{"id":6208,"date":"2024-12-19T09:13:34","date_gmt":"2024-12-19T01:13:34","guid":{"rendered":"https:\/\/www.xinyixx.com\/?p=6208"},"modified":"2024-12-19T09:13:34","modified_gmt":"2024-12-19T01:13:34","slug":"300","status":"publish","type":"post","link":"https:\/\/www.xinyixx.com\/index.php\/2024\/12\/19\/300\/","title":{"rendered":"\u51e0\u4e4e\u6700\u5168\u7684\u4e2d\u6587NLP\u8d44\u6e90\u5e93"},"content":{"rendered":"\n

\u5728\u5165\u95e8\u5230\u719f\u6089NLP\u7684\u8fc7\u7a0b\u4e2d\uff0c\u7528\u5230\u4e86\u5f88\u591agithub\u4e0a\u7684\u5305\uff0c\u9042\u6574\u7406\u4e86\u4e00\u4e0b\uff0c\u5206\u4eab\u5728\u8fd9\u91cc\u3002<\/p>\n\n\n\n

\u7c7bChatGPT\u7684\u6a21\u578b\u8bc4\u6d4b\u5bf9\u6bd4<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
ChatALL\uff1a\u53ef\u4ee5\u540c\u65f6\u4e0e\u591a\u4e2aAI\u804a\u5929\u673a\u5668\u4eba\uff08\u542b\u6e05\u534e\u3001\u8baf\u98de\u7684\u4ea7\u54c1\uff09<\/td>\u53ef\u4ee5\u540c\u65f6\u4e0e\u591a\u4e2aAI\u804a\u5929\u673a\u5668\u4eba\uff08\u5982ChatGPT\u3001Bing Chat\u3001Bard\u3001Alpaca\u3001Vincuna\u3001Claude\u3001ChatGLM\u3001MOSS\u3001iFlytek Spark\u3001ERNIE\u7b49\uff09\u8fdb\u884c\u5bf9\u8bdd\u7684\u5de5\u5177\u3002\u5b83\u53ef\u4ee5\u5e76\u884c\u53d1\u9001\u63d0\u793a\u7ed9\u4e0d\u540c\u7684AI\u673a\u5668\u4eba\uff0c\u5e2e\u52a9\u7528\u6237\u627e\u5230\u6700\u597d\u7684\u56de\u7b54<\/td>github-ChatALL<\/a><\/td><\/tr>
Chatbot Arena<\/td>\u5b9e\u9645\u573a\u666f\u7528Elo rating\u5bf9 LLM \u8fdb\u884c\u57fa\u51c6\u6d4b\u8bd5 – \u4ecb\u7ecd\u4e86 Chatbot Arena\uff0c\u4e00\u79cd\u9488\u5bf9\u5927\u578b\u8bed\u8a00\u6a21\u578b (LLM) \u7684\u57fa\u51c6\u5e73\u53f0\uff0c\u91c7\u7528\u533f\u540d\u3001\u968f\u673a\u7684\u65b9\u5f0f\u8fdb\u884c\u5bf9\u6297\u8bc4\u6d4b\uff0c\u8bc4\u6d4b\u65b9\u5f0f\u57fa\u4e8e\u56fd\u9645\u8c61\u68cb\u7b49\u7ade\u6280\u6e38\u620f\u4e2d\u5e7f\u6cdb\u4f7f\u7528\u7684 Elo rating system\u3002\u53d1\u5e03\u4e869\u4e2a\u6d41\u884c\u7684\u5f00\u6e90 LLM \u6a21\u578b\u7684 Elo rating \u5e76\u63a8\u51fa\u6392\u884c\u699c\u3002\u5e73\u53f0\u91c7\u7528 FastChat \u591a\u6a21\u578b\u670d\u52a1\u7cfb\u7edf\uff0c\u5728\u591a\u4e2a\u8bed\u8a00\u4e0b\u63d0\u4f9b\u4ea4\u4e92\u5f0f\u754c\u9762\uff0c\u6570\u636e\u6765\u6e90\u4e8e\u7528\u6237\u6295\u7968\u3002\u603b\u7ed3\u4e86 Chatbot Arena \u7684\u4f18\u70b9\u5e76\u8ba1\u5212\u63d0\u4f9b\u66f4\u597d\u7684\u91c7\u6837\u7b97\u6cd5\u3001\u6392\u540d\u548c\u670d\u52a1\u7cfb\u7edf<\/td>\u622a\u6b622023\u5e745\u67083\u65e5<\/a><\/td><\/tr>
\u7c7bChatGPT\u6a21\u578b\u8bc4\u6d4b\u603b\u7ed3<\/td>\u5927\u578b\u8bed\u8a00\u6a21\u578b(LLM)\u53d7\u5230\u5e7f\u6cdb\u5173\u6ce8\uff0c\u8fd9\u4e9b\u5f3a\u5927\u7684\u6a21\u578b\u80fd\u591f\u7406\u89e3\u590d\u6742\u7684\u4fe1\u606f\uff0c\u5e76\u5bf9\u5404\u79cd\u95ee\u9898\u63d0\u4f9b\u7c7b\u4eba\u7684\u56de\u5e94\u3002\u5176\u4e2dGPT-3\u548cGPT-4\u8868\u73b0\u6700\u597d\uff0cFlan-t5\u548cLit-LLaMA\u8868\u73b0\u4e5f\u4e0d\u9519\u3002\u4f46\u8981\u6ce8\u610f\uff0c\u6a21\u578b\u5546\u7528\u53ef\u80fd\u9700\u8981\u4ed8\u8d39\u548c\u6570\u636e\u5171\u4eab<\/td>blog<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLMs\uff09\u5927\u76d8\u70b9<\/td><\/td>blog<\/a><\/td><\/tr>
\u5927\u6a21\u578b\u8bc4\u6d4b\u65b9\u9762\u7684\u6700\u65b0\u7814\u7a76<\/td>\u957f\u6587\u672c\u5efa\u6a21\u4e00\u76f4\u662fChaGPT\u4ee4\u4eba\u60ca\u8273\u7684\u80fd\u529b\u4e4b\u4e00\uff0c\u6211\u4eec\u4ee5\u3010\u7bc7\u7ae0\u7ffb\u8bd1\u3011\u4e3a\u5b9e\u9a8c\u573a\u666f\uff0c\u5bf9\u5927\u6a21\u578b\u7684\u7bc7\u7ae0\u5efa\u6a21\u80fd\u529b\u8fdb\u884c\u5168\u9762\u3001\u7ec6\u7c92\u5ea6\u7684\u6d4b\u8bd5\u3002<\/td>paper<\/a><\/td><\/tr>
\u4e2d\u6587\u5927\u6a21\u578b\u8bc4\u6d4b\u5de5\u5177&\u6392\u884c\u699c<\/td>C-Eval\u662f\u4e00\u4e2a\u5168\u9762\u7684\u4e2d\u6587\u8bc4\u4f30\u5957\u4ef6\uff0c\u9002\u7528\u4e8e\u57fa\u7840\u6a21\u578b\u3002\u5b83\u5305\u542b13948\u4e2a\u591a\u9879\u9009\u62e9\u9898\uff0c\u6db5\u76d652\u4e2a\u4e0d\u540c\u7684\u5b66\u79d1\u548c\u56db\u4e2a\u96be\u5ea6\u7ea7\u522b\uff0c\u5177\u4f53\u5982\u4e0b\u6240\u793a\u3002\u8bf7\u8bbf\u95ee\u6211\u4eec\u7684\u7f51\u7ad9\u6216\u67e5\u9605\u6211\u4eec\u7684\u8bba\u6587\u83b7\u53d6\u66f4\u591a\u8be6\u7ec6\u4fe1\u606f\u3002<\/td>github<\/a>paper<\/a><\/td><\/tr>
OpenCompass \u5927\u6a21\u578b\u8bc4\u6d4b<\/td>OpenCompass \u4e0a\u6d77\u4eba\u5de5\u667a\u80fd\u5b9e\u9a8c\u5ba4\u5f00\u53d1\u7684\u4e00\u6b3e\u5f00\u6e90\u3001\u9ad8\u6548\u3001\u5168\u9762\u7684\u8bc4\u6d4b\u5927\u6a21\u578b\u4f53\u7cfb\u53ca\u5f00\u653e\u5e73\u53f0\uff0c\u63d0\u4f9b\u5b8c\u6574\u5f00\u6e90\u53ef\u590d\u73b0\u7684\u8bc4\u6d4b\u6846\u67b6\uff0c\u652f\u6301\u5927\u8bed\u8a00\u6a21\u578b\u3001\u591a\u6a21\u6001\u6a21\u578b\u5404\u7c7b\u6a21\u578b\u7684\u4e00\u7ad9\u5f0f\u8bc4\u6d4b\u3002\u5229\u7528\u5206\u5e03\u5f0f\u6280\u672f\uff0c\u5373\u4f7f\u9762\u5bf9\u5343\u4ebf\u53c2\u6570\u6a21\u578b\u4e5f\u80fd\u5728\u6570\u5c0f\u65f6\u5185\u5b8c\u6210\u8bc4\u6d4b\u3002\u57fa\u4e8e\u591a\u4e2a\u4e0d\u540c\u7ef4\u5ea6\u7684\u9ad8\u8ba4\u53ef\u5ea6\u6570\u636e\u96c6\u5f00\u653e\u591a\u6837\u5316\u7684\u8bc4\u6d4b\u65b9\u5f0f\uff0c\u5305\u62ec\u96f6\u6837\u672c\u8bc4\u6d4b\u3001\u5c0f\u6837\u672c\u8bc4\u6d4b\u548c\u601d\u7ef4\u94fe\u8bc4\u6d4b\uff0c\u5168\u65b9\u4f4d\u91cf\u5316\u6a21\u578b\u5404\u4e2a\u7ef4\u5ea6\u80fd\u529b\u3002<\/td>github<\/a> website<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7c7bChatGPT\u7684\u8d44\u6599<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Open LLMs\uff1a\u53ef\u4f9b\u5546\u4e1a\u4f7f\u7528\u7684\u5f00\u653e\u5927\u578b\u8bed\u8a00\u6a21\u578b(LLM)<\/td>A list of open LLMs available for commercial use<\/td>github<\/a><\/td><\/tr>
LLM Zoo: \u5927\u578b\u8bed\u8a00\u6a21\u578b\u7684\u6570\u636e\u3001\u6a21\u578b\u548c\u57fa\u51c6\u96c6\u5e02<\/td>LLM Zoo: democratizing ChatGPT – a project that provides data, models, and evaluation benchmark for large language models<\/td>github<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b(LLM)\u8d44\u6599\u5408\u96c6<\/td>\u76f8\u5173\u8bba\u6587\u5217\u8868\uff0c\u5305\u62ec\u6307\u5bfc\u3001\u63a8\u7406\u3001\u51b3\u7b56\u3001\u6301\u7eed\u6539\u8fdb\u548c\u81ea\u6211\u63d0\u5347\u7b49\u65b9\u9762\u7684\u7814\u7a76\u5de5\u4f5c<\/td>LLM\u8d44\u6599\u5408\u96c6<\/a><\/td><\/tr>
DecryptPrompt<\/td>\u603b\u7ed3Prompt&LLM\u8bba\u6587\uff0c\u5f00\u6e90\u6570\u636e&\u6a21\u578b\uff0cAIGC\u5e94\u7528<\/td>github<\/a><\/td><\/tr>
SmartGPT<\/td>\u65e8\u5728\u4e3a\u5927\u578b\u8bed\u8a00\u6a21\u578b(\u5c24\u5176\u662fGPT-3.5\u548cGPT-4)\u63d0\u4f9b\u5b8c\u6210\u590d\u6742\u4efb\u52a1\u7684\u80fd\u529b\uff0c\u901a\u8fc7\u5c06\u5b83\u4eec\u5206\u89e3\u6210\u66f4\u5c0f\u7684\u95ee\u9898\uff0c\u5e76\u4f7f\u7528\u4e92\u8054\u7f51\u548c\u5176\u4ed6\u5916\u90e8\u6765\u6e90\u6536\u96c6\u4fe1\u606f\u3002\u7279\u70b9\u5305\u62ec\u6a21\u5757\u5316\u8bbe\u8ba1\uff0c\u6613\u4e8e\u914d\u7f6e\uff0c\u4ee5\u53ca\u5bf9\u63d2\u4ef6\u7684\u9ad8\u5ea6\u652f\u6301\u3002SmartGPT\u7684\u8fd0\u4f5c\u57fa\u4e8e”Autos”\u7684\u6982\u5ff5\uff0c\u5305\u62ec”Runner”\u548c”Assistant”\u4e24\u79cd\u7c7b\u578b\uff0c\u90fd\u914d\u6709\u5904\u7406\u8ba1\u5212\u3001\u63a8\u7406\u548c\u4efb\u52a1\u6267\u884c\u7684LLM\u4ee3\u7406\u3002\u6b64\u5916\uff0cSmartGPT\u8fd8\u5177\u6709\u5185\u5b58\u7ba1\u7406\u7cfb\u7edf\uff0c\u4ee5\u53ca\u53ef\u4ee5\u5b9a\u4e49\u5404\u79cd\u547d\u4ee4\u7684\u63d2\u4ef6\u7cfb\u7edf<\/td>github-SmartGPT<\/a><\/td><\/tr>
