors='pt').input_ids.cuda()
+outputs = model.generate(input_ids, max_new_tokens=128)
+print(tokenizer.decode(outputs[0]))
+```
+
+How to use quantized models
+```python
+from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
+model_path = 'vita-group/llama-2-7b_wanda_2_4_gptq_4bit_128g'
+model = AutoGPTQForCausalLM.from_quantized(
+        model_path,
+        # inject_fused_attention=False, # or 
+        disable_exllama=True,
+        device_map='auto',
+    )
+```
+
+|    | Base Model   | Model Size   | Compression Method                                                                            | Compression Degree                                                                    |
+|---:|:-------------|:-------------|:----------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|
+|  0 | Llama-2      | 7b           | [magnitude_unstructured](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured) | [s0.1](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured/tree/s0.1) |
+|  1 | Llama-2      | 7b           | [magnitude_unstructured](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured) | [s0.2](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured/tree/s0.2) |
+|  2 | Llama-2      | 7b           | [magnitude_unstructured](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured) | [s0.3](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured/tree/s0.3) |
+|  3 | Llama-2      | 7b           | [magnitude_unstructured](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured) | [s0.5](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured/tree/s0.5) |
+|  4 | Llama-2      | 7b           | [magnitude_unstructured](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured) | [s0.6](https://huggingface.co/vita-group/llama-2-7b_magnitude_unstructured/tree/s0.6) |
+|  5 | Llama-2      | 7b           | [sparsegpt_unstructured](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured) | [s0.1](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured/tree/s0.1) |
+|  6 | Llama-2      | 7b           | [sparsegpt_unstructured](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured) | [s0.2](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured/tree/s0.2) |
+|  7 | Llama-2      | 7b           | [sparsegpt_unstructured](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured) | [s0.3](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured/tree/s0.3) |
+|  8 | Llama-2      | 7b           | [sparsegpt_unstructured](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured) | [s0.5](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured/tree/s0.5) |
+|  9 | Llama-2      | 7b           | [sparsegpt_unstructured](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured) | [s0.6](https://huggingface.co/vita-group/llama-2-7b_sparsegpt_unstructured/tree/s0.6) |
+| 10 | Llama-2      | 7b           | [wanda_unstructured](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured)         | [s0.1](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured/tree/s0.1)     |
+| 11 | Llama-2      | 7b           | [wanda_unstructured](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured)         | [s0.2](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured/tree/s0.2)     |
+| 12 | Llama-2      | 7b           | [wanda_unstructured](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured)         | [s0.3](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured/tree/s0.3)     |
+| 13 | Llama-2      | 7b           | [wanda_unstructured](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured)         | [s0.5](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured/tree/s0.5)     |
+| 14 | Llama-2      | 7b           | [wanda_unstructured](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured)         | [s0.6](https://huggingface.co/vita-group/llama-2-7b_wanda_unstructured/tree/s0.6)     |