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{"id":34948,"date":"2024-10-13T22:09:35","date_gmt":"2024-10-13T14:09:35","guid":{"rendered":"https:\/\/linguaresources.com\/?p=34948"},"modified":"2024-10-13T22:09:35","modified_gmt":"2024-10-13T14:09:35","slug":"hugging-face%e6%8e%a8%e5%87%ba%e6%96%b0%e5%b7%a5%e5%85%b7%ef%bc%8c%e5%bc%80%e5%8f%91%e8%80%85%e5%8f%aa%e9%9c%80%e5%87%a0%e5%88%86%e9%92%9f%e5%b0%b1%e8%83%bd%e7%94%a8openai%e6%9e%84%e5%bb%baai%e9%a9%b1","status":"publish","type":"post","link":"https:\/\/linguaresources.com\/?p=34948","title":{"rendered":"Hugging Face\u63a8\u51fa\u65b0\u5de5\u5177\uff0c\u5f00\u53d1\u8005\u53ea\u9700\u51e0\u5206\u949f\u5c31\u80fd\u7528OpenAI\u6784\u5efaAI\u9a71\u52a8\u7684\u7f51\u7edc\u5e94\u7528"},"content":{"rendered":"

 <\/p>\n

Hugging Face\u53d1\u5e03\u4e86\u4e00\u6b3e\u521b\u65b0\u7684Python\u5305\uff0c\u5f00\u53d1\u8005\u4ec5\u7528\u51e0\u884c\u4ee3\u7801\u5373\u53ef\u521b\u5efaAI\u9a71\u52a8\u7684\u7f51\u7edc\u5e94\u7528\u3002<\/p>\n

\u8fd9\u4e2a\u540d\u4e3a\u201cOpenAI-Gradio\u201d\u7684\u5de5\u5177\u7b80\u5316\u4e86\u5c06OpenAI\u7684\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08large language models\uff0c\u7b80\u79f0LLMs\uff09\u96c6\u6210\u5230\u7f51\u7edc\u5e94\u7528\u4e2d\u7684\u8fc7\u7a0b\uff0c\u4f7f\u5f97\u5404\u4e2a\u6280\u80fd\u6c34\u5e73\u7684\u5f00\u53d1\u8005\u90fd\u80fd\u66f4\u5bb9\u6613\u5730\u4f7f\u7528AI\u3002<\/p>\n

\u5f00\u53d1\u8005\u5982\u4f55\u7528<\/strong>OpenAI-Gradio<\/strong>\u5728\u51e0\u5206\u949f\u5185\u521b\u5efa\u7f51\u7edc\u5e94\u7528<\/strong><\/p>\n

OpenAI-Gradio\u5305\u5c06OpenAI\u7684API\u4e0eGradio\u96c6\u6210\uff0c\u540e\u8005\u662f\u4e00\u4e2a\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\uff08machine learning\uff0c\u7b80\u79f0ML\uff09\u5e94\u7528\u754c\u9762\u5de5\u5177\u3002<\/p>\n

\u5f00\u53d1\u8005\u53ea\u9700\u51e0\u4e2a\u6b65\u9aa4\u5c31\u80fd\u5b89\u88c5\uff0c\u8bbe\u7f6e\u4ed6\u4eec\u7684OpenAI API\u5bc6\u94a5\uff0c\u5e76\u542f\u52a8\u4e00\u4e2a\u5168\u529f\u80fd\u7684\u7f51\u7edc\u5e94\u7528\u3002<\/p>\n

\u8fd9\u79cd\u7b80\u5355\u7684\u8bbe\u7f6e\u4f7f\u5f97\u8d44\u6e90\u6709\u9650\u7684\u5c0f\u578b\u56e2\u961f\u4e5f\u80fd\u5feb\u901f\u90e8\u7f72\u5148\u8fdb\u7684AI\u6a21\u578b\u3002<\/p>\n

\u4f8b\u5982\uff0c\u5728\u5b89\u88c5\u540e\uff1a<\/p>\n

pip install openai-gradio<\/em><\/p>\n

\u5f00\u53d1\u8005\u53ef\u4ee5\u7f16\u5199\u5982\u4e0b\u4ee3\u7801\uff1a<\/p>\n

import gradio as gr<\/em><\/p>\n

import openai_gradio<\/em><\/p>\n

\u00a0<\/em><\/p>\n

gr.load(<\/em><\/p>\n

\u00a0\u00a0\u00a0 name=’gpt-4-turbo’,<\/em><\/p>\n

\u00a0\u00a0\u00a0 src=openai_gradio.registry,<\/em><\/p>\n

).launch()<\/em><\/p>\n

\u8fd9\u5c11\u91cf\u7684\u4ee3\u7801\u5c31\u80fd\u542f\u52a8\u4e00\u4e2a\u8fde\u63a5\u5230OpenAI\u7684GPT-4-turbo\u6a21\u578b\u7684Gradio\u754c\u9762\uff0c\u5141\u8bb8\u7528\u6237\u76f4\u63a5\u4ece\u7f51\u7edc\u5e94\u7528\u4e2d\u4e0e\u5148\u8fdb\u7684AI\u4e92\u52a8\u3002<\/p>\n