OpenGPT<\/td>\u7528\u4e8e\u521b\u5efa\u57fa\u4e8e\u6307\u4ee4\u7684\u6570\u636e\u96c6\u5e76\u8bad\u7ec3\u5bf9\u8bdd\u9886\u57df\u4e13\u5bb6\u5927\u578b\u8bed\u8a00\u6a21\u578b(LLMs)\u7684\u6846\u67b6\u3002\u5df2\u7ecf\u6210\u529f\u5e94\u7528\u4e8e\u8bad\u7ec3\u5065\u5eb7\u62a4\u7406\u5bf9\u8bdd\u6a21\u578bNHS-LLM\uff0c\u5229\u7528\u6765\u81ea\u82f1\u56fd\u56fd\u5bb6\u536b\u751f\u670d\u52a1\u4f53\u7cfb(NHS)\u7f51\u7ad9\u7684\u6570\u636e\uff0c\u751f\u6210\u4e86\u5927\u91cf\u7684\u95ee\u7b54\u5bf9\u548c\u72ec\u7279\u5bf9\u8bdd<\/td>github-OpenGPT<\/a><\/td><\/tr>
PaLM 2\u6280\u672f\u62a5\u544a<\/td>Google\u6700\u65b0\u53d1\u5e03PaLM 2\uff0c\u4e00\u79cd\u65b0\u7684\u8bed\u8a00\u6a21\u578b\uff0c\u5177\u6709\u66f4\u597d\u7684\u591a\u8bed\u8a00\u548c\u63a8\u7406\u80fd\u529b\uff0c\u540c\u65f6\u6bd4\u5176\u524d\u8eabPaLM\u66f4\u8282\u7701\u8ba1\u7b97\u8d44\u6e90\u3002PaLM 2\u7efc\u5408\u4e86\u591a\u9879\u7814\u7a76\u8fdb\u5c55\uff0c\u5305\u62ec\u8ba1\u7b97\u6700\u4f18\u7684\u6a21\u578b\u548c\u6570\u636e\u89c4\u6a21\u3001\u66f4\u591a\u6837\u5316\u548c\u591a\u8bed\u8a00\u7684\u6570\u636e\u96c6\u3001\u4ee5\u53ca\u66f4\u6709\u6548\u7684\u6a21\u578b\u67b6\u6784\u548c\u76ee\u6807\u51fd\u6570\u3002PaLM 2\u5728\u591a\u79cd\u4efb\u52a1\u548c\u80fd\u529b\u4e0a\u8fbe\u5230\u4e86\u6700\u5148\u8fdb\u7684\u6027\u80fd\uff0c\u5305\u62ec\u8bed\u8a00\u6c34\u5e73\u8003\u8bd5\u3001\u5206\u7c7b\u548c\u95ee\u7b54\u3001\u63a8\u7406\u3001\u7f16\u7a0b\u3001\u7ffb\u8bd1\u548c\u81ea\u7136\u8bed\u8a00\u751f\u6210\u7b49\u3002PaLM 2\u8fd8\u5c55\u793a\u4e86\u5f3a\u5927\u7684\u591a\u8bed\u8a00\u80fd\u529b\uff0c\u80fd\u591f\u5904\u7406\u6570\u767e\u79cd\u8bed\u8a00\uff0c\u5e76\u5728\u4e0d\u540c\u8bed\u8a00\u4e4b\u95f4\u8fdb\u884c\u7ffb\u8bd1\u548c\u89e3\u91ca\u3002PaLM 2\u8fd8\u8003\u8651\u4e86\u8d1f\u8d23\u4efb\u7684\u4f7f\u7528\u95ee\u9898\uff0c\u5305\u62ec\u63a8\u7406\u65f6\u63a7\u5236\u6bd2\u6027\u3001\u51cf\u5c11\u8bb0\u5fc6\u5316\u3001\u8bc4\u4f30\u6f5c\u5728\u7684\u4f24\u5bb3\u548c\u504f\u89c1\u7b49<\/td>PaLM 2 Technical Report<\/a><\/td><\/tr>
DB-GPT<\/td>\u4e8evicuna-13b\u548cFastChat\u7684\u5f00\u6e90\u5b9e\u9a8c\u9879\u76ee\uff0c\u91c7\u7528\u4e86langchain\u548cllama-index\u6280\u672f\u8fdb\u884c\u4e0a\u4e0b\u6587\u5b66\u4e60\u548c\u95ee\u7b54\u3002\u9879\u76ee\u5b8c\u5168\u672c\u5730\u5316\u90e8\u7f72\uff0c\u4fdd\u8bc1\u6570\u636e\u7684\u9690\u79c1\u5b89\u5168\uff0c\u80fd\u76f4\u63a5\u8fde\u63a5\u5230\u79c1\u6709\u6570\u636e\u5e93\u5904\u7406\u79c1\u6709\u6570\u636e\u3002\u5176\u529f\u80fd\u5305\u62ecSQL\u751f\u6210\u3001SQL\u8bca\u65ad\u3001\u6570\u636e\u5e93\u77e5\u8bc6\u95ee\u7b54\u7b49<\/td>github-DB-GPT<\/a><\/td><\/tr>
Transformers\u76f8\u5173\u6587\u732e\u8d44\u6e90\u5927\u5217\u8868<\/td>\u5305\u542b\u4e86\u5404\u79cd\u5404\u6837\u7684Transformer\u6a21\u578b\uff0c\u4f8b\u5982BERT\u3001GPT\u3001Transformer-XL\u7b49\uff0c\u8fd9\u4e9b\u6a21\u578b\u5df2\u7ecf\u5728\u8bb8\u591a\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4efb\u52a1\u4e2d\u5f97\u5230\u4e86\u5e7f\u6cdb\u5e94\u7528\u3002\u6b64\u5916\uff0c\u8be5\u5217\u8868\u8fd8\u63d0\u4f9b\u4e86\u8fd9\u4e9b\u6a21\u578b\u7684\u76f8\u5173\u8bba\u6587\u548c\u4ee3\u7801\u94fe\u63a5\uff0c\u4e3a\u81ea\u7136\u8bed\u8a00\u5904\u7406\u9886\u57df\u7684\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u63d0\u4f9b\u4e86\u5f88\u597d\u7684\u53c2\u8003\u8d44\u6e90<\/td>github<\/a><\/td><\/tr>
GPT-4\u7ec8\u6781\u6307\u5357<\/td>\u4e00\u4efd\u5173\u4e8e\u5982\u4f55\u4f7f\u7528GPT3\u548cGPT4\u7684\u6307\u5357\uff0c\u5176\u4e2d\u5305\u62ec100\u591a\u4e2a\u8d44\u6e90\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5b66\u4e60\u5982\u4f55\u7528\u5b83\u6765\u63d0\u9ad8\u751f\u6d3b\u6548\u7387\u3002\u5305\u62ec\u5982\u4f55\u5b66\u4e60ChatGPT\u57fa\u7840\u77e5\u8bc6\u3001\u5982\u4f55\u5b66\u4e60ChatGPT\u9ad8\u7ea7\u77e5\u8bc6\u3001\u5982\u4f55\u5728\u8bed\u8a00\u5b66\u4e60\u4e2d\u4f7f\u7528GPT-3\u3001\u5982\u4f55\u5728\u6559\u5b66\u4e2d\u4f7f\u7528GPT-3\u3001\u5982\u4f55\u4f7f\u7528GPT-4\u7b49\uff0c\u8fd8\u63d0\u4f9b\u4e86\u5982\u4f55\u5347\u7ea7\u5230ChatGPT+\u8ba1\u5212\u4ee5\u4f7f\u7528GPT-4\u4ee5\u53ca\u5982\u4f55\u514d\u8d39\u4f7f\u7528GPT-4\u7684\u65b9\u6cd5\u7b49\u5185\u5bb9\u3002\u540c\u65f6\uff0c\u8fd8\u63d0\u4f9b\u4e86\u5982\u4f55\u5728\u4e1a\u52a1\u3001\u751f\u4ea7\u529b\u3001\u53d7\u76ca\u3001\u91d1\u94b1\u7b49\u65b9\u9762\u4f7f\u7528ChatGPT\u7684\u6307\u5357<\/td>link<\/a><\/td><\/tr>
\u57fa\u4e8eLoRA\u7684LLM\u53c2\u6570\u9ad8\u6548\u5fae\u8c03<\/td><\/td>link<\/a><\/td><\/tr>
\u590d\u6742\u63a8\u7406\uff1a\u5927\u8bed\u8a00\u6a21\u578b\u7684\u5317\u6781\u661f\u80fd\u529b<\/td>\u5728 GPT-4 \u53d1\u5e03\u535a\u5ba2\u4e2d\uff0c\u4f5c\u8005\u5199\u9053\uff1a\u201c\u5728\u4e00\u6b21\u968f\u610f\u7684\u8c08\u8bdd\u4e2d\uff0cGPT-3.5 \u548c GPT-4 \u4e4b\u95f4\u7684\u533a\u522b\u53ef\u80fd\u662f\u5fae\u5999\u7684\u3002\u5f53\u4efb\u52a1\u7684\u590d\u6742\u7a0b\u5ea6\u8fbe\u5230\u8db3\u591f\u7684\u9608\u503c\u65f6\uff0c\u5dee\u5f02\u5c31\u4f1a\u663e\u73b0\u51fa\u6765\u3002\u201d\u8fd9\u610f\u5473\u7740\u590d\u6742\u4efb\u52a1\u5f88\u53ef\u80fd\u662f\u5927\u578b\u548c\u5c0f\u578b\u8bed\u8a00\u6a21\u578b\u7684\u5173\u952e\u5dee\u5f02\u56e0\u7d20\u3002\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u5c06\u4ed4\u7ec6\u5206\u6790\u8ba8\u8bba\u5982\u4f55\u8ba9\u5927\u8bed\u8a00\u6a21\u578b\u62e5\u6709\u5f3a\u5927\u7684\u590d\u6742\u63a8\u7406\u80fd\u529b\u3002<\/td>blog<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b\u7684\u6d8c\u73b0\u80fd\u529b\u662f\u5426\u662f\u6d77\u5e02\u8703\u697c\uff1f<\/td>\u5927\u8bed\u8a00\u6a21\u578b\u7684\u6d8c\u73b0\u80fd\u529b\u4e00\u76f4\u662f\u88ab\u5927\u5bb6\u89c6\u4f5c\u5f88\u795e\u5947\u7684\u73b0\u8c61\uff0c\u4f3c\u4e4e\u662f\u4e00\u79cd\u5927\u529b\u51fa\u5947\u8ff9\uff0c\u4f46\u8fd9\u7bc7\u8bba\u6587\u8ba4\u4e3a\u8fd9\u53ef\u80fd\u53ea\u662f\u4e00\u79cd\u9519\u89c9\u3002<\/td>paper<\/a><\/td><\/tr>
\u5927\u8bed\u8a00\u6a21\u578b\u7684\u6982\u7387\u603b\u7ed3<\/td>\u975e\u5e38\u8be6\u5c3d\u7684LLM\u79d1\u5b66\u89e3\u91ca\u548c\u603b\u7ed3<\/td>paper<\/a><\/td><\/tr>
LLaMA \u6a21\u578b\u7b80\u53f2<\/td>LLaMA\u662fMeta\u53d1\u5e03\u7684\u8bed\u8a00\u6a21\u578b\uff0c\u91c7\u7528Transformer\u67b6\u6784\uff0c\u6709\u591a\u4e2a\u7248\u672c\uff0c\u6700\u5927\u4e3a65B\u53c2\u6570\u3002\u4e0eGPT\u7c7b\u4f3c\uff0c\u53ef\u7528\u4e8e\u8fdb\u4e00\u6b65\u5fae\u8c03\uff0c\u9002\u7528\u4e8e\u591a\u79cd\u4efb\u52a1\u3002\u4e0eGPT\u4e0d\u540c\u7684\u662f\uff0cLLaMA\u662f\u5f00\u6e90\u7684\uff0c\u53ef\u4ee5\u5728\u672c\u5730\u8fd0\u884c\u3002\u73b0\u6709\u7684LLaMA\u6a21\u578b\u5305\u62ec\uff1aAlpaca\u3001Vicuna\u3001Koala\u3001GPT4-x-Alpaca\u548cWizardLM\u3002\u6bcf\u4e2a\u6a21\u578b\u90fd\u6709\u4e0d\u540c\u7684\u8bad\u7ec3\u6570\u636e\u548c\u6027\u80fd\u8868\u73b0<\/td>blog<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b\u7684\u590d\u6742\u63a8\u7406<\/td>\u8ba8\u8bba\u4e86\u5982\u4f55\u8bad\u7ec3\u5177\u6709\u5f3a\u5927\u590d\u6742\u63a8\u7406\u80fd\u529b\u7684\u8bed\u8a00\u6a21\u578b\uff0c\u5e76\u63a2\u8ba8\u4e86\u5982\u4f55\u6709\u6548\u5730\u63d0\u793a\u6a21\u578b\u4ee5\u5145\u5206\u91ca\u653e\u5176\u6f5c\u529b\uff1b\u9488\u5bf9\u8bed\u8a00\u6a21\u578b\u548c\u7f16\u7a0b\u7684\u8bad\u7ec3\u76f8\u4f3c\u6027\uff0c\u63d0\u51fa\u4e86\u4e09\u9636\u6bb5\u7684\u8bad\u7ec3\uff1a\u6301\u7eed\u8bad\u7ec3\u3001\u76d1\u7763\u5fae\u8c03\u548c\u5f3a\u5316\u5b66\u4e60\uff1b\u4ecb\u7ecd\u4e86\u8bc4\u4f30\u5927\u578b\u8bed\u8a00\u6a21\u578b\u63a8\u7406\u80fd\u529b\u7684\u4e00\u5957\u4efb\u52a1\u96c6\u5408\uff1b\u8ba8\u8bba\u4e86\u5982\u4f55\u8fdb\u884c\u63d0\u793a\u5de5\u7a0b\uff0c\u901a\u8fc7\u63d0\u4f9b\u5404\u79cd\u5b66\u4e60\u673a\u4f1a\u4f7f\u6a21\u578b\u83b7\u5f97\u66f4\u597d\u7684\u5b66\u4e60\u6548\u679c\uff0c\u6700\u7ec8\u5b9e\u73b0\u667a\u80fd\u5316<\/td>link<\/a><\/td><\/tr>
