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44 lines
2.4 KiB
44 lines
2.4 KiB
2 years ago
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import time
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from vllm import LLM, SamplingParams
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prompts = [
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"生成论文小标题内容#问：论文题目是“大学生村官管理研究”，目录是“一、大学生村官管理现状分析\\n1.1 村官数量及分布情况\\n1.2 村官岗位设置及职责\\n1.3 村官工作绩效评估\\n\\n二、大学生村官管理存在的问题\\n2.1 村官队伍结构不合理\\n2.2 村官工作能力不足\\n2.3 村官管理制度不健全\\n\\n三、大学生村官管理对策研究\\n3.1 加强村官队伍建设\\n3.2 提高村官工作能力\\n3.3 完善村官管理制度\\n\\n四、大学生村官管理案例分析\\n4.1 案例一：某村大学生村官工作情况分析\\n4.2 案例二：某村大学生村官管理策略探讨\\n\\n五、大学生村官管理的未来发展趋势\\n5.1 多元化村官队伍建设\\n5.2 信息化村官管理模式\\n5.3 村官职业化发展\\n\\n六、大学生村官管理的政策建议\\n6.1 加强对大学生村官的培训和管理\\n6.2 完善大学生村官管理制度\\n6.3 提高大学生村官的待遇和福利\\n\\n七、结论与展望”，请把其中的小标题“3.3 完善村官管理制度”的内容补充完整，补充内容字数在1500字左右\n答：\n"
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]
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# prompts = [
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# "问：请列出张仲景的所有经方名称\n答：\n"
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# ]
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sampling_params = SamplingParams(temperature=0.95, top_p=0.7,presence_penalty=0.9,stop="</s>", max_tokens=2048)
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models_path = "/home/majiahui/project/models-llm/openbuddy-llama-7b-finetune"
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llm = LLM(model=models_path, tokenizer_mode="slow")
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t1 = time.time()
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outputs = llm.generate(prompts, sampling_params)
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# Print the outputs.
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zishu = 0
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# t2 = time.time()
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for i,output in enumerate(outputs):
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generated_text = output.outputs[0].text
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zishu += len(generated_text)
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print("================================================================================")
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print(i)
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print("=================================================================================")
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print(f"Generated text: {generated_text}")
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t2 = time.time()
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time_cost = t2-t1
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print(time_cost)
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print("speed", zishu/time_cost)
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#
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zishu_one = zishu/time_cost
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print(f"speed: {zishu_one} tokens/s")
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# # from vllm import LLM
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# #
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# # llm = LLM(model="/home/majiahui/models-LLM/openbuddy-llama-7b-v1.4-fp16") # Name or path of your model
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# # output = llm.generate("Hello, my name is")
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# # print(output)
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