\u5f00\u53d1\u8005\u8fd8\u53ef\u4ee5\u8fdb\u4e00\u6b65\u81ea\u5b9a\u4e49\u754c\u9762\uff0c\u6dfb\u52a0\u7279\u5b9a\u7684\u8f93\u5165\u548c\u8f93\u51fa\u914d\u7f6e\uff0c\u751a\u81f3\u5c06\u5e94\u7528\u5d4c\u5165\u5230\u66f4\u5927\u7684\u9879\u76ee\u4e2d\u3002<\/p>\n

\u4e3a\u5404\u7c7b\u4f01\u4e1a\u7b80\u5316<\/strong>AI<\/strong>\u5f00\u53d1<\/strong><\/p>\n

Hugging Face\u7684OpenAI-Gradio\u5305\u6d88\u9664\u4e86AI\u5f00\u53d1\u4e2d\u7684\u4f20\u7edf\u969c\u788d\uff0c\u4f8b\u5982\u7ba1\u7406\u590d\u6742\u7684\u540e\u7aef\u57fa\u7840\u8bbe\u65bd\u6216\u5904\u7406\u6a21\u578b\u6258\u7ba1\u3002<\/p>\n

\u89e3\u51b3\u4e86\u8fd9\u4e9b\u6311\u6218\uff0c\u8be5\u5305\u4f7f\u5404\u7c7b\u89c4\u6a21\u7684\u4f01\u4e1a\u65e0\u9700\u5e9e\u5927\u7684\u5de5\u7a0b\u56e2\u961f\u6216\u663e\u8457\u7684\u4e91\u57fa\u7840\u8bbe\u65bd\u5373\u53ef\u6784\u5efa\u548c\u90e8\u7f72AI\u9a71\u52a8\u7684\u5e94\u7528\u3002<\/p>\n

\u8fd9\u4e00\u8f6c\u53d8\u8ba9\u66f4\u591a\u4f01\u4e1a\u66f4\u5bb9\u6613\u83b7\u5f97\u4eba\u5de5\u667a\u80fd\u5f00\u53d1\u3002\u65e0\u9700\u590d\u6742\u7684\u57fa\u7840\u8bbe\u65bd\uff0c\u5c0f\u578b\u548c\u4e2d\u578b\u516c\u53f8\u3001\u521d\u521b\u4f01\u4e1a\u548c\u5728\u7ebf\u96f6\u552e\u5546\u73b0\u5728\u53ef\u4ee5\u5feb\u901f\u8bd5\u9a8cAI\u9a71\u52a8\u7684\u5de5\u5177\uff0c\u5982\u81ea\u52a8\u5316\u5ba2\u6237\u670d\u52a1\u7cfb\u7edf\u6216\u4e2a\u6027\u5316\u4ea7\u54c1\u63a8\u8350\u3002<\/p>\n

\u501f\u52a9\u8fd9\u4e9b\u65b0\u5de5\u5177\uff0c\u516c\u53f8\u53ef\u4ee5\u5728\u6570\u5929\u800c\u975e\u6570\u6708\u5185\u521b\u5efa\u548c\u542f\u52a8AI\u9879\u76ee\u3002<\/p>\n

\u4ec5\u7528\u51e0\u884c\u4ee3\u7801\u81ea\u5b9a\u4e49<\/strong>AI<\/strong>\u754c\u9762<\/strong><\/p>\n

openai-gradio\u7684\u4e00\u4e2a\u7a81\u51fa\u7279\u70b9\u662f\u5f00\u53d1\u8005\u53ef\u4ee5\u8f7b\u677e\u5730\u4e3a\u7279\u5b9a\u5e94\u7528\u81ea\u5b9a\u4e49\u754c\u9762\u3002<\/p>\n