\u5927\u8bed\u8a00\u6a21\u578b\u8fdb\u5316\u6811<\/td><\/td>paper<\/a><\/td><\/tr>
\u674e\u5b8f\u6bc5\uff1a\u7a77\u4eba\u5982\u4f55\u4f4e\u8d44\u6e90\u590d\u523b\u81ea\u5df1\u7684ChatGPT<\/td><\/td>blog<\/a><\/td><\/tr>
\u8bad\u7ec3ChatGPT\u7684\u5fc5\u5907\u8d44\u6e90\uff1a\u8bed\u6599\u3001\u6a21\u578b\u548c\u4ee3\u7801\u5e93\u5b8c\u5168\u6307\u5357<\/td><\/td>\u8d44\u6e90\u94fe\u63a5<\/a>\u8bba\u6587\u5730\u5740<\/a><\/td><\/tr>
GitHub\u5b9d\u85cf\u5e93\uff0c\u91cc\u9762\u6574\u7406\u4e86GPT\u76f8\u5173\u7684\u5404\u79cd\u5f00\u6e90\u9879\u76ee<\/td><\/td>github<\/a><\/td><\/tr>
ChatGPT\u4e2d\u6587\u6307\u5357<\/td><\/td>gitlab<\/a><\/td><\/tr>
\u63a2\u8ba8\u4e86ChatGPT\u5728\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u5e94\u7528\u3001\u4f18\u52bf\u3001\u9650\u5236\u4ee5\u53ca\u672a\u6765\u53d1\u5c55\u65b9\u5411<\/td>\u5f3a\u8c03\u4e86\u5728\u4f7f\u7528\u8be5\u6280\u672f\u65f6\u7684\u4f26\u7406\u9053\u5fb7\u8003\u91cf\u548c\u63d0\u793a\u5de5\u7a0b\u6280\u672f\u3002<\/td>paper<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b\u76f8\u5173\u6587\u732e\u8d44\u6e90\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u5927\u578b\u8bed\u8a00\u6a21\u578b\u6587\u732e\u7efc\u8ff0–\u4e2d\u6587\u7248<\/td><\/td>github<\/a><\/td><\/tr>
ChatGPT \u76f8\u5173\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
Pre-Training to Learn in Context<\/td><\/td>paper<\/a><\/td><\/tr>
Langchain\u67b6\u6784\u56fe<\/td><\/td>image<\/a><\/td><\/tr>
LLM\u5f00\u53d1\u4eba\u5458\u90fd\u5e94\u8be5\u77e5\u9053\u7684\u6570\u5b57<\/td><\/td>github<\/a><\/td><\/tr>
\u5927\u8bed\u8a00\u6a21\u578b\u5982\u4f55\u6784\u5efa\u5f3a\u5927\u7684\u590d\u6742\u63a8\u7406\u80fd\u529b<\/td><\/td>blog<\/a><\/td><\/tr>
LLMs\u4e5d\u5c42\u5996\u5854<\/td>\u5206\u4eab\u6253\u602a(ChatGLM\u3001Chinese-LLaMA-Alpaca\u3001MiniGPT-4\u3001FastChat\u3001LLaMA\u3001gpt4all\u7b49)\u5b9e\u6218\u4e0e\u7ecf\u9a8c<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7c7bChatGPT\u7684\u5f00\u6e90\u6846\u67b6<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
LLM-As-Chatbot<\/td>\u8fd9\u4e2a\u9879\u76ee\u628a\u5e02\u9762\u4e0a\u6709\u7684LLM\u5168\u90e8\u505a\u6210\u4e86Chatbot\uff0c\u76f4\u63a5\u53ef\u4ee5\u5728google colab\u8fd0\u884c\uff0c\u4e0d\u9700\u8981\u81ea\u5df1\u642d\u5efa\uff0c\u975e\u5e38\u9002\u7528\u4e8e\u60f3\u4f53\u9a8cLLM\u7684\u670b\u53cb\u4eec\u3002\u6211\u521a\u8bd5\u4e86\uff0c\u771f\u7684\u8d85\u7b80\u5355\u3002\u6709\u4e9bLLM\u9700\u8981\u7684\u663e\u5b58\u6bd4\u8f83\u591a\uff0c\u6240\u4ee5\u6700\u597d\u662f\u8981\u6709colab pro\u8ba2\u9605\u3002<\/td>github<\/a><\/td><\/tr>
OpenBuddy<\/td>\u4e00\u6b3e\u5f3a\u5927\u7684\u5f00\u6e90\u591a\u8bed\u8a00\u804a\u5929\u673a\u5668\u4eba\u6a21\u578b\uff0c\u76ee\u6807\u662f\u5168\u7403\u7528\u6237\uff0c\u91cd\u70b9\u662f\u5bf9\u8bddAI\u548c\u6d41\u7545\u7684\u591a\u8bed\u8a00\u652f\u6301\uff0c\u5305\u62ec\u82f1\u6587\u3001\u4e2d\u6587\u7b49\u591a\u79cd\u8bed\u8a00\u3002\u57fa\u4e8eFacebook\u7684LLAMA\u6a21\u578b\uff0c\u8fdb\u884c\u4e86\u5fae\u8c03\uff0c\u5305\u62ec\u6269\u5c55\u8bcd\u6c47\u8868\u3001\u589e\u52a0\u5e38\u7528\u5b57\u7b26\u548c\u589e\u5f3a\u7684token embeddings\u3002\u901a\u8fc7\u8fd9\u4e9b\u6539\u8fdb\u548c\u591a\u8f6e\u5bf9\u8bdd\u6570\u636e\u96c6\uff0cOpenBuddy\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5f3a\u5927\u7684\u6a21\u578b\uff0c\u80fd\u56de\u7b54\u95ee\u9898\u5e76\u5728\u5404\u79cd\u8bed\u8a00\u4e4b\u95f4\u8fdb\u884c\u7ffb\u8bd1\u4efb\u52a1\u3002OpenBuddy\u7684\u4f7f\u547d\u662f\u63d0\u4f9b\u4e00\u4e2a\u514d\u8d39\u3001\u5f00\u653e\u4e14\u53ef\u79bb\u7ebf\u4f7f\u7528\u7684AI\u6a21\u578b\uff0c\u8be5\u6a21\u578b\u53ef\u4ee5\u5728\u7528\u6237\u7684\u8bbe\u5907\u4e0a\u8fd0\u884c\uff0c\u65e0\u8bba\u4ed6\u4eec\u7684\u8bed\u8a00\u6216\u6587\u5316\u80cc\u666f\u5982\u4f55\u3002\u76ee\u524d\uff0cOpenBuddy-13B\u7684\u6f14\u793a\u7248\u672c\u53ef\u4ee5\u5728Discord\u670d\u52a1\u5668\u4e0a\u627e\u5230\u3002\u5176\u5173\u952e\u529f\u80fd\u5305\u62ec\u591a\u8bed\u8a00\u5bf9\u8bddAI(\u5305\u62ec\u4e2d\u6587\u3001\u82f1\u6587\u3001\u65e5\u6587\u3001\u97e9\u6587\u3001\u6cd5\u6587\u7b49)\u3001\u589e\u5f3a\u7684\u8bcd\u6c47\u8868\u548c\u5bf9\u5e38\u89c1CJK\u5b57\u7b26\u7684\u652f\u6301\uff0c\u4ee5\u53ca\u4e24\u79cd\u6a21\u578b\u7248\u672c\uff1a7B\u548c13B<\/td>github-OpenBuddy<\/a><\/td><\/tr>
Panda: \u6d77\u5916\u4e2d\u6587\u5f00\u6e90\u5927\u8bed\u8a00\u6a21\u578b<\/td>\u57fa\u4e8e Llama-7B, -13B, -33B, -65B \u8fdb\u884c\u4e2d\u6587\u9886\u57df\u4e0a\u7684\u6301\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u7528\u4e86\u63a5\u8fd115M\u6761\u6570\u636e\uff0c\u5e76\u9488\u5bf9\u63a8\u7406\u80fd\u529b\u5728\u4e2d\u6587benchmark\u4e0a\u8fdb\u884c\u4e86\u8bc4\u6d4b<\/td>github-PandaLM<\/a><\/td><\/tr>
Dromedary\uff1a\u4e00\u4e2a\u5f00\u6e90\u7684\u81ea\u5bf9\u9f50\u8bed\u8a00\u6a21\u578b\uff0c\u53ea\u9700\u5c11\u91cf\u4eba\u5de5\u76d1\u7763\u5373\u53ef\u8fdb\u884c\u8bad\u7ec3<\/td><\/td>github-Dromedary<\/a><\/td><\/tr>
LaMini-LM \u84b8\u998f\u7684\u5c0f\u578b\u3001\u9ad8\u6548\u7684\u8bed\u8a00\u6a21\u578b\u96c6\u5408<\/td>\u4ece ChatGPT \u84b8\u998f\u7684\u5c0f\u578b\u3001\u9ad8\u6548\u7684\u8bed\u8a00\u6a21\u578b\u96c6\u5408\uff0c\u57282.58 M \u6307\u4ee4\u5927\u89c4\u6a21\u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u8bad\u7ec3<\/td>github<\/a><\/td><\/tr>
LLaMA-Adapter V2<\/td>\u4e0a\u6d77\u4eba\u5de5\u667a\u80fd\u5b9e\u9a8c\u5ba4 LLaMA-Adapter V2\uff0c\u4ec5\u6ce8\u516514M\u53c2\u6570\uff0c1\u5c0f\u65f6\u65f6\u95f4\u5373\u53ef\u5b8c\u6210\u8bad\u7ec3\uff0c\u5bf9\u6bd4\u8f83\u679c\u786e\u5b9e\u5f88\u60ca\u8273\uff0c\u4e14\u5177\u6709\u591a\u6a21\u6001\u529f\u80fd\uff08\u5bf9\u56fe\u50cf\u8fdb\u884c\u89e3\u91ca\u548c\u95ee\u7b54\uff09<\/td>github<\/a><\/td><\/tr>
HuggingChat<\/td>Hugging Face \u63a8\u51fa\u7b2c\u4e00\u4e2a ChatGPT \u5f00\u6e90\u66ff\u4ee3\u54c1\uff1aHuggingChat\u3002\u57fa\u4e8e Open Assistant \u5927\u6a21\u578b\u642d\u5efa\uff0c\u652f\u6301\u4e2d\u6587\u5bf9\u8bdd\u4e0e\u7f16\u5199\u4ee3\u7801\uff0c\u4f46\u6682\u4e0d\u652f\u6301\u4e2d\u6587\u56de\u590d\u3002\u5e94\u7528\u5df2\u4e0a\u7ebf\uff0c\u65e0\u9700\u4ee3\u7406\uff0c\u6253\u5f00\u5373\u53ef\u8bbf\u95ee<\/td>link<\/a><\/td><\/tr>
Open-Chinese-LLaMA<\/td>\u57fa\u4e8e LLaMA-7B \u7ecf\u8fc7 \u4e2d\u6587\u6570\u636e\u96c6\u589e\u91cf\u9884\u8bad\u7ec3 \u4ea7\u751f\u7684 \u4e2d\u6587\u5927\u8bed\u8a00\u6a21\u578b\u57fa\u5ea7<\/td>github<\/a><\/td><\/tr>
OpenLLaMA<\/td>LLaMA\u6a21\u578b\u7684\u5f00\u6e90\u590d\u73b0\uff0c\u5728RedPajama\u6570\u636e\u96c6\u4e0a\u8bad\u7ec3\uff0c\u4f7f\u7528\u4e86\u4e0eLLaMA\u76f8\u540c\u7684\u9884\u5904\u7406\u6b65\u9aa4\u548c\u8d85\u53c2\u6570\uff0c\u6a21\u578b\u7ed3\u6784\uff0c\u4e0a\u4e0b\u6587\u957f\u5ea6\uff0c\u8bad\u7ec3\u6b65\u9aa4\uff0c\u5b66\u4e60\u7387\u8c03\u5ea6\u548c\u4f18\u5316\u5668\u3002OpenLLaMA\u7684PyTorch\u548cJax\u6743\u91cd\u53ef\u4ee5\u5728Huggingface Hub\u4e0a\u83b7\u5f97\u3002OpenLLaMA\u5728\u5404\u79cd\u4efb\u52a1\u4e2d\u5c55\u73b0\u51fa\u4e0eLLaMA\u548cGPT-J\u76f8\u4f3c\u7684\u8868\u73b0\uff0c\u90e8\u5206\u4efb\u52a1\u8868\u73b0\u4f18\u5f02<\/td>github<\/a><\/td><\/tr>
