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license: mit |
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# Compressed LLM Model Zone |
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The models are prepared by [Visual Informatics Group @ University of Texas at Austin (VITA-group)](https://vita-group.github.io/). Credits to Ajay Jaiswal, Zhenyu Zhang, Zhangheng Li, Lu Yin, Shiwei Liu and Junyuan Hong. |
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License: [MIT License](https://opensource.org/license/mit/) |
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Setup environment |
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```shell |
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pip install torch==2.0.0+cu117 torchvision==0.15.1+cu117 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu117 |
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pip install transformers==4.31.0 |
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pip install accelerate |
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pip install auto-gptq # for gptq |
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pip install sentencepiece |
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``` |
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How to use pruned models |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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base_model = 'llama-2-7b' |
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comp_method = 'magnitude_unstructured' |
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comp_degree = 0.2 |
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model_path = f'vita-group/{base_model}_{comp_method}' |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, |
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revision=f's{comp_degree}', |
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torch_dtype=torch.float16, |
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low_cpu_mem_usage=True, |
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device_map="auto" |
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) |
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tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-7b-hf') |
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input_ids = tokenizer('Hello! I am a VITA-compressed-LLM chatbot!', return_tensors='pt').input_ids.cuda() |
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outputs = model.generate(input_ids, max_new_tokens=128) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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How to use wanda+gptq models |
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```python |
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from transformers import AutoTokenizer |
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from auto_gptq import AutoGPTQForCausalLM |
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model_path = 'vita-group/llama-2-7b_wanda_2_4_gptq_4bit_128g' |
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tokenizer_path = 'meta-llama/Llama-2-7b-hf' |
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model = AutoGPTQForCausalLM.from_quantized( |
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model_path, |
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# inject_fused_attention=False, # or |
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disable_exllama=True, |
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device_map='auto', |
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) |
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tokenizer = AutoTokenizer.from_pretrained(tokenizer_path, trust_remote_code=True) |
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input_ids = tokenizer('Hello! I am a VITA-compressed-LLM chatbot!', return_tensors='pt').input_ids.to('cuda') |
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outputs = model.generate(input_ids=input_ids, max_length=128) |
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tokenizer.decode(outputs[0]) |
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``` |
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How to use gptq models |
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```python |
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from transformers import AutoTokenizer |
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from auto_gptq import AutoGPTQForCausalLM |
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# model_path = 'vita-group/llama-2-7b_wanda_2_4_gptq_4bit_128g' |
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# tokenizer_path = 'meta-llama/Llama-2-7b-hf' |
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model_path = 'vita-group/vicuna-7b-v1.3_gptq' |
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tokenizer_path = 'lmsys/vicuna-7b-v1.3' |
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model = AutoGPTQForCausalLM.from_quantized( |
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model_path, |
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# inject_fused_attention=False, # or |
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disable_exllama=True, |
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device_map='auto', |
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revision='2bit_128g', |
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) |
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from transformers import AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained(tokenizer_path, trust_remote_code=True) |
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input_ids = tokenizer('Hello! I am a VITA-compressed-LLM chatbot!', return_tensors='pt').input_ids.to('cuda') |
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outputs = model.generate(input_ids=input_ids, max_length=128) |
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tokenizer.decode(outputs[0]) |
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``` |
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| | Base Model | Model Size | Compression Method | Compression Degree | |
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|---:|:-------------|:-------------|:----------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 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) | |
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| 10 | Llama-2 | 7b | [wanda_gptq](https://huggingface.co/vita-group/llama-2-7b_wanda_2_4_gptq_4bit_128g) | 4bit_128g | |
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| 11 | 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) | |
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| 12 | 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) | |
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| 13 | 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) | |
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| 14 | 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) | |
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| 15 | 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) | |
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| 16 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [10bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/10bit_128g) | |
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| 17 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [12bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/12bit_128g) | |
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| 18 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [14bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/14bit_128g) | |
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| 19 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [2bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/2bit_128g) | |
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| 20 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [3bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/3bit_128g) | |
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| 21 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [4bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/4bit_128g) | |
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| 22 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [6bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/6bit_128g) | |
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| 23 | vicuna-v1.3 | 13b | [gptq](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq) | [8bit_128g](https://huggingface.co/vita-group/vicuna-13b-v1.3_gptq/tree/8bit_128g) | |
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| 24 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [10bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/10bit_128g) | |
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| 25 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [12bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/12bit_128g) | |
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| 26 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [14bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/14bit_128g) | |
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| 27 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [2bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/2bit_128g) | |
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| 28 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [3bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/3bit_128g) | |
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| 29 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [4bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/4bit_128g) | |
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| 30 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [6bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/6bit_128g) | |
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| 31 | vicuna-v1.3 | 7b | [gptq](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq) | [8bit_128g](https://huggingface.co/vita-group/vicuna-7b-v1.3_gptq/tree/8bit_128g) | |
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