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LLM-Detector: Improving AI-generated Chinese Text Detection with Large Language Models
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LLM-Detector: Improving AI-generated Chinese Text Detection with Large Language Models
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers.generation import GenerationConfig
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# Note: The default behavior now has injection attack prevention off.
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tokenizer = AutoTokenizer.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", trust_remote_code=True)
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# use bf16
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# model = AutoModelForCausalLM.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", device_map="auto", trust_remote_code=True, bf16=True).eval()
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# use fp16
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# model = AutoModelForCausalLM.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", device_map="auto", trust_remote_code=True, fp16=True).eval()
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# use cpu only
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# model = AutoModelForCausalLM.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", device_map="cpu", trust_remote_code=True).eval()
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# use auto mode, automatically select precision based on the device.
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model = AutoModelForCausalLM.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", device_map="auto", trust_remote_code=True).eval()
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#model = AutoModelForCausalLM.from_pretrained("QiYuan-tech/LLM-Detector-Small-zh", device_map="auto", trust_remote_code=True).cuda()
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# Specify hyperparameters for generation. But if you use transformers>=4.32.0, there is no need to do this.
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# model.generation_config = GenerationConfig.from_pretrained("./Qwen-1_8B-Chat", trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
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response, history = model.chat(tokenizer, "你好", history=None)
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print(response)
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```
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