replit-code-v1-3b<\/td>BY-SA 4.0\u6388\u6743\u53d1\u5e03\uff0c\u8fd9\u610f\u5473\u7740\u5141\u8bb8\u5546\u4e1a\u4f7f\u7528<\/td>link<\/a><\/td><\/tr>
MOSS<\/td>MOSS\u662f\u4e00\u4e2a\u652f\u6301\u4e2d\u82f1\u53cc\u8bed\u548c\u591a\u79cd\u63d2\u4ef6\u7684\u5f00\u6e90\u5bf9\u8bdd\u8bed\u8a00\u6a21\u578b\uff0cmoss-moon\u7cfb\u5217\u6a21\u578b\u5177\u6709160\u4ebf\u53c2\u6570\uff0c\u5728FP16\u7cbe\u5ea6\u4e0b\u53ef\u5728\u5355\u5f20A100\/A800\u6216\u4e24\u5f203090\u663e\u5361\u8fd0\u884c\uff0c\u5728INT4\/8\u7cbe\u5ea6\u4e0b\u53ef\u5728\u5355\u5f203090\u663e\u5361\u8fd0\u884c\u3002MOSS\u57fa\u5ea7\u8bed\u8a00\u6a21\u578b\u5728\u7ea6\u4e03\u5343\u4ebf\u4e2d\u82f1\u6587\u4ee5\u53ca\u4ee3\u7801\u5355\u8bcd\u4e0a\u9884\u8bad\u7ec3\u5f97\u5230\uff0c\u540e\u7eed\u7ecf\u8fc7\u5bf9\u8bdd\u6307\u4ee4\u5fae\u8c03\u3001\u63d2\u4ef6\u589e\u5f3a\u5b66\u4e60\u548c\u4eba\u7c7b\u504f\u597d\u8bad\u7ec3\u5177\u5907\u591a\u8f6e\u5bf9\u8bdd\u80fd\u529b\u53ca\u4f7f\u7528\u591a\u79cd\u63d2\u4ef6\u7684\u80fd\u529b\u3002<\/td>github<\/a><\/td><\/tr>
RedPajama<\/td>1.2 \u4e07\u4ebftokens\u6570\u636e\u96c6<\/td>link<\/a><\/td><\/tr>
chinese_llama_alpaca_lora \u62bd\u53d6\u6846\u67b6<\/td><\/td>github<\/a><\/td><\/tr>
Scaling Transformer to 1M tokens and beyond with RMT<\/td>\u8be5\u8bba\u6587\u63d0\u51fa\u4e00\u79cd\u540d\u4e3a RMT \u7684\u65b0\u6280\u672f\uff0c\u6216\u8bb8\u53ef\u5c06 Transform \u7684 Token \u4e0a\u9650\u6269\u5c55\u81f3 100 \u4e07\uff0c\u751a\u81f3\u66f4\u591a\u3002<\/td>github<\/a><\/td><\/tr>
Open Assistant<\/td>\u5305\u542b\u5927\u91cfAI\u751f\u6210\u7684\u3001\u4eba\u5de5\u6807\u6ce8\u7684\u8bed\u6599\u5e93\u548c\u5305\u62ec\u57fa\u4e8eLLaMA\u548c\u57fa\u4e8ePythia\u7684\u591a\u79cd\u6a21\u578b\u53ef\u9009\u3002\u53d1\u5e03\u7684\u6570\u636e\u96c6\u5305\u62ec\u8d85\u8fc7161K\u8f83\u9ad8\u8d28\u91cf\u7684\uff0c\u591a\u8fbe35\u79cd\u8bed\u8a00\u7684\u4eba\u5de5\u52a9\u624b\u578b\u4ea4\u4e92\u5bf9\u8bdd\u8bed\u6599\u5e93<\/td>data<\/a> model<\/a><\/td><\/tr>
ChatGLM Efficient Tuning<\/td>\u57fa\u4e8e PEFT \u7684\u9ad8\u6548 ChatGLM \u5fae\u8c03<\/td>github<\/a><\/td><\/tr>
Dolly\u4ecb\u7ecd<\/td><\/td>news<\/a><\/td><\/tr>
Baize\uff1a\u4e00\u79cd\u5bf9\u81ea\u804a\u5929\u6570\u636e\u8fdb\u884c\u53c2\u6570\u9ad8\u6548\u8c03\u4f18\u7684\u5f00\u6e90\u804a\u5929\u6a21\u578b<\/td>Baize\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u804a\u5929\u6a21\u578b\uff0c\u53ef\u4ee5\u8fdb\u884c\u591a\u8f6e\u5bf9\u8bdd\u3002\u5b83\u662f\u901a\u8fc7\u4f7f\u7528ChatGPT\u81ea\u6211\u5bf9\u8bdd\u751f\u6210\u9ad8\u8d28\u91cf\u7684\u591a\u8f6e\u804a\u5929\u8bed\u6599\u5e93\uff0c\u5e76\u4f7f\u7528\u53c2\u6570\u9ad8\u6548\u8c03\u6574\u6765\u589e\u5f3aLLaMA\uff08\u4e00\u4e2a\u5f00\u6e90\u7684\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff09\u800c\u521b\u5efa\u7684\u3002Baize\u6a21\u578b\u5728\u5177\u6709\u6700\u5c0f\u6f5c\u5728\u98ce\u9669\u7684\u60c5\u51b5\u4e0b\u8868\u73b0\u51fa\u826f\u597d\u7684\u591a\u8f6e\u5bf9\u8bdd\u6027\u80fd\u3002\u5b83\u53ef\u4ee5\u5728\u5355\u4e2aGPU\u4e0a\u8fd0\u884c\uff0c\u4f7f\u66f4\u5e7f\u6cdb\u7684\u7814\u7a76\u4eba\u5458\u53ef\u4ee5\u4f7f\u7528\u5b83\u3002Baize\u6a21\u578b\u548c\u6570\u636e\u4ec5\u7528\u4e8e\u7814\u7a76\u76ee\u7684\u3002<\/td>\u8bba\u6587\u5730\u5740<\/a>\u6e90\u7801\u5730\u5740<\/a><\/td><\/tr>
GPTrillion–\u672a\u627e\u5230\u5f00\u6e90\u4ee3\u7801<\/td>\u5305\u542b1.5\u4e07\u4ebf\uff081.5T\uff09\u53c2\u6570\u7684\u5927\u6a21\u578bGPTrillion\u5f00\u6e90\u4e86\uff0c\u53f7\u79f0\u662f\u76ee\u524d\u4e16\u754c\u4e0a\u6700\u5927\u7684\u5f00\u6e90LLM<\/td>google_doc<\/a><\/td><\/tr>
Cerebras-GPT-13B(\u53ef\u5546\u7528)<\/td><\/td>hugging_face<\/a><\/td><\/tr>
Chinese-ChatLLaMA<\/td>\u4e2d\u6587ChatLLaMA\u5bf9\u8bdd\u6a21\u578b\uff1b\u9884\u8bad\u7ec3\/\u6307\u4ee4\u5fae\u8c03\u6570\u636e\u96c6\uff0c\u57fa\u4e8e TencentPretrain \u591a\u6a21\u6001\u9884\u8bad\u7ec3\u6846\u67b6\u6784\u5efa\uff0c\u652f\u6301\u7b80\u7e41\u4f53\u4e2d\u6587\u3001\u82f1\u6587\u3001\u65e5\u6587\u7b49\u591a\u8bed\u8a00<\/td>github<\/a><\/td><\/tr>
Lit-LLaMA<\/td>\u57fa\u4e8eApache 2.0\u8bb8\u53ef\u8bc1\u5b8c\u5168\u5f00\u6e90\u7684LLaMA\u72ec\u7acb\u5b9e\u73b0\uff0c\u5efa\u7acb\u5728nanoGPT\u4e4b\u4e0a\uff0c\u65e8\u5728\u89e3\u51b3\u539f\u59cbLLaMA\u4ee3\u7801\u91c7\u7528GPL\u8bb8\u53ef\u8bc1\u7684\u9650\u5236\uff0c\u4ee5\u5b9e\u73b0\u66f4\u5e7f\u6cdb\u7684\u5b66\u672f\u548c\u5546\u4e1a\u5e94\u7528<\/td>github<\/a><\/td><\/tr>
MosaicML<\/td>MPT-7B-StoryWriter\uff0c65K tokens\uff0c\u53ef\u4ee5\u628a\u300a\u4e86\u4e0d\u8d77\u7684\u76d6\u8328\u6bd4\u300b\u90fd\u4e00\u6b21\u6027\u6254\u8fdb\u53bb\u3002<\/td>huggingface<\/a><\/td><\/tr>
Langchain<\/td>\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLMs\uff09\u6b63\u5728\u6210\u4e3a\u4e00\u9879\u5177\u6709\u53d8\u9769\u6027\u7684\u6280\u672f\uff0c\u4f7f\u5f00\u53d1\u8005\u80fd\u591f\u6784\u5efa\u4ee5\u524d\u65e0\u6cd5\u5b9e\u73b0\u7684\u5e94\u7528\u7a0b\u5e8f\u3002\u7136\u800c\uff0c\u4ec5\u4ec5\u4f7f\u7528\u8fd9\u4e9b\u72ec\u7acb\u7684LLMs\u901a\u5e38\u4e0d\u8db3\u4ee5\u521b\u5efa\u4e00\u4e2a\u771f\u6b63\u5f3a\u5927\u7684\u5e94\u7528\u7a0b\u5e8f – \u771f\u6b63\u7684\u529b\u91cf\u6765\u81ea\u4e8e\u80fd\u591f\u5c06\u5b83\u4eec\u4e0e\u5176\u4ed6\u8ba1\u7b97\u6216\u77e5\u8bc6\u6765\u6e90\u76f8\u7ed3\u5408\u3002<\/td>github<\/a><\/td><\/tr>
Guidance<\/td>\u5f15\u5bfc\u80fd\u591f\u6bd4\u4f20\u7edf\u7684\u63d0\u793a\u6216\u94fe\u63a5\u66f4\u6709\u6548\u5730\u63a7\u5236\u73b0\u4ee3\u8bed\u8a00\u6a21\u578b\uff0c\u5e76\u4e14\u66f4\u9ad8\u6548\u3002\u5f15\u5bfc\u7a0b\u5e8f\u5141\u8bb8\u60a8\u5c06\u751f\u6210\u3001\u63d0\u793a\u548c\u903b\u8f91\u63a7\u5236\u4ea4\u9519\u5230\u5355\u4e00\u8fde\u7eed\u6d41\u4e2d\uff0c\u4e0e\u8bed\u8a00\u6a21\u578b\u5b9e\u9645\u5904\u7406\u6587\u672c\u7684\u65b9\u5f0f\u76f8\u5339\u914d\u3002\u50cf”Chain of Thought”\u53ca\u5176\u8bb8\u591a\u53d8\u4f53\uff08\u4f8b\u5982ART\u3001Auto-CoT\u7b49\uff09\u8fd9\u6837\u7684\u7b80\u5355\u8f93\u51fa\u7ed3\u6784\u5df2\u88ab\u8bc1\u660e\u80fd\u6539\u5584\u8bed\u8a00\u6a21\u578b\u7684\u6027\u80fd\u3002\u66f4\u5f3a\u5927\u7684\u8bed\u8a00\u6a21\u578b\uff08\u5982GPT-4\uff09\u7684\u51fa\u73b0\u4f7f\u5f97\u66f4\u4e30\u5bcc\u7684\u7ed3\u6784\u6210\u4e3a\u53ef\u80fd\uff0c\u800c\u5f15\u5bfc\u5219\u4f7f\u5f97\u6784\u5efa\u8fd9\u79cd\u7ed3\u6784\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\u548c\u7ecf\u6d4e\u3002<\/td>github<\/a><\/td><\/tr>
WizardLM<\/td>\u8d4b\u4e88\u5927\u578b\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u9075\u5faa\u590d\u6742\u6307\u4ee4\u7684\u80fd\u529b\uff0c\u4f7f\u7528\u5b8c\u6574\u8fdb\u5316\u6307\u4ee4\uff08\u7ea6300k\uff09\u8bad\u7ec3\u7684WizardLM-7B\u6a21\u578b<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

LLM\u7684\u8bad\u7ec3_\u63a8\u7406_\u4f4e\u8d44\u6e90_\u9ad8\u6548\u8bad\u7ec3<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
QLoRA–Guanaco<\/td>\u4e00\u79cd\u9ad8\u6548\u7684\u5fae\u8c03\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728\u5355\u4e2a48GB\u7684GPU\u4e0a\u5fae\u8c03\u4e00\u4e2a\u62e5\u670965B\u53c2\u6570\u7684\u6a21\u578b\uff0c\u540c\u65f6\u4fdd\u6301\u5b8c\u6574\u768416\u4f4d\u5fae\u8c03\u4efb\u52a1\u6027\u80fd\uff0c\u5e76\u901a\u8fc7QLoRA\u5c06\u68af\u5ea6\u53cd\u5411\u4f20\u64ad\u901a\u8fc7\u4e00\u4e2a\u51bb\u7ed3\u7684\u30014\u4f4d\u91cf\u5316\u7684\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u5230\u4f4e\u79e9\u9002\u914d\u5668\uff08LoRA\uff09<\/td>github<\/a><\/td><\/tr>