\u6dfb\u52a0\u51e0\u884c\u4ee3\u7801\uff0c\u4ed6\u4eec\u53ef\u4ee5\u8c03\u6574\u4ece\u8f93\u5165\u5b57\u6bb5\u5230\u8f93\u51fa\u683c\u5f0f\u7684\u4e00\u5207\u8fc7\u7a0b\uff0c\u5b9a\u5236\u5e94\u7528\u4ee5\u6267\u884c\u8bf8\u5982\u56de\u7b54\u5ba2\u6237\u67e5\u8be2\u6216\u751f\u6210\u62a5\u544a\u7684\u4efb\u52a1\u3002<\/p>\n

\u4f8b\u5982\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u4fee\u6539\u754c\u9762\u4ee5\u5305\u542b\u7279\u5b9a\u7684\u63d0\u793a\u548c\u54cd\u5e94\uff0c\u8c03\u6574\u4ece\u8f93\u5165\u65b9\u6cd5\u5230\u8f93\u51fa\u683c\u5f0f\u7684\u4e00\u5207\u8fc7\u7a0b\u3002<\/p>\n

\u8fd9\u53ef\u80fd\u6d89\u53ca\u521b\u5efa\u4e00\u4e2a\u5904\u7406\u5ba2\u6237\u670d\u52a1\u95ee\u9898\u7684\u804a\u5929\u673a\u5668\u4eba\u6216\u4e00\u4e2a\u57fa\u4e8e\u7528\u6237\u8f93\u5165\u751f\u6210\u60f3\u6cd5\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\u3002<\/p>\n

Gradio\u63d0\u4f9b\u4e86\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n

gr.load(<\/em><\/p>\n

\u00a0\u00a0\u00a0 name=’gpt-4-turbo’,<\/em><\/p>\n

\u00a0\u00a0\u00a0 src=openai_gradio.registry,<\/em><\/p>\n

\u00a0\u00a0\u00a0 title=’OpenAI-Gradio Integration’,<\/em><\/p>\n

\u00a0\u00a0\u00a0 description=”Chat with GPT-4-turbo model.”,<\/em><\/p>\n

\u00a0\u00a0\u00a0 examples=[“Explain quantum gravity to a 5-year-old.”, “How many R’s are in the word Strawberry?”]<\/em><\/p>\n

).launch()<\/em><\/p>\n

\u8be5\u5de5\u5177\u7684\u7075\u6d3b\u6027\u53ef\u4ee5\u5b9e\u73b0\u65e0\u7f1d\u96c6\u6210\u5230\u66f4\u5e7f\u6cdb\u7684\u57fa\u4e8e\u7f51\u9875\u7684\u9879\u76ee\u6216\u72ec\u7acb\u5e94\u7528\u4e2d\u3002<\/p>\n

\u8be5\u5305\u8fd8\u53ef\u4ee5\u65e0\u7f1d\u96c6\u6210\u5230\u66f4\u5927\u7684Gradio\u7f51\u9875UI\uff08user interface\uff0c\u7b80\u79f0UI\uff0c\u7528\u6237\u754c\u9762\uff09\u4e2d\uff0c\u5141\u8bb8\u5728\u5355\u4e2a\u5e94\u7528\u4e2d\u4f7f\u7528\u591a\u4e2a\u6a21\u578b\u3002<\/p>\n

\u4e3a\u4ec0\u4e48\u8fd9\u5f88\u91cd\u8981\uff1a<\/strong>Hugging Face<\/strong>\u5728<\/strong>AI<\/strong>\u5f00\u53d1\u4e2d\u7684\u5f71\u54cd\u529b\u4e0d\u65ad\u589e\u957f<\/strong><\/p>\n

Hugging Face\u7684\u6700\u65b0\u53d1\u5e03\u4f7f\u5176\u6210\u4e3aAI\u57fa\u7840\u8bbe\u65bd\u9886\u57df\u7684\u5173\u952e\u89d2\u8272\u3002\u901a\u8fc7\u7b80\u5316\u5c06OpenAI\u6a21\u578b\u96c6\u6210\u5230\u73b0\u5b9e\u5e94\u7528\u4e2d\u7684\u8fc7\u7a0b\uff0cHugging Face\u6b63\u5728\u63a8\u52a8\u5f00\u53d1\u8005\u5728\u8d44\u6e90\u6709\u9650\u7684\u60c5\u51b5\u4e0b\u5b9e\u73b0\u66f4\u591a\u6210\u679c\u3002<\/p>\n

