{"id":14737,"date":"2023-09-22T13:33:12","date_gmt":"2023-09-22T05:33:12","guid":{"rendered":"https:\/\/aif.amtbbs.org\/?p=14737"},"modified":"2023-09-22T13:33:12","modified_gmt":"2023-09-22T05:33:12","slug":"%e9%a6%96%e6%ac%a1%e5%87%bb%e8%b4%a5gpt-4%ef%bc%9f700%e4%ba%bf%e5%8f%82%e6%95%b0xwin-lm%e7%99%bb%e9%a1%b6%e6%96%af%e5%9d%a6%e7%a6%8falpacaeval%ef%bc%8c13b%e6%a8%a1%e5%9e%8b%e5%90%8a%e6%89%93chatgpt","status":"publish","type":"post","link":"https:\/\/aif.amtbbs.org\/index.php\/2023\/09\/22\/14737\/","title":{"rendered":"\u9996\u6b21\u51fb\u8d25GPT-4\uff1f700\u4ebf\u53c2\u6570Xwin-LM\u767b\u9876\u65af\u5766\u798fAlpacaEval\uff0c13B\u6a21\u578b\u540a\u6253ChatGPT"},"content":{"rendered":"
\u7b2c\u4e00\u4e2a\u5728AlpacaEval\u4e0a\u8d85\u8d8aGPT-4\u7684\u6a21\u578b\uff0c\u51fa\u73b0\u4e86\uff01<\/section>\n
\u4eca\u5e746\u6708\uff0cAlpacaEval\u699c\u5355\u4e00\u516c\u5e03\uff0cGPT-4\u5c31\u4ee5\u7edd\u5bf9\u9886\u5148\u7684\u4f18\u52bf\u593a\u5f97\u7b2c\u4e00\uff0c\u80dc\u7387\u8d85\u8fc795%\u3002<\/section>\n
\u4e09\u4e2a\u6708\u540e\uff0c\u4e00\u5339\u53ebXwin-LM\u7684\u9ed1\u9a6c\uff0c\u5c45\u7136\u628a\u7a33\u5c45\u699c\u9996\u7684GPT-4\u4eceTOP 1\u62c9\u4e0b\u6765\u4e86\uff1f<\/section>\n

\"\u56fe\u7247\"<\/p>\n

\u9879\u76ee\u5730\u5740\uff1ahttps:\/\/tatsu-lab.github.io\/alpaca_eval\/<\/p>\n

\u800c\u4e14\uff0cXwin-LM\u5728\u540c\u53c2\u6570\u6a21\u578b\u7684\u5bf9\u5792\u4e2d\uff0c\u4e5f\u6beb\u65e0\u4f8b\u5916\u5730\u62ff\u4e0b\u4e86\u4e09\u4e2a\u7b2c\u4e00\uff1a<\/section>\n
\"\u56fe\u7247\"<\/section>\n
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Xwin-LM-70B-V0.1\uff1a\u5728AlpacaEval\u57fa\u51c6\u6d4b\u8bd5\u4e2d\u5bf9Davinci-003\u7684\u80dc\u7387\u8fbe\u523095.57%\uff0c\u5728AlpacaEval\u4e2d\u6392\u540d\u7b2c\u4e00\u3002\u4e5f\u662f\u7b2c\u4e00\u4e2a\u5728AlpacaEval\u4e0a\u8d85\u8d8aGPT-4\u7684\u6a21\u578b\u3002\u6b64\u5916\uff0c\u5b83\u5bf9\u4e0aGPT-4\u7684\u80dc\u7387\u4e3a60.61\u3002<\/section>\n
Xwin-LM-13B-V0.1\uff1a\u5728AlpacaEval\u4e0a\u53d6\u5f97\u4e8691.76%\u7684\u80dc\u7387\uff0c\u5728\u6240\u670913B\u6a21\u578b\u4e2d\u6392\u540d\u7b2c\u4e00\u3002<\/section>\n
Xwin-LM-7B-V0.1\uff1a\u5728AlpacaEval\u4e0a\u53d6\u5f97\u4e8687.82%\u7684\u80dc\u7387\uff0c\u5728\u6240\u67097B\u673a\u578b\u4e2d\u6392\u540d\u7b2c\u4e00\u3002<\/section>\n<\/blockquote>\n
\"\u56fe\u7247\"<\/section>\n
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Xwin-LM\uff1a700\u4ebf\u53c2\u6570\u6253\u8d62GPT-4<\/p>\n<\/section>\n<\/section>\n