Chinese-Guanaco<\/td>\u4e00\u4e2a\u4e2d\u6587\u4f4e\u8d44\u6e90\u7684\u91cf\u5316\u8bad\u7ec3\/\u90e8\u7f72\u65b9\u6848<\/td>github<\/a><\/td><\/tr>
DeepSpeed Chat: \u4e00\u952e\u5f0fRLHF\u8bad\u7ec3<\/td><\/td>github<\/a><\/td><\/tr>
LLMTune: \u5728\u6d88\u8d39\u7ea7GPU\u4e0a\u5fae\u8c03\u5927\u578b65B+LLM<\/td>\u53ef\u4ee5\u5728\u666e\u901a\u6d88\u8d39\u7ea7GPU\u4e0a\u8fdb\u884c4\u4f4d\u5fae\u8c03\uff0c\u4f8b\u5982\u6700\u5927\u768465B LLAMA\u6a21\u578b\u3002LLMTune\u8fd8\u5b9e\u73b0\u4e86LoRA\u7b97\u6cd5\u548cGPTQ\u7b97\u6cd5\u6765\u538b\u7f29\u548c\u91cf\u5316LLM\uff0c\u5e76\u901a\u8fc7\u6570\u636e\u5e76\u884c\u5904\u7406\u5927\u578b\u6a21\u578b\u3002\u6b64\u5916\uff0cLLMTune\u63d0\u4f9b\u4e86\u547d\u4ee4\u884c\u754c\u9762\u548cPython\u5e93\u7684\u4f7f\u7528\u65b9\u5f0f<\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eChatGLM-6B+LoRA\u5728\u6307\u4ee4\u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u5fae\u8c03<\/td>\u57fa\u4e8edeepspeed\u652f\u6301\u591a\u5361\u5fae\u8c03\uff0c\u901f\u5ea6\u76f8\u6bd4\u5355\u5361\u63d0\u53478-9\u500d\u5177\u4f53\u8bbe\u7f6e\u53ef\u89c1 \u5fae\u8c033 \u57fa\u4e8eDeepSpeed\u8fdb\u884cLora\u5fae\u8c03<\/td>github<\/a><\/td><\/tr>
\u5fae\u8f6f\u53d1\u5e03RLHF\u8bad\u7ec3\u5de5\u5177DeepSpeed Chat<\/td><\/td>github<\/a><\/td><\/tr>
LlamaChat\uff1aMac\u4e0a\u57fa\u4e8eLLaMa\u7684\u804a\u5929\u673a\u5668\u4eba<\/td><\/td>github<\/a><\/td><\/tr>
ChatGPT\/GPT4\u5f00\u6e90\u201c\u5e73\u66ff\u201d\u4eec<\/td><\/td>github<\/a><\/td><\/tr>
\u8bad\u7ec3\u5927\u578b\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u5b9e\u7528\u5efa\u8bae\u548c\u6280\u5de7<\/td>\u5e2e\u52a9\u60a8\u8bad\u7ec3\u5927\u578b\u6a21\u578b\uff08>1B \u53c2\u6570\uff09\u3001\u907f\u514d\u4e0d\u7a33\u5b9a\u6027\u3001\u4fdd\u5b58\u5f00\u59cb\u5931\u8d25\u7684\u5b9e\u9a8c\u800c\u4e0d\u4ece 0 \u91cd\u65b0\u5f00\u59cb<\/td>link<\/a><\/td><\/tr>
Instruction Tuning with GPT-4<\/td><\/td>paper<\/a><\/td><\/tr>
xturing<\/td>\u4e00\u4e2aPython\u8f6f\u4ef6\u5305\uff0c\u7528\u4e8e\u9ad8\u6548\u3001\u5feb\u901f\u3001\u7b80\u5355\u5730\u5fae\u8c03LLM\u6a21\u578b\uff0c\u652f\u6301LLaMA\u3001GPT-J\u3001GPT-2\u7b49\u591a\u79cd\u6a21\u578b\uff0c\u53ef\u4f7f\u7528\u5355GPU\u548c\u591aGPU\u8bad\u7ec3\uff0c\u4f7f\u7528LoRA\u7b49\u9ad8\u6548\u5fae\u8c03\u6280\u672f\u53ef\u5c06\u786c\u4ef6\u6210\u672c\u964d\u4f4e\u9ad8\u8fbe90%\uff0c\u5e76\u5728\u77ed\u65f6\u95f4\u5185\u5b8c\u6210\u6a21\u578b\u8bad\u7ec3<\/td>github<\/a><\/td><\/tr>
GPT4All<\/td>\u4e00\u4e2a\u5141\u8bb8\u5728Macbook\u672c\u5730\u8fd0\u884cGPT\u7684\u5f00\u6e90\u9879\u76ee\u3002\u57fa\u4e8eLLaMa-7B\u5927\u8bed\u8a00\u6a21\u578b\u6253\u9020\uff0c\u5305\u62ec\u6570\u636e\u3001\u4ee3\u7801\u548cdemo\u90fd\u662f\u5f00\u6e90\u7684\uff0c\u5bf9\u8bdd\u98ce\u683c\u504f\u5411AI\u52a9\u7406<\/td>github<\/a><\/td><\/tr>
\u7528Alpaca-LoRA\u5fae\u8c03ChatGPT\u7c7b\u6a21\u578b<\/td><\/td>link<\/a><\/td><\/tr>
LMFlow<\/td>\u53ef\u6269\u5c55\u3001\u65b9\u4fbf\u6709\u6548\u7684\u5de5\u5177\u7bb1\uff0c\u7528\u4e8e\u5fae\u8c03\u5927\u578b\u673a\u5668\u5b66\u4e60\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
\u95fb\u8fbe\uff1a\u5927\u578b\u8bed\u8a00\u6a21\u578b\u8c03\u7528\u5e73\u53f0<\/td>\u76ee\u524d\u652f\u6301chatGLM-6B\u3001chatRWKV\u3001chatYuan\u548cchatGLM-6B\u6a21\u578b\u4e0b\u7684chatPDF\uff08\u81ea\u5efa\u77e5\u8bc6\u5e93\u67e5\u627e\uff09’<\/td>github<\/a><\/td><\/tr>
Micro Agent<\/td>\u5c0f\u578b\u81ea\u4e3b\u667a\u80fd\u4f53\u5f00\u6e90\u9879\u76ee\uff0c\u7531LLM(OpenAI GPT-4)\u63d0\u4f9b\u52a8\u529b\uff0c\u53ef\u4ee5\u4e3a\u4f60\u7f16\u5199\u8f6f\u4ef6\uff0c\u53ea\u9700\u8bbe\u7f6e\u4e00\u4e2a\u201c\u76ee\u7684\u201d\uff0c\u8ba9\u5b83\u81ea\u5df1\u5de5\u4f5c<\/td>github<\/a><\/td><\/tr>
Llama-X<\/td>\u5f00\u6e90\u7684\u5b66\u672f\u7814\u7a76\u9879\u76ee\uff0c\u901a\u8fc7\u793e\u533a\u5171\u540c\u52aa\u529b\uff0c\u9010\u6b65\u5c06LLaMA\u7684\u6027\u80fd\u63d0\u9ad8\u5230SOTA LLM\u6c34\u5e73\uff0c\u8282\u7701\u91cd\u590d\u5de5\u4f5c\uff0c\u5171\u540c\u521b\u9020\u66f4\u591a\u3001\u66f4\u5feb\u7684\u589e\u91cf<\/td>github<\/a><\/td><\/tr>
Chinese-LLaMA-Alpaca<\/td>\u4e2d\u6587LLaMA&Alpaca\u5927\u8bed\u8a00\u6a21\u578b+\u672c\u5730\u90e8\u7f72 (Chinese LLaMA & Alpaca LLMs) – \u5f00\u6e90\u4e86\u7ecf\u8fc7\u4e2d\u6587\u6587\u672c\u6570\u636e\u9884\u8bad\u7ec3\u7684\u4e2d\u6587LLaMA\u5927\u6a21\u578b\uff1b\u5f00\u6e90\u4e86\u8fdb\u4e00\u6b65\u7ecf\u8fc7\u6307\u4ee4\u7cbe\u8c03\u7684\u4e2d\u6587Alpaca\u5927\u6a21\u578b\uff1b\u5feb\u901f\u5730\u4f7f\u7528\u7b14\u8bb0\u672c\u7535\u8111\uff08\u4e2a\u4ebaPC\uff09\u672c\u5730\u90e8\u7f72\u548c\u4f53\u9a8c\u91cf\u5316\u7248\u5927\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
Efficient Alpaca<\/td>\u57fa\u4e8eLLaMA\u5b9e\u73b0\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u65e8\u5728\u901a\u8fc7\u5fae\u8c03 LLaMA-7B\u6a21\u578b\u5728\u8d44\u6e90\u6d88\u8017\u66f4\u5c11\u3001\u63a8\u7406\u901f\u5ea6\u66f4\u5feb\u3001\u66f4\u9002\u5408\u7814\u7a76\u8005\u4f7f\u7528\u65b9\u9762\u63d0\u9ad8Stanford Alpaca\u7684\u6027\u80fd<\/td>github<\/a><\/td><\/tr>
ChatGLM-6B-Slim<\/td>\u88c1\u51cf\u638920K\u56fe\u7247Token\u7684ChatGLM-6B\uff0c\u5b8c\u5168\u4e00\u6837\u7684\u6027\u80fd\uff0c\u5360\u7528\u66f4\u5c0f\u7684\u663e\u5b58<\/td>github<\/a><\/td><\/tr>
Chinese-Vicuna<\/td>\u4e00\u4e2a\u4e2d\u6587\u4f4e\u8d44\u6e90\u7684llama+lora\u65b9\u6848<\/td>github<\/a><\/td><\/tr>
Alpaca-LoRA<\/td>\u7528LoRA\u5728\u6d88\u8d39\u7ea7\u786c\u4ef6\u4e0a\u590d\u73b0\u65af\u5766\u798fAlpaca\u7684\u7ed3\u679c<\/td>github<\/a><\/td><\/tr>
LLM Accelerator<\/td>\u8ba9\u57fa\u7840\u5927\u6a21\u578b\u66f4\u806a\u660e\u7684LLM Accelerator\u6765\u4e86\uff01\u57fa\u7840\u5927\u6a21\u578b\u6b63\u5728\u8bf8\u591a\u5e94\u7528\u4e2d\u53d1\u6325\u7740\u65e5\u76ca\u91cd\u8981\u7684\u4f5c\u7528\u3002\u5927\u591a\u6570\u5927\u8bed\u8a00\u6a21\u578b\u7684\u8bad\u7ec3\u90fd\u662f\u91c7\u53d6\u81ea\u56de\u5f52\u7684\u65b9\u5f0f\u8fdb\u884c\u751f\u6210\uff0c\u867d\u7136\u81ea\u56de\u5f52\u6a21\u578b\u751f\u6210\u7684\u6587\u672c\u8d28\u91cf\u6709\u6240\u4fdd\u8bc1\uff0c\u4f46\u5374\u5bfc\u81f4\u4e86\u9ad8\u6602\u7684\u63a8\u7406\u6210\u672c\u548c\u957f\u65f6\u95f4\u7684\u5ef6\u8fdf\u3002\u7531\u4e8e\u5927\u6a21\u578b\u7684\u53c2\u6570\u91cf\u5de8\u5927\u3001\u63a8\u7406\u6210\u672c\u9ad8\uff0c\u56e0\u6b64\u5982\u4f55\u5728\u5927\u89c4\u6a21\u90e8\u7f72\u5927\u6a21\u578b\u7684\u8fc7\u7a0b\u4e2d\u964d\u4f4e\u6210\u672c\u3001\u51cf\u5c0f\u5ef6\u8fdf\u662f\u4e00\u4e2a\u5173\u952e\u8bfe\u9898\u3002\u9488\u5bf9\u6b64\u95ee\u9898\uff0c\u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\u7684\u7814\u7a76\u5458\u4eec\u63d0\u51fa\u4e86\u4e00\u79cd\u4f7f\u7528\u53c2\u8003\u6587\u672c\u65e0\u635f\u52a0\u901f\u5927\u8bed\u8a00\u6a21\u578b\u63a8\u7406\u7684\u65b9\u6cd5 LLM Accelerator\uff0c\u5728\u5927\u6a21\u578b\u5178\u578b\u7684\u5e94\u7528\u573a\u666f\u4e2d\u53ef\u4ee5\u53d6\u5f97\u4e24\u5230\u4e09\u500d\u7684\u52a0\u901f\u3002<\/td>blog<\/a><\/td><\/tr>
\u5927\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u5fae\u8c03\u6280\u672f\u7b14\u8bb0<\/td><\/td>github<\/a><\/td><\/tr>