\u8fd9\u4e00\u4e3e\u63aa\u4e5f\u6807\u5fd7\u7740\u5411AI\u4f18\u5148\u5f00\u53d1\u7684\u66f4\u5e7f\u6cdb\u8d8b\u52bf\uff0c\u4f01\u4e1a\u53ef\u4ee5\u66f4\u5feb\u5730\u8fed\u4ee3\u5e76\u5c06\u5c16\u7aef\u6280\u672f\u6295\u5165\u751f\u4ea7\u3002<\/p>\n

openai-gradio\u5305\u662fHugging Face\u66f4\u5e7f\u6cdb\u6218\u7565\u7684\u4e00\u90e8\u5206\uff0c\u65e8\u5728\u8d4b\u80fd\u5f00\u53d1\u8005\u5e76\u98a0\u8986\u4f20\u7edf\u7684AI\u6a21\u578b\u5f00\u53d1\u5468\u671f\u3002<\/p>\n

\u6b63\u5982OpenAI\u7684\u9996\u5e2d\u4ea7\u54c1\u5b98\u51ef\u6587\u00b7\u5a01\u5c14\uff08Kevin Weil\uff09\u5728\u516c\u53f8\u6700\u8fd1\u7684DevDay\u4e0a\u6240\u63d0\u5230\u7684\uff0c\u51cf\u5c11\u5e94\u7528AI\u7684\u969c\u788d\u5bf9\u4e8e\u52a0\u901f\u5176\u5728\u5404\u884c\u4e1a\u7684\u5e94\u7528\u81f3\u5173\u91cd\u8981\u3002<\/p>\n

Hugging Face\u7684\u5b89\u88c5\u5305\u76f4\u63a5\u89e3\u51b3\u4e86\u8fd9\u4e00\u9700\u6c42\uff0c\u7b80\u5316\u4e86\u5f00\u53d1\u8fc7\u7a0b\uff0c\u540c\u65f6\u4fdd\u6301\u4e86OpenAI\u7684LLMs\u7684\u5f3a\u5927\u529f\u80fd\u3002<\/p>\n

Hugging Face<\/strong>\u8ba9<\/strong>AI<\/strong>\u5de5\u5177\u89e6\u624b\u53ef\u53ca<\/strong><\/p>\n

Hugging Face\u7684openai-gradio\u5305\u4f7fAI\u5f00\u53d1\u53d8\u5f97\u50cf\u5199\u51e0\u884c\u4ee3\u7801\u4e00\u6837\u7b80\u5355\u3002\u5b83\u4e3a\u4f01\u4e1a\u5feb\u901f\u6784\u5efa\u548c\u90e8\u7f72AI\u9a71\u52a8\u7684\u7f51\u7edc\u5e94\u7528\u6253\u5f00\u4e86\u5927\u95e8\uff0c\u4e3a\u521d\u521b\u4f01\u4e1a\u548c\u5927\u578b\u4f01\u4e1a\u63d0\u4f9b\u4e86\u516c\u5e73\u7ade\u4e89\u7684\u673a\u4f1a\u3002<\/p>\n

\u8be5\u5de5\u5177\u51cf\u5c11\u4e86\u4ee5\u5f80\u5e94\u7528AI\u7684\u8bb8\u591a\u56f0\u96be\uff0c\u63d0\u4f9b\u4e86\u4e00\u79cd\u66f4\u5feb\u3001\u66f4\u5bb9\u6613\u7684\u65b9\u5f0f\u6765\u5229\u7528OpenAI\u7684\u8bed\u8a00\u6a21\u578b\u7684\u529b\u91cf\u3002<\/p>\n

\u968f\u7740\u66f4\u591a\u884c\u4e1a\u6d89\u8db3AI\uff0c\u5bf9\u53ef\u6269\u5c55\u3001\u7ecf\u6d4e\u9ad8\u6548\u5de5\u5177\u7684\u9700\u6c42\u6bd4\u4ee5\u5f80\u4efb\u4f55\u65f6\u5019\u90fd\u66f4\u4e3a\u8feb\u5207\u3002Hugging Face\u7684\u89e3\u51b3\u65b9\u6848\u8fce\u5408\u4e86\u8fd9\u4e00\u9700\u6c42\uff0c\u4f7f\u5f00\u53d1\u8005\u80fd\u591f\u5728\u5f88\u77ed\u7684\u65f6\u95f4\u5185\u5b9e\u73b0\u4ece\u539f\u578b\u5230\u751f\u4ea7\u7684\u8fc7\u7a0b\u3002<\/p>\n

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\u539f\u6587\u94fe\u63a5<\/a><\/p>\n

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\u7f16\u8f91\uff1a\u674e\u65ed\u5a9b<\/p>\n

\u5ba1\u6821\uff1a\u7ae0\u575a<\/p>\n

 <\/p>\n

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