Xwin-LM\u662f\u4ee5Llama 2\u4e3a\u57fa\u7840\u8fdb\u884c\u5fae\u8c03\u7684\uff0c\u8be5\u6a21\u578b\u65e8\u5728\u5f00\u53d1\u548c\u5f00\u6e90\u5927\u8bed\u8a00\u6a21\u578b\u7684\u5bf9\u9f50\u6280\u672f\uff0c\u5305\u62ec\u76d1\u7763\u5fae\u8c03\uff08SFT\uff09\u3001\u5956\u52b1\u6a21\u578b\uff08RM\uff09\u3001\u62d2\u7edd\u91c7\u6837\u3001\u4eba\u7c7b\u53cd\u9988\u5f3a\u5316\u5b66\u4e60\uff08RLHF\uff09\u7b49\u3002<\/section>\n
\"\u56fe\u7247\"<\/section>\n
1. \u6027\u80fd\u8bc4\u4f30<\/strong><\/section>\n
\u7814\u7a76\u4eba\u5458\u8bc4\u4f30\u4e86Xwin-LM\u5728805\u4e2a\u95ee\u9898\u4e0a\u4e0eText-Davinci-003 \u3001ChatGPT\u548cGPT-4\u7684\u80dc\u7387\u3002<\/section>\n
\u53ef\u4ee5\u770b\u5230\uff0cXwin-LM\u768470B\u6a21\u578b\u5b8c\u5168\u9738\u699c\uff0c\u6210\u4e3aAlpacaEval\u6307\u6807\u4e0a\u7684\u6027\u80fd\u8bc4\u4f30\u7684\u7b2c\u4e00\uff0c\u5e76\u9996\u6b21\u6253\u8d25\u4e86GPT-4\uff0c\u5bf9GPT-4\u7684\u80dc\u7387\u8fbe\u5230\u4e8660.61%\u3002<\/section>\n
Xwin-LM\u5176\u4ed6\u89c4\u6a21\u7684\u6a21\u578b\uff0c\u5982Xwin-LM-13B-V0.1\u3001Xwin-LM-7B-V0.1\u5728\u6027\u80fd\u4e0a\u4e5f\u8fdc\u8d85\u76f8\u540c\u89c4\u6a21\u7684\u5176\u4ed6\u6a21\u578b\u3002<\/section>\n
Xwin-LM-7B-V0.1\u751a\u81f3\u8d85\u8fc7\u4e86\u6bd4\u5b83\u89c4\u6a21\u66f4\u5927\u7684Llama 2-13B-Chat\u3002<\/section>\n
\"\u56fe\u7247\"<\/section>\n
2. \u6848\u4f8b\u6bd4\u8f83<\/strong><\/section>\n
\"\u56fe\u7247\"<\/section>\n
\u5728\u7b2c\u4e00\u4e2a\u6848\u4f8b\u4e2d\uff0c\u7814\u7a76\u4eba\u5458\u5411GPT-4\u548cXwin-LM\u63d0\u95ee\uff1a<\/section>\n
\u300c\u6211\u628a\u4e00\u4e2a\u76d8\u5b50\u653e\u5728\u82f9\u679c\u4e0a\u9762\uff0c\u7136\u540e\u628a\u76d8\u5b50\u4ece\u53a8\u623f\u5e26\u5230\u9910\u5385\u3002\u82f9\u679c\u73b0\u5728\u5728\u54ea\u91cc\uff1f\u300d<\/section>\n
GPT-4\u7684\u56de\u7b54\u662f\uff1a<\/section>\n
\u300c\u82f9\u679c\u73b0\u5728\u5728\u9910\u5385\uff0c\u5f53\u4f60\u628a\u76d8\u5b50\u4ece\u53a8\u623f\u5230\u7aef\u9910\u5385\u65f6\uff0c\u5b83\u5c31\u5728\u76d8\u5b50\u4e0b\u9762\u3002\u300d<\/section>\n
\u5728\u8fd9\u91ccGPT-4\u7ed9\u51fa\u4e86\u4e00\u4e2a\u7f3a\u5c11\u5e38\u8bc6\u7684\u56de\u590d\uff0c\u73b0\u5b9e\u751f\u6d3b\u4e2d\u6709\u91cd\u529b\uff0c\u5728\u76d8\u5b50\u4e0b\u65b9\u7684\u82f9\u679c\u4fdd\u6301\u539f\u6765\u7684\u72b6\u6001\uff0c\u5e76\u4e0d\u4f1a\u548c\u76d8\u5b50\u4e00\u8d77\u5230\u9910\u5385\u3002<\/section>\n