PyLLMs<\/td>\u7b80\u6d01\u7684 Python \u5e93\uff0c\u7528\u4e8e\u8fde\u63a5\u5404\u79cd LLM(OpenAI\u3001Anthropic\u3001Google\u3001AI21\u3001Cohere\u3001Aleph Alpha\u3001HuggingfaceHub)\uff0c\u5185\u7f6e\u6a21\u578b\u6027\u80fd\u57fa\u51c6\u3002\u975e\u5e38\u9002\u5408\u5feb\u901f\u539f\u578b\u8bbe\u8ba1\u548c\u8bc4\u4f30\u4e0d\u540c\u6a21\u578b\uff0c\u5177\u6709\u4ee5\u4e0b\u7279\u70b9\uff1a\u901a\u8fc7\u5c11\u91cf\u4ee3\u7801\u8fde\u63a5\u9876\u7ea7 LLM\uff1b\u54cd\u5e94\u5143\u6570\u636e\u5305\u62ec\u5904\u7406\u7684Token\u3001\u6210\u672c\u548c\u5ef6\u8fdf\uff0c\u5bf9\u5404\u4e2a\u6a21\u578b\u8fdb\u884c\u6807\u51c6\u5316\uff1b\u652f\u6301\u591a\u6a21\u578b\uff1a\u540c\u65f6\u4ece\u4e0d\u540c\u6a21\u578b\u83b7\u53d6\u8865\u5168\uff1bLLM \u57fa\u51c6\uff1a\u8bc4\u4f30\u6a21\u578b\u7684\u8d28\u91cf\u3001\u901f\u5ea6\u548c\u6210\u672c<\/td>github<\/a><\/td><\/tr>
\u7528\u6df7\u5408\u7cbe\u5ea6\u52a0\u901f\u5927\u578b\u8bed\u8a00\u6a21\u578b<\/td>\u901a\u8fc7\u4f7f\u7528\u4f4e\u7cbe\u5ea6\u6d6e\u70b9\u6570\u8fd0\u7b97\uff0c\u53ef\u4ee5\u5c06\u8bad\u7ec3\u548c\u63a8\u65ad\u901f\u5ea6\u63d0\u5347\u591a\u8fbe3\u500d\uff0c\u540c\u65f6\u4e0d\u5f71\u54cd\u6a21\u578b\u51c6\u786e\u6027<\/td>blog<\/a><\/td><\/tr>
\u65b0\u7684LLM\u8bad\u7ec3\u65b9\u6cd5 Federate<\/td>\u675c\u514b\u5927\u5b66\u548c\u5fae\u8f6f\u4e00\u8d77\u53d1\u5e03\u4e86\u4e00\u4e2a\u65b0\u7684LLM\u8bad\u7ec3\u65b9\u6cd5 Federated GPT\uff0c\u8fd9\u4e2a\u8bad\u7ec3\u65b9\u6cd5\u662f\u5c06\u539f\u672c\u4e2d\u5fc3\u5316\u7684\u8bad\u7ec3\u65b9\u6cd5\u5206\u6563\u5230\u4e0d\u540c\u7684\u8fb9\u7f18\u8bbe\u5907\u91cc\u9762\uff08edge device\uff09\uff0c\u7136\u540e\u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u518d\u4e0a\u4f20\u5230\u4e2d\u5fc3\u53bb\u5c06\u5404\u5b50\u6a21\u578b\u5408\u5e76\u3002<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u63d0\u793a\u5de5\u7a0b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
OpenBuprompt-engineering-note<\/td>\u63d0\u793a\u5de5\u7a0b\u7b14\u8bb0(\u8bfe\u7a0b\u603b\u7ed3)\u300b\u4ecb\u7ecd\u4e86\u9762\u5411\u5f00\u53d1\u8005\u7684 ChatGPT Prompt Engineering Learning Notes \u8bfe\u7a0b\uff0c\u8be5\u8bfe\u7a0b\u63d0\u4f9b\u4e86\u8bed\u8a00\u6a21\u578b\u7684\u5de5\u4f5c\u539f\u7406\u548c\u63d0\u793a\u5de5\u7a0b\u5b9e\u8df5\uff0c\u5e76\u5c55\u793a\u4e86\u5982\u4f55\u5c06\u8bed\u8a00\u6a21\u578b API \u5e94\u7528\u4e8e\u5404\u79cd\u4efb\u52a1\u7684\u5e94\u7528\u7a0b\u5e8f\u4e2d\u3002\u8bfe\u7a0b\u5305\u62ec\u603b\u7ed3\u3001\u63a8\u65ad\u3001\u8f6c\u6362\u3001\u6269\u5c55\u548c\u6253\u9020\u804a\u5929\u673a\u5668\u4eba\u7b49\u65b9\u9762\u7684\u5185\u5bb9\uff0c\u5e76\u8bb2\u8ff0\u4e86\u5982\u4f55\u8bbe\u8ba1\u597d\u7684\u63d0\u793a\u548c\u6784\u5efa\u81ea\u5b9a\u4e49\u804a\u5929\u673a\u5668\u4eba\u3002<\/td>github-OpenBuprompt<\/a><\/td><\/tr>
\u63d0\u793a\u5de5\u7a0b\u6307\u5357<\/td><\/td>link<\/a><\/td><\/tr>
AIGC\u63d0\u793a\u5de5\u7a0b\u5b66\u4e60\u7ad9 Learn Prompt<\/td>ChatGPT\/Midjourney\/Runway<\/td>link<\/a><\/td><\/tr>
Prompts \u7cbe\u9009 – ChatGPT \u4f7f\u7528\u6307\u5357<\/td>ChatGPT \u4f7f\u7528\u6307\u5357\uff0c\u63d0\u5347 ChatGPT \u53ef\u73a9\u6027\u548c\u53ef\u7528\u6027<\/td>github<\/a><\/td><\/tr>
\u975e\u5b98\u65b9\u7684ChatGPT\u8d44\u6e90\u805a\u5408\u5217\u8868\uff0c\u65e8\u5728\u6c47\u603b\u4f7f\u7528ChatGPT<\/td>\u65e8\u5728\u6c47\u603b\u4f7f\u7528ChatGPT\u7684\u5e94\u7528\u3001Web\u5e94\u7528\u3001\u6d4f\u89c8\u5668\u6269\u5c55\u3001CLI\u5de5\u5177\u3001\u673a\u5668\u4eba\u3001\u96c6\u6210\u3001\u8f6f\u4ef6\u5305\u3001\u6587\u7ae0\u7b49\u8d44\u6e90<\/td>github<\/a><\/td><\/tr>
Snack Prompt\uff1aChatGPT Prompt\u63d0\u793a\u5206\u4eab\u793e\u533a<\/td><\/td>link<\/a><\/td><\/tr>
ChatGPT\u63d0\u95ee\u6280\u5de7<\/td>\u5982\u4f55\u5411 ChatGPT \u63d0\u95ee\u4ee5\u83b7\u5f97\u9ad8\u8d28\u91cf\u7b54\u6848\uff1a\u63d0\u793a\u6280\u5de7\u5de5\u7a0b\u5b8c\u5168\u6307\u5357<\/td>github<\/a><\/td><\/tr>
rompt-Engineering-Guide-Chinese – \u63d0\u793a\u5de5\u7a0b\u5e08\u6307\u5357<\/td>\u6e90\u81ea\u82f1\u6587\u7248\uff0c\u4f46\u589e\u52a0\u4e86AIGC\u7684prompt\u90e8\u5206<\/td>github<\/a><\/td><\/tr>
OpenPrompt<\/td>\u4e00\u4e2a\u5f00\u653e\u7684\u5171\u4eabPrompt\u793e\u533a\uff0c\u5927\u5bb6\u4e00\u8d77\u63a8\u8350\u597d\u7528\u7684prompt<\/td>github<\/a><\/td><\/tr>
GPT-Prompts<\/td>\u6559\u4f60\u5982\u4f55\u7528GPT\u751f\u6210Prompts<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7c7bChatGPT\u7684\u6587\u6863\u95ee\u7b54<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
privateGPT<\/td>\u57fa\u4e8eGPT4All-J\u7684\u79c1\u6709\u5316\u90e8\u7f72\u6587\u6863\u95ee\u7b54\u5e73\u53f0\uff0c\u65e0\u9700\u8054\u7f51\uff0c\u80fd100%\u4fdd\u8bc1\u7528\u6237\u7684\u9690\u79c1\u4e0d\u6cc4\u9732\u3002\u63d0\u4f9b\u4e86\u4e00\u4e2aAPI\uff0c\u7528\u6237\u53ef\u4ee5\u4f7f\u7528\u81ea\u5df1\u7684\u6587\u6863\u8fdb\u884c\u4ea4\u4e92\u5f0f\u95ee\u7b54\u548c\u751f\u6210\u6587\u672c\u3002\u6b64\u5916\uff0c\u5e73\u53f0\u652f\u6301\u81ea\u5b9a\u4e49\u8bad\u7ec3\u6570\u636e\u548c\u6a21\u578b\u53c2\u6570\uff0c\u4ee5\u6ee1\u8db3\u4e2a\u6027\u5316\u9700\u6c42<\/td>github-privateGPT<\/a><\/td><\/tr>
Auto-evaluator<\/td>\u6587\u6863\u95ee\u7b54\u7684\u81ea\u52a8\u8bc4\u4f30 \uff1b\u3001<\/td>github<\/a><\/td><\/tr>
PDF GP<\/td>\u4e00\u4e2a\u57fa\u4e8e GPT \u5b9e\u73b0\u7684\u5f00\u6e90 PDF \u6587\u6863\u804a\u5929\u65b9\u6848,\u4e3b\u8981\u5b9e\u73b0\u4ee5\u4e0b\u529f\u80fd\uff1a\u8ddf PDF \u6587\u6863\u8fdb\u884c\u4e00\u5bf9\u4e00\u5bf9\u8bdd\uff1b\u81ea\u52a8\u5207\u5272\u5185\u5bb9\uff0c\u5e76\u4f7f\u7528\u5f3a\u5927\u7684\u6df1\u5ea6\u5e73\u5747\u7f51\u7edc\u7f16\u7801\u5668\u6765\u751f\u6210\u5d4c\u5165\uff1b\u5bf9 PDF \u5185\u5bb9\u6267\u884c\u8bed\u4e49\u641c\u7d22\uff0c\u5e76\u5c06\u6700\u76f8\u5173\u7684\u5d4c\u5165\u4f20\u9012\u7ed9 Open AI\uff1b\u81ea\u5b9a\u4e49\u903b\u8f91\uff0c\u751f\u6210\u66f4\u7cbe\u786e\u7684\u54cd\u5e94\u4fe1\u606f\uff0c\u901f\u5ea6\u8981\u6bd4 OpenAI \u7684\u5feb\u3002<\/td>github<\/a><\/td><\/tr>
Redis-LLM-Document-Chat<\/td>\u7528LlamaIndex\u3001Redis\u548cOpenAI\u4e0ePDF\u6587\u6863\u8fdb\u884c\u4ea4\u4e92\uff0c\u5305\u542b\u4e00\u4e2aJupyter\u7b14\u8bb0\u672c\uff0c\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528Redis\u4f5c\u4e3a\u5411\u91cf\u6570\u636e\u5e93\u6765\u5b58\u50a8\u548c\u68c0\u7d22\u6587\u6863\u5411\u91cf\uff0c\u8fd8\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528LlamaIndex\u5728\u6587\u6863\u4e2d\u6267\u884c\u8bed\u4e49\u641c\u7d22\uff0c\u4ee5\u53ca\u5982\u4f55\u5229\u7528OpenAI\u63d0\u4f9b\u7c7b\u4f3c\u804a\u5929\u673a\u5668\u4eba\u7684\u4f53\u9a8c<\/td>github<\/a><\/td><\/tr>
doc-chatbot<\/td>GPT-4 + Pinecone + LangChain + MongoDB\u5b9e\u73b0\u7684\u6587\u6863\u804a\u5929\u673a\u5668\u4eba\uff0c\u53ef\u591a\u6587\u4ef6\u3001\u591a\u8bdd\u9898\u548c\u591a\u7a97\u53e3\u804a\u5929\uff0c\u804a\u5929\u5386\u53f2\u7531MongoDB\u4fdd\u5b58<\/td>github<\/a><\/td><\/tr>
document.ai<\/td>\u57fa\u4e8e\u5411\u91cf\u6570\u636e\u5e93\u4e0eGPT3.5\u7684\u901a\u7528\u672c\u5730\u77e5\u8bc6\u5e93\u65b9\u6848(A universal local knowledge base solution based on vector database and GPT3.5)<\/td>github<\/a><\/td><\/tr>
DocsGPT<\/td>DocsGPT\u662f\u4e00\u79cd\u5c16\u7aef\u7684\u5f00\u6e90\u89e3\u51b3\u65b9\u6848\uff0c\u53ef\u4ee5\u7b80\u5316\u5728\u9879\u76ee\u6587\u6863\u4e2d\u67e5\u627e\u4fe1\u606f\u7684\u8fc7\u7a0b\u3002\u901a\u8fc7\u96c6\u6210\u5f3a\u5927\u7684GPT\u6a21\u578b\uff0c\u5f00\u53d1\u4eba\u5458\u53ef\u4ee5\u8f7b\u677e\u5730\u63d0\u51fa\u5173\u4e8e\u9879\u76ee\u7684\u95ee\u9898\u5e76\u83b7\u5f97\u51c6\u786e\u7684\u7b54\u6848\u3002<\/td>github<\/a><\/td><\/tr>
