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from transformers import AutoTokenizer, pipeline |
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from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig |
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import torch |
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model_id = "MaziyarPanahi/Smaug-72B-v0.1-GPTQ" |
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quantize_config = BaseQuantizeConfig( |
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bits=4, |
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group_size=128, |
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desc_act=False |
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) |
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model = AutoGPTQForCausalLM.from_quantized( |
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model_id, |
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use_safetensors=True, |
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device="cuda:0", |
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quantize_config=quantize_config) |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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pipe = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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max_new_tokens=512, |
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temperature=0.7, |
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top_p=0.95, |
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repetition_penalty=1.1 |
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) |
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outputs = pipe("What is a large language model?") |
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print(outputs[0]["generated_text"]) |
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