\u76f8\u6bd4\u4e4b\u4e0b\uff0cXwin-LM\u7684\u56de\u7b54\u5c31\u6bd4\u8f83\u7b26\u5408\u73b0\u5b9e\u60c5\u51b5\uff0c\u5e76\u4e14\u8fd8\u7ed9\u51fa\u4e86\u628a\u82f9\u679c\u5e26\u5230\u53a8\u623f\u7684\u65b9\u6cd5\uff1a<\/section>\n
\u300c\u82f9\u679c\u8fd8\u5728\u53a8\u623f\u91cc\uff0c\u56e0\u4e3a\u4f60\u53ea\u662f\u79fb\u52a8\u4e86\u76d8\u5b50\u3002<\/section>\n
\u82f9\u679c\u5728\u76d8\u5b50\u4e0b\u9762\uff0c\u6240\u4ee5\u5982\u679c\u4f60\u60f3\u628a\u82f9\u679c\u5e26\u5230\u9910\u5385\uff0c\u4f60\u5e94\u8be5\u76f4\u63a5\u79fb\u52a8\u82f9\u679c\u6216\u628a\u82f9\u679c\u653e\u5728\u76d8\u5b50\u91cc\uff0c\u7136\u540e\u628a\u76d8\u5b50\u79fb\u5230\u9910\u5385\u3002\u300d<\/section>\n
\u5728\u7b2c\u4e8c\u4e2a\u6848\u4f8b\u4e2d\uff0c\u7814\u7a76\u4eba\u5458\u5411GPT-4\u548cXwin-LM\u63d0\u95ee\uff1a<\/section>\n
\u300c\u600e\u4e48\u6cd5\u8bed\u8bf4\u300e\u665a\u4e0a\u597d\u300f\uff1f\u300d<\/section>\n
GPT-4\u7684\u56de\u7b54\u662f\uff1a<\/section>\n
\u300c\u5728\u6cd5\u8bed\u4e2d\uff0c\u300e\u665a\u4e0a\u597d\u300f\u7528\u300ebonsoir\u300f\u8868\u8fbe\u3002\u300d<\/section>\n
\u800cXwin-LM\u7684\u56de\u7b54\u662f\uff1a<\/section>\n
\u300c\u5728\u6cd5\u8bed\u4e2d\uff0c\u300e\u665a\u4e0a\u597d\u300f\u88ab\u7ffb\u8bd1\u4e3a\u300ebonsoir\u300f\u3002\u8fd9\u79cd\u95ee\u5019\u8bed\u5728\u665a\u4e0a\u548c\u591c\u95f4\u4f7f\u7528\uff0c\u901a\u5e38\u5728\u4e0b\u5348 6 \u70b9\u4e4b\u540e\u3002<\/section>\n
\u5b83\u662f\u300ebon\u300f\uff08\u610f\u601d\u662f\u597d\uff09\u548c\u300esoir\u300f\uff08\u610f\u601d\u662f\u665a\u4e0a\uff09\u7684\u7ec4\u5408\u3002\u8981\u53d1\u97f3\uff0c\u8bf7\u8bf4\u300ebone-swahr\u300f\u300d\u3002<\/section>\n
\u867d\u7136GPT-4\u7684\u56de\u7b54\u662f\u6b63\u786e\u7684\uff0c\u4f46Xwin-LM\u4e0d\u4ec5\u6b63\u786e\u56de\u7b54\u4e86\u95ee\u9898\uff0c\u8fd8\u89e3\u91ca\u4e86\u6cd5\u8bed\u8868\u8fbe\u4e2d\u300c\u665a\u4e0a\u597d\u300d\u7684\u6765\u6e90\u548c\u53d1\u97f3\uff0c\u53cd\u9988\u7ed9\u7528\u6237\u7684\u4fe1\u606f\u66f4\u52a0\u4e30\u5bcc\u3002<\/section>\n
3. NLP\u4efb\u52a1<\/strong><\/section>\n
\u4e0b\u8868\u662fXwin-LM\u4e0e\u5176\u4ed6LLM\u5728NLP\u57fa\u7840\u4efb\u52a1\u4e0a\u7684\u6bd4\u8f83\u3002<\/section>\n
\u53ef\u4ee5\u770b\u5230\uff0cXwin-LM-70B-V0.1\u6a21\u578b\u5728\u6240\u6709\u4efb\u52a1\u4e2d\u7684\u6027\u80fd\u90fd\u76f8\u5bf9\u8f83\u9ad8\uff0c\u5728MMLU 5-shot\u548cHellaSwag 10-shot\u4efb\u52a1\u4e2d\u66f4\u662f\u8868\u73b0\u51fa\u8272\u3002<\/section>\n
\u5e76\u4e14\uff0c\u4ece\u7efc\u5408\u6c34\u5e73\u4e0a\u6765\u8bf4\uff0cXwin-LM-70B-V0.1\u662f\u8868\u73b0\u6700\u597d\u7684\u3002<\/section>\n