ChatGPT Retrieval Plugin<\/td>ChatGPT\u68c0\u7d22\u63d2\u4ef6\u5b58\u50a8\u5e93\u63d0\u4f9b\u4e86\u4e00\u79cd\u7075\u6d3b\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u53ef\u4ee5\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u67e5\u8be2\u5bf9\u4e2a\u4eba\u6216\u7ec4\u7ec7\u6587\u6863\u8fdb\u884c\u8bed\u4e49\u641c\u7d22\u548c\u68c0\u7d22\u3002<\/td>github<\/a><\/td><\/tr>
LamaIndex<\/td>lamaIndex\uff08GPT\u7d22\u5f15\uff09\u662f\u60a8\u7684LLM\u5e94\u7528\u7a0b\u5e8f\u7684\u6570\u636e\u6846\u67b6\u3002<\/td>github<\/a><\/td><\/tr>
chatWeb<\/td>ChatWeb\u53ef\u4ee5\u722c\u53d6\u4efb\u610f\u7f51\u9875\u6216PDF\uff0cDOCX\uff0cTXT\u6587\u4ef6\u5e76\u63d0\u53d6\u6b63\u6587\uff0c\u53ef\u4ee5\u751f\u6210\u5d4c\u5165\u5f0f\u6982\u8981\uff0c\u53ef\u4ee5\u6839\u636e\u6b63\u6587\u5185\u5bb9\u56de\u7b54\u4f60\u7684\u95ee\u9898\u3002 \u57fa\u4e8egpt3.5\u7684chatAPI\u548cembeddingAPI\uff0c\u4ee5\u53ca\u5411\u91cf\u6570\u636e\u5e93\u5b9e\u73b0\u3002<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7c7bChatGPT\u7684\u884c\u4e1a\u5e94\u7528<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u65b0\u95fb\u62a5\u9053\u8fdb\u884c\u60c5\u611f\u5206\u6790<\/td>\u7528ChatGPT\u901a\u8fc7\u5bf9\u4e0a\u5e02\u516c\u53f8\u7684\u65b0\u95fb\u62a5\u9053\u8fdb\u884c\u60c5\u611f\u5206\u6790\uff0c\u572815\u4e2a\u6708\u65f6\u95f4\u5185\u5728\u80a1\u7968\u5e02\u573a(\u4ea4\u6613\u671f\u6743)\u4ea7\u751f\u4e86500%\u7684\u56de\u62a5\uff08\u5728\u5386\u53f2\u6570\u636e\u4e2d\u6d4b\u8bd5\u5f97\u51fa\u7684\u7ed3\u679c\uff09\u2014\u2014\u63a2\u8ba8\u4e86ChatGPT\u5728\u5229\u7528\u65b0\u95fb\u6807\u9898\u7684\u60c5\u611f\u5206\u6790\u6765\u9884\u6d4b\u80a1\u5e02\u56de\u62a5\u65b9\u9762\u7684\u6f5c\u529b\u3002\u53d1\u73b0ChatGPT\u7684\u60c5\u611f\u5206\u6790\u80fd\u529b\u8d85\u8fc7\u4e86\u4f20\u7edf\u7684\u65b9\u6cd5\uff0c\u5e76\u4e14\u4e0e\u80a1\u5e02\u56de\u62a5\u5448\u6b63\u76f8\u5173\u3002\u63d0\u51faChatGPT\u5728\u91d1\u878d\u7ecf\u6d4e\u9886\u57df\u6709\u5f88\u5927\u7684\u4ef7\u503c\uff0c\u5e76\u5bf9\u672a\u6765\u7684\u7814\u7a76\u548c\u5e94\u7528\u63d0\u51fa\u4e86\u4e00\u4e9b\u542f\u793a\u548c\u5efa\u8bae<\/td>paper<\/a><\/td><\/tr>
\u7f16\u7a0b\u8bed\u8a00\u751f\u6210\u6a21\u578b StarCoder<\/td>BigCode\u662f ServiceNow Inc. \u548c Hugging Face Inc. \u5408\u4f5c\u6210\u7acb\u7684\u3002StarCoder \u6709\u591a\u4e2a\u7248\u672c\u3002\u6838\u5fc3\u7248\u672c StarCoderBase \u5177\u6709 155 \u4ebf\u4e2a\u53c2\u6570\uff0c\u652f\u630180\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c8192\u4e2atoken\u7684\u4e0a\u4e0b\u6587\u3002\u89c6\u9891\u4e3a\u5176vscode\u63d2\u4ef6\u6548\u679c<\/td>github<\/a><\/td><\/tr>
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages<\/td>code generation<\/td>paper<\/a><\/td><\/tr>
MedicalGPT-zh\uff1a\u4e2d\u6587\u533b\u7597\u901a\u7528\u8bed\u8a00\u6a21\u578b<\/td>\u4e2d\u6587\u533b\u7597\u901a\u7528\u8bed\u8a00\u6a21\u578b\uff0c\u57fa\u4e8e28\u4e2a\u79d1\u5ba4\u7684\u533b\u7597\u5171\u8bc6\u4e0e\u4e34\u5e8a\u6307\u5357\u6587\u672c\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u533b\u7597\u9886\u57df\u77e5\u8bc6\u4e0e\u5bf9\u8bdd\u80fd\u529b<\/td>github<\/a><\/td><\/tr>
MagicSlides<\/td>\u4e0d\u5c11\u4eba\u68a6\u5bd0\u4ee5\u6c42\u7684AI\u81ea\u4f5cPPT\uff0c\u514d\u8d39\u7248\u6bcf\u6708\u80fd\u505a3\u4e2aPPT\uff0c\u652f\u63012500\u5b57\u8f93\u5165<\/td>link<\/a><\/td><\/tr>
SalesGPT<\/td>\u4f7f\u7528LLM\u5b9e\u73b0\u4e0a\u4e0b\u6587\u611f\u77e5\u7684\u9500\u552e\u52a9\u624b\uff0c\u53ef\u81ea\u52a8\u5316\u9500\u552e\u62d3\u5c55\u4ee3\u8868\u7684\u6d3b\u52a8\uff0c\u5982\u5916\u547c\u9500\u552e\u7535\u8bdd<\/td>github<\/a><\/td><\/tr>
\u534e\u9a7c(HuaTuo): \u57fa\u4e8e\u4e2d\u6587\u533b\u5b66\u77e5\u8bc6\u7684LLaMA\u5fae\u8c03\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
ai-code-translator<\/td>\u5e2e\u52a9\u4f60\u628a\u4ee3\u7801\u4ece\u4e00\u79cd\u8bed\u8a00\u7ffb\u8bd1\u6210\u53e6\u4e00\u79cd\u8bed\u8a00\uff0c\u8fd9\u4e8b\u5bf9ChatGPT\u6765\u8bf4\u7b80\u76f4\u592a\u64c5\u957f\u4e86\uff0c\u5c24\u5176\u662fGPT-4\uff0c\u7ffb\u8bd1\u8d28\u91cf\u76f8\u5f53\u9ad8\uff0c\u800c\u4e14tokens\u957f\u5ea6\u4e5f\u53ef\u4ee5\u66f4\u957f\u3002<\/td>github<\/a><\/td><\/tr>
ChatGenTitle<\/td>\u4f7f\u7528\u767e\u4e07arXiv\u8bba\u6587\u4fe1\u606f\u5728LLaMA\u6a21\u578b\u4e0a\u8fdb\u884c\u5fae\u8c03\u7684\u8bba\u6587\u9898\u76ee\u751f\u6210\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
Regex.ai<\/td>\u4e00\u6b3e\u6240\u89c1\u5373\u6240\u5f97\u7684\uff0c\u57fa\u4e8e AI \u7684\u6b63\u5219\u8868\u8fbe\u5f0f\u81ea\u52a8\u751f\u6210\u5de5\u5177\uff0c\u53ea\u9700\u8981\u9009\u62e9\u51fa\u6570\u636e\uff0c\u5b83\u5c31\u80fd\u5e2e\u4f60\u5199\u6b63\u5219\u8868\u8fbe\u5f0f\uff0c\u5e76\u63d0\u4f9b\u591a\u79cd\u63d0\u53d6\u6570\u636e\u7684\u65b9\u5f0f<\/td>video<\/a><\/td><\/tr>
ChatDoctor<\/td>\u4e00\u4e2a\u57fa\u4e8e\u533b\u5b66\u9886\u57df\u77e5\u8bc6\u5fae\u8c03LLaMA\u7684\u533b\u5b66\u804a\u5929\u6a21\u578b\uff0c\u5176\u4e2d\u533b\u5b66\u6570\u636e\u5305\u542b\u5927\u7ea6700\u79cd\u75be\u75c5\u7684\u6570\u636e\u3001\u4ee5\u53ca\u5927\u7ea65000\u6bb5\u533b\u751f\u548c\u75c5\u4eba\u7684\u5bf9\u8bdd\u8bb0\u5f55<\/td>paper<\/a><\/td><\/tr>
CodeGPT<\/td>\u63d0\u9ad8\u7f16\u7a0b\u80fd\u529b\u7684\u5173\u952e\u5728\u4e8e\u6570\u636e\u3002CodeGPT\u662f\u901a\u8fc7GPT\u751f\u6210\u7684\u7528\u4e8eGPT\u7684\u4ee3\u7801\u5bf9\u8bdd\u6570\u636e\u96c6\u3002\u73b0\u5728\u516c\u5f00\u4e8632K\u6761\u4e2d\u6587\u6570\u636e\uff0c\u8ba9\u6a21\u578b\u66f4\u64c5\u957f\u7f16\u7a0b<\/td>github<\/a><\/td><\/tr>
LaWGPT<\/td>\u4e00\u7cfb\u5217\u57fa\u4e8e\u4e2d\u6587\u6cd5\u5f8b\u77e5\u8bc6\u7684\u5f00\u6e90\u5927\u8bed\u8a00\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
LangChain-ChatGLM-Webui<\/td>\u53d7langchain-ChatGLM\u542f\u53d1, \u5229\u7528LangChain\u548cChatGLM-6B\u7cfb\u5217\u6a21\u578b\u5236\u4f5c\u7684Webui, \u63d0\u4f9b\u57fa\u4e8e\u672c\u5730\u77e5\u8bc6\u7684\u5927\u6a21\u578b\u5e94\u7528.\u76ee\u524d\u652f\u6301\u4e0a\u4f20 txt\u3001docx\u3001md\u3001pdf\u7b49\u6587\u672c\u683c\u5f0f\u6587\u4ef6, \u63d0\u4f9b\u5305\u62ecChatGLM-6B\u7cfb\u5217\u3001Belle\u7cfb\u5217\u7b49\u6a21\u578b\u6587\u4ef6\u4ee5\u53caGanymedeNil\/text2vec-large-chinese\u3001nghuyong\/ernie-3.0-base-zh\u3001nghuyong\/ernie-3.0-nano-zh\u7b49Embedding\u6a21\u578b.<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7c7bChatGPT\u7684\u8bfe\u7a0b\u8d44\u6599<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Databricks<\/td>\uff08Dolly\u6a21\u578b\u7684\u4f5c\u8005\uff09\u5728edX\u53d1\u5e03\u4e86\u4e24\u4e2a\u514d\u8d39\u8bfe\u7a0b\u7a0b\uff0c\u5176\u4e2d\u7b2c\u4e8c\u4e2a\u662f\u5173\u4e8eLLM\u662f\u5982\u4f55\u6784\u5efa\u7684\u3002<\/td>link<\/a><\/td><\/tr>
\u5927\u8bed\u8a00\u6a21\u578b\u6280\u672f\u5206\u4eab\u7cfb\u5217<\/td>\u4e1c\u5317\u5927\u5b66\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5b9e\u9a8c\u5ba4<\/td>video<\/a><\/td><\/tr>
GPT-4\u662f\u5982\u4f55\u5de5\u4f5c\u7684\uff1f\u5982\u4f55\u5229\u7528GPT-4\u6253\u9020\u667a\u80fd\u7a0b\u5e8f\uff1f<\/td>\u54c8\u4f5b\u5927\u5b66CS50\u516c\u5f00\u8bfe<\/td>video<\/a><\/td><\/tr>
\u63d0\u793a\u5de5\u7a0b\u6700\u4f73\u5b9e\u8df5\uff1aAndrew Ng \u63d0\u793a\u5de5\u7a0b\u65b0\u8bfe\u6458\u8981+LangChain\u7ecf\u9a8c\u603b\u7ed3<\/td><\/td>medium_blog<\/a><\/td><\/tr>
\u5fae\u8c03LLM\u6a21\u578b<\/td>\u5982\u679c\u4f60\u5bf9\u5fae\u8c03LLM\u6a21\u578b\u611f\u5174\u8da3\uff0c\u4e00\u5b9a\u8981\u5173\u6ce8\u8fd9\u4e2a\u6cb9\u7ba1\u535a\u4e3b\uff0c\u4ed6\u628a\u51e0\u4e4e\u4e16\u9762\u4e0a\u6240\u6709\u7684LLM\u6a21\u578b\u90fd\u516c\u5f00\u4e86\u5fae\u8c03\u7684\u65b9\u6cd5\u3002<\/td>\u6cb9\u7ba1\u535a\u4e3b Sam Witteveen<\/td><\/tr>