\"\u56fe\u7247\"<\/section>\n
4. \u63a8\u7406\u80fd\u529b<\/strong><\/section>\n
\u7814\u7a76\u4eba\u5458\u63d0\u51fa\uff0c\u4e3a\u4e86\u5728\u4f7f\u7528Xwin-LM\u8fdb\u884c\u63a8\u7406\u65f6\u83b7\u5f97\u6240\u9700\u7684\u7ed3\u679c\uff0c\u9700\u8981\u4e25\u683c\u9075\u5b88\u63a8\u7406\u7684\u5bf9\u8bdd\u6a21\u677f\u3002<\/section>\n
Xwin-LM\u91c7\u7528Vicuna\u5efa\u7acb\u7684\u63d0\u793a\u683c\u5f0f\uff0c\u5e76\u652f\u6301\u591a\u56de\u5408\u5bf9\u8bdd\u3002<\/section>\n
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    A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: Hi! ASSISTANT: Hello.<\/s<\/span>><\/span>USER: Who are you? ASSISTANT: I am Xwin-LM.<\/s<\/span>><\/span>......<\/span><\/code><\/pre>\n<\/section>\n
    HuggingFace\u793a\u4f8b<\/strong><\/section>\n
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      from transformers import AutoTokenizer, AutoModelForCausalLM<\/span><\/code>\r\n<\/span><\/code>model = AutoModelForCausalLM.from_pretrained(\"Xwin-LM\/Xwin-LM-7B-V0.1\"<\/span>)<\/span><\/code>tokenizer = AutoTokenizer.from_pretrained(\"Xwin-LM\/Xwin-LM-7B-V0.1\"<\/span>)<\/span><\/code>(<\/span><\/code>    prompt := \"A chat between a curious user and an artificial intelligence assistant. \"<\/span><\/span><\/code>            \"The assistant gives helpful, detailed, and polite answers to the user's questions. \"<\/span><\/span><\/code>            \"USER: Hello, can you help me? \"<\/span><\/span><\/code>            \"ASSISTANT:\"<\/span><\/span><\/code>)<\/span><\/code>inputs = tokenizer(prompt, return_tensors=\"pt\"<\/span>)<\/span><\/code>samples = model.generate(**inputs, max_new_tokens=4096, temperature=0.7)<\/span><\/code>output = tokenizer.decode(samples[0][inputs[\"input_ids\"<\/span>].shape[1]:], skip_special_tokens=True)<\/span><\/code>print(output) <\/span><\/code># Of course! I'm here to help. Please feel free to ask your question or describe the issue you're having, and I'll do my best to assist you.<\/span><\/span><\/code>\r\n<\/span><\/code><\/pre>\n<\/section>\n
      VLLM\u793a\u4f8b<\/strong><\/section>\n
      \u56e0\u4e3aXwin-LM\u662f\u57fa\u4e8eLlama 2\u5fae\u8c03\u800c\u6765\uff0c\u5b83\u8fd8\u652f\u6301\u4f7f\u7528VLLM\u8fdb\u884c\u5feb\u901f\u63a8\u7406\u3002<\/section>\n
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        from vllm import LLM, SamplingParams<\/span><\/code>(<\/span><\/code>    prompt := \"A chat between a curious user and an artificial intelligence assistant. \"<\/span><\/span><\/code>            \"The assistant gives helpful, detailed, and polite answers to the user's questions. \"<\/span><\/span><\/code>            \"USER: Hello, can you help me? \"<\/span><\/span><\/code>            \"ASSISTANT:\"<\/span><\/span><\/code>)<\/span><\/code>sampling_params = SamplingParams(temperature=0.7, max_tokens=4096)<\/span><\/code>llm = LLM(model=\"Xwin-LM\/Xwin-LM-7B-V0.1\"<\/span>)<\/span><\/code>outputs = llm.generate([prompt,], sampling_params)<\/span><\/code>\r\n<\/span><\/code>for output in outputs:<\/span><\/code>    prompt = output.prompt<\/span><\/code>    generated_text = output.outputs[0].text<\/span><\/code>    print(generated_text)<\/span><\/code>\r\n<\/span><\/code><\/pre>\n<\/section>\n
        \n
        AlpacaEval\uff1a\u6613\u4f7f\u7528\u3001\u901f\u5ea6\u5feb\u3001\u6210\u672c\u4f4e\u3001\u7ecf\u8fc7\u4eba\u7c7b\u6807\u6ce8\u9a8c\u8bc1<\/p>\n<\/section>\n<\/section>\n
        \u4f5c\u4e3a\u4e00\u6b3eLLM\u81ea\u52a8\u8bc4\u4f30\u5de5\u5177\uff0cAlpacaEval\u628aAlpacaFarm\u548cAviary\u8fdb\u884c\u4e86\u7ed3\u5408\u3002<\/section>\n
        \u4e00\u65b9\u9762\u4f7f\u7528\u4e0eAlpacaFarm\u76f8\u540c\u7684\u4ee3\u7801\uff08\u7f13\u5b58\/\u968f\u673a\u6392\u5217\/\u8d85\u53c2\u6570\uff09\uff0c\u53e6\u4e00\u65b9\u9762\u5219\u4f7f\u7528\u7c7b\u4f3c\u4e8eAviary\u7684\u6392\u5e8f\u63d0\u793a\u3002<\/section>\n
        \u4e0e\u6b64\u540c\u65f6\uff0c\u8fd8\u5bf9Aviary\u7684\u63d0\u793a\u8fdb\u884c\u4e86\u4fee\u6539\uff0c\u4ece\u800c\u51cf\u5c11\u5bf9\u8f83\u957f\u8f93\u51fa\u7684\u504f\u89c1\u3002<\/section>\n
        \u56e2\u961f\u8868\u793a\uff0cAlpacaEval\u6709\u7740\u62d4\u7fa4\u7684\u6548\u679c\uff1a<\/section>\n
        – \u4e0e\u4eba\u7c7b\u591a\u6570\u7968\u7684\u4e00\u81f4\u6027\uff0c\u9ad8\u4e8e\u5355\u4e2a\u4eba\u7c7b\u6807\u6ce8\u8005<\/section>\n
        – \u80dc\u7387\u4e0e\u4eba\u7c7b\u6807\u6ce8\u9ad8\u5ea6\u76f8\u5173\uff080.94\uff09<\/section>\n
        \"\u56fe\u7247\"<\/section>\n
        – \u80dc\u7387<\/strong><\/section>\n
        \u6a21\u578b\u7684\u8f93\u51fa\u5728\u6bcf\u4e2a\u6307\u4ee4\u4e0a\u4f18\u4e8etext-davinci-003\uff08\u5373\u53c2\u8003\u6587\u672c\uff09\u7684\u6bd4\u4f8b\u3002<\/section>\n
        \u5177\u4f53\u800c\u8a00\uff0c\u9996\u5148\u4eceAlpacaEval\u6570\u636e\u96c6\u4e2d\u6536\u96c6\u4e86\u671f\u671b\u6a21\u578b\u5728\u6bcf\u4e2a\u6307\u4ee4\u4e0a\u7684\u8f93\u51fa\u5bf9\uff0c\u5e76\u5c06\u6bcf\u4e2a\u8f93\u51fa\u4e0e\u76f8\u540c\u6307\u4ee4\u4e0b\u7684\u53c2\u8003\u6a21\u578b\uff08text-davinci-003\uff09\u7684\u8f93\u51fa\u8fdb\u884c\u914d\u5bf9\u3002<\/section>\n
        \u968f\u540e\uff0c\u628a\u8fd9\u4e9b\u8f93\u51fa\u540c\u65f6\u5582\u7ed9\u81ea\u52a8\u8bc4\u6d4b\u5668\uff0c\u8ba9\u5b83\u53bb\u5224\u65ad\u54ea\u4e00\u4e2a\u66f4\u597d\uff08\u4e5f\u5c31\u662f\u8bc4\u6d4b\u5668\u7684\u504f\u597d\uff09\u3002<\/section>\n
        \u6700\u540e\uff0c\u5c06\u6570\u636e\u96c6\u4e2d\u6240\u6709\u6307\u4ee4\u7684\u504f\u597d\u8fdb\u884c\u5e73\u5747\uff0c\u4ece\u800c\u5f97\u5230\u6a21\u578b\u76f8\u5bf9\u4e8etext-davinci-003\u7684\u80dc\u7387\u3002\u5982\u679c\u4e24\u4e2a\u6a21\u578b\u6253\u5e73\uff0c\u90a3\u4e48\u5c31\u7b97\u534a\u4e2a\u504f\u597d\u3002<\/section>\n
        \"\u56fe\u7247\"<\/p>\n
        \u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/2305.14387.pdf<\/section>\n
        – \u5c40\u9650\u6027<\/strong><\/section>\n
        \u867d\u7136AlpacaEval\u4e3a\u6bd4\u8f83\u6a21\u578b\u9075\u5faa\u6307\u4ee4\u7684\u80fd\u529b\u63d0\u4f9b\u4e86\u4e00\u79cd\u6709\u6548\u7684\u65b9\u6cd5\uff0c\u4f46\u5b83\u5e76\u4e0d\u662f\u5bf9\u6a21\u578b\u80fd\u529b\u8fdb\u884c\u5168\u9762\u8bc4\u4f30\u7684\u9ec4\u91d1\u6807\u51c6\u3002<\/section>\n
        \u6b63\u5982AlpacaFarm\u8bba\u6587\u4e2d\u8be6\u8ff0\u7684\u90a3\u6837\uff0c\u81ea\u52a8\u6807\u6ce8\u5668\u7684\u80dc\u7387\u4e0e\u957f\u5ea6\u76f8\u5173\u3002\u867d\u7136\u4eba\u7c7b\u6807\u6ce8\u4e5f\u4f1a\u6709\u8fd9\u79cd\u504f\u5dee\uff0c\u4f46\u76ee\u524d\u8fd8\u4e0d\u6e05\u695a\u66f4\u957f\u7684\u7b54\u6848\u662f\u5426\u4f1a\u589e\u52a0\u4e0b\u6e38\u4efb\u52a1\u7684\u6548\u7528\u3002<\/section>\n
        \u6b64\u5916\uff0cAlpacaFarm\u7684\u8bc4\u4f30\u96c6\u867d\u7136\u591a\u79cd\u591a\u6837\uff0c\u4f46\u4e3b\u8981\u7531\u7b80\u5355\u7684\u6307\u4ee4\u7ec4\u6210\u3002<\/section>\n
        \u6700\u540e\uff0cAlpacaEval\u5e76\u4e0d\u8bc4\u4f30\u4efb\u4f55\u6a21\u578b\u7684\u5b89\u5168\u6027\u3002<\/section>\n
        <\/div>\n
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        \u7b2c\u4e00\u4e2a\u5728AlpacaEval\u4e0a\u8d85\u8d8aGPT-4\u7684\u6a21\u578b\uff0c\u51fa\u73b0\u4e86\uff01 \u4eca\u5e746\u6708\uff0cAlpacaEval\u699c\u5355\u4e00\u516c\u5e03\uff0cGPT […]<\/p>\n
        <\/div>\n
        <\/g><\/svg><\/i> \"Loading\"<\/p>\n
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