Transformer\u7684\u67b6\u6784\u89e3\u8bfb<\/td>\u901a\u4fd7\u6613\u61c2\u7684\u4ecb\u7ecd<\/td>youtube1<\/a>youtube2<\/a> youtube3<\/a><\/td><\/tr>
Transformer multi head\u673a\u5236\u7684\u89c6\u9891<\/td>\u5982\u679c\u60f3\u8981\u771f\u6b63\u7406\u89e3\u6574\u4e2aTransform\u7684\u6bcf\u4e00\u4e2a\u7ec6\u8282\uff0c\u5305\u62ec\u91cc\u9762\u7684\u6570\u5b66\u539f\u7406\uff0c\u53ef\u4ee5\u770b\u4e00\u4e0b\u8fd9\u4e2a\u89c6\u9891\uff0c\u771f\u7684\u662f\u5256\u6790\u5730\u975e\u5e38\u8be6\u7ec6<\/td>youtube<\/a><\/td><\/tr>
Introduction to Large Language Models<\/td>\u5927\u8bed\u8a00\u6a21\u578b\u4ecb\u7ecd<\/td>\u4ecb\u7ecd\u4e86\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08Large Language Models\uff0cLLMs\uff09\u7684\u6982\u5ff5\u3001\u4f7f\u7528\u573a\u666f\u3001\u63d0\u793a\u8c03\u6574\u4ee5\u53caGoogle\u7684Gen AI\u5f00\u53d1\u5de5\u5177\u3002<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

LLM\u7684\u5b89\u5168\u95ee\u9898<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
LLM\u6a21\u578b\u5b89\u5168\u7814\u7a76<\/td><\/td>link<\/a><\/td><\/tr>
Chatbot Injections & Exploit<\/td>\u6536\u96c6\u4e86\u4e00\u4e9bChatbot\u6ce8\u5165\u548c\u6f0f\u6d1e\u7684\u4f8b\u5b50\uff0c\u4ee5\u5e2e\u52a9\u4eba\u4eec\u4e86\u89e3Chatbot\u7684\u6f5c\u5728\u6f0f\u6d1e\u548c\u8106\u5f31\u6027\u3002\u6ce8\u5165\u548c\u653b\u51fb\u7684\u65b9\u5f0f\u5305\u62ec\u547d\u4ee4\u6ce8\u5165\u3001\u5b57\u7b26\u7f16\u7801\u3001\u793e\u4ea4\u5de5\u7a0b\u3001\u8868\u60c5\u7b26\u53f7\u3001Unicode\u7b49\u3002\u4ed3\u5e93\u63d0\u4f9b\u4e86\u4e00\u4e9b\u793a\u4f8b\uff0c\u5176\u4e2d\u4e00\u4e9b\u5305\u62ec\u53ef\u7528\u4e8e\u653b\u51fbChatbot\u7684\u8868\u60c5\u7b26\u53f7\u5217\u8868<\/td>github<\/a><\/td><\/tr>
GPTSecurity<\/td>\u4e00\u4e2a\u6db5\u76d6\u4e86\u524d\u6cbf\u5b66\u672f\u7814\u7a76\u548c\u5b9e\u8df5\u7ecf\u9a8c\u5206\u4eab\u7684\u793e\u533a\uff0c\u96c6\u6210\u4e86\u751f\u6210\u9884\u8bad\u7ec3 Transformer\uff08GPT\uff09\u3001\u4eba\u5de5\u667a\u80fd\u751f\u6210\u5185\u5bb9\uff08AIGC\uff09\u4ee5\u53ca\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u7b49\u5b89\u5168\u9886\u57df\u5e94\u7528\u7684\u77e5\u8bc6\u3002\u5728\u8fd9\u91cc\uff0c\u60a8\u53ef\u4ee5\u627e\u5230\u5173\u4e8eGPT\/AIGC\/LLM\u6700\u65b0\u7684\u7814\u7a76\u8bba\u6587\u3001\u535a\u5ba2\u6587\u7ae0\u3001\u5b9e\u7528\u7684\u5de5\u5177\u548c\u9884\u8bbe\u6307\u4ee4\uff08Prompts\uff09\u3002<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u591a\u6a21\u6001LLM<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
DeepFloyd IF<\/td>\u9ad8\u5ea6\u903c\u771f\u4e14\u5177\u6709\u8bed\u8a00\u7406\u89e3\u80fd\u529b\u7684\u6700\u65b0\u5f00\u6e90\u6587\u672c\u5230\u56fe\u50cf\u6a21\u578b\uff0c\u7531\u4e00\u4e2a\u51bb\u7ed3\u6587\u672c\u7f16\u7801\u5668\u548c\u4e09\u4e2a\u8fde\u7eed\u7684\u50cf\u7d20\u6269\u6563\u6a21\u5757\u7ec4\u6210\uff0c\u662f\u4e00\u4e2a\u9ad8\u6548\u7684\u6a21\u578b\uff0c\u6027\u8d85\u8d8a\u4e86\u5f53\u524d\u6700\u5148\u8fdb\u7684\u6a21\u578b\uff0c\u5728COCO\u6570\u636e\u96c6\u4e0a\u5b9e\u73b0\u4e86\u96f6\u6837\u672c\u7684FID\u5f97\u5206\u4e3a6.66<\/td>github<\/a><\/td><\/tr>
Multi-modal GPT<\/td>\u7528\u591a\u6a21\u6001GPT\u8bad\u7ec3\u4e00\u4e2a\u80fd\u540c\u65f6\u63a5\u6536\u89c6\u89c9\u548c\u8bed\u8a00\u6307\u4ee4\u7684\u804a\u5929\u673a\u5668\u4eba\u3002\u57fa\u4e8eOpenFlamingo\u591a\u6a21\u6001\u6a21\u578b\uff0c\u4f7f\u7528\u5404\u79cd\u5f00\u653e\u6570\u636e\u96c6\u521b\u5efa\u5404\u79cd\u89c6\u89c9\u6307\u5bfc\u6570\u636e\uff0c\u8054\u5408\u8bad\u7ec3\u89c6\u89c9\u548c\u8bed\u8a00\u6307\u5bfc\uff0c\u6709\u6548\u63d0\u9ad8\u6a21\u578b\u6027\u80fd<\/td>github<\/a><\/td><\/tr>
AudioGPT<\/td>Understanding and Generating Speech, Music, Sound, and Talking Head’ by AIGC-Audio<\/td>github<\/a><\/td><\/tr>
text2image-prompt-generator<\/td>\u57fa\u4e8eGPT-2\u752825\u4e07\u6761Midjourney\u7684promps\u8bad\u7ec3\u51fa\u6765\u7684\u5c0f\u6a21\u578b\uff0c\u53ef\u4ee5\u751f\u6210\u9ad8\u8d28\u91cf\u7684Midjourney prompt<\/td>link<\/a> data<\/a><\/td><\/tr>
\u6c47\u603b6\u4e2aMidjourney\u4ee5\u5916\u7684\u514d\u8d39\u4ee5\u6587\u751f\u56fe\u670d\u52a1\uff1a<\/td><\/td>Bing Image Creator<\/a> Playground AI<\/a> DreamStudio<\/a> Pixlr<\/a> Leonardo AI <\/a>Craiyon<\/a><\/td><\/tr>
BARK<\/td>\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684TTS\uff08\u6587\u5b57\u8f6c\u8bed\u97f3\uff09\u9879\u76ee\uff0c\u8fd9\u4e2a\u9879\u76ee\u7684\u7279\u70b9\u662f\uff0c\u5b83\u53ef\u4ee5\u5728\u6587\u5b57\u4e2d\u52a0\u5165\u63d0\u793a\u8bcd\uff0c\u6bd4\u5982\u201c\u5927\u7b11\u201d\u3002\u8fd9\u4e2a\u63d0\u793a\u8bcd\u4f1a\u53d8\u6210\u7b11\u7684\u58f0\u97f3\uff0c\u7136\u540e\u5408\u6210\u5230\u8bed\u97f3\u91cc\u53bb\u3002\u5b83\u4e5f\u53ef\u4ee5\u6df7\u5408\u201c\u7537\u58f0\u201d\uff0c\u201c\u5973\u58f0\u201d\uff0c\u8fd9\u6837\u518d\u505a\u5c31\u53ef\u4ee5\u4e0d\u7528\u518d\u505a\u62fc\u63a5\u64cd\u4f5c\u4e86<\/td>github<\/a><\/td><\/tr>
whisper<\/td>\u5728\u8bed\u97f3\u8f6c\u6587\u5b57\uff08STT\uff0c\u4e5f\u79f0ASR\uff09\u65b9\u9762\uff0cwhisper\u662f\u6211\u7528\u8fc7\u7684\u6700\u597d\u7684\uff0c\u6700\u5feb\u7684\u5e93\u3002\u6ca1\u60f3\u5230\uff0c\u8fd9\u4e48\u5feb\u7684\u6a21\u578b\uff0c\u8fd8\u80fd70x\u7684\u4f18\u5316\u7a7a\u95f4\u3002\u6211\u51c6\u5907\u90e8\u7f72\u8fd9\u4e2a\u6a21\u578b\uff0c\u5e76\u5f00\u653e\u7ed9\u5927\u5bb6\u4f7f\u7528\uff0c\u53ef\u4ee5\u7528\u6765\u8f6c\u5f55\u5927\u7684\u8bed\u97f3\u6587\u4ef6\uff0c\u548c\u8fdb\u884c\u7ffb\u8bd1\u3002\u8fd9\u4e2a\u6a21\u578b\u662f\u591a\u8bed\u8a00\u7684\uff0c\u800c\u4e14\u80fd\u81ea\u52a8\u8bc6\u522b\u662f\u4ec0\u4e48\u8bed\u8a00\uff0c\u771f\u7684\u975e\u5e38\u5f3a\u5927<\/td>github<\/a><\/td><\/tr>
OFA-Chinese\uff1a\u4e2d\u6587\u591a\u6a21\u6001\u7edf\u4e00\u9884\u8bad\u7ec3\u6a21\u578b<\/td>transformers\u7ed3\u6784\u7684\u4e2d\u6587OFA\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
\u6587\u751f\u56fe\u5f00\u6e90\u6a21\u578b\u8bd5\u70bc\u573a<\/td>\u53ef\u6839\u636e\u8f93\u5165\u6587\u5b57\u540c\u65f6\u7528stable-diffusion 1.5\u3001stable-diffusion 2.1\u3001DALL-E\u3001kandinsky-2\u7b49\u6a21\u578b\u751f\u6210\u56fe\u50cf\uff0c\u65b9\u4fbf\u6d4b\u8bd5\u6bd4\u8f83<\/td>link<\/a><\/td><\/tr>
LLMScore<\/td>LLMScore\u662f\u4e00\u79cd\u5168\u65b0\u7684\u6846\u67b6\uff0c\u80fd\u591f\u63d0\u4f9b\u5177\u6709\u591a\u7c92\u5ea6\u7ec4\u5408\u6027\u7684\u8bc4\u4f30\u5206\u6570\u3002\u5b83\u4f7f\u7528\u5927\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u6765\u8bc4\u4f30\u6587\u672c\u5230\u56fe\u50cf\u751f\u6210\u6a21\u578b\u3002\u9996\u5148\uff0c\u5c06\u56fe\u50cf\u8f6c\u5316\u4e3a\u56fe\u50cf\u7ea7\u522b\u548c\u5bf9\u8c61\u7ea7\u522b\u7684\u89c6\u89c9\u63cf\u8ff0\uff0c\u7136\u540e\u5c06\u8bc4\u4f30\u6307\u4ee4\u8f93\u5165\u5230LLM\u4e2d\uff0c\u4ee5\u8861\u91cf\u5408\u6210\u56fe\u50cf\u4e0e\u6587\u672c\u7684\u5bf9\u9f50\u7a0b\u5ea6\uff0c\u5e76\u6700\u7ec8\u751f\u6210\u4e00\u4e2a\u8bc4\u5206\u548c\u89e3\u91ca\u3002\u6211\u4eec\u7684\u5927\u91cf\u5206\u6790\u663e\u793a\uff0cLLMScore\u5728\u4f17\u591a\u6570\u636e\u96c6\u4e0a\u4e0e\u4eba\u7c7b\u5224\u65ad\u7684\u76f8\u5173\u6027\u6700\u9ad8\uff0c\u660e\u663e\u4f18\u4e8e\u5e38\u7528\u7684\u6587\u672c-\u56fe\u50cf\u5339\u914d\u5ea6\u91cf\u6307\u6807CLIP\u548cBLIP\u3002<\/td>paper<\/a>github<\/a><\/td><\/tr>
VisualGLM-6B<\/td>VisualGLM-6B \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\uff0c\u652f\u6301\u56fe\u50cf\u3001\u4e2d\u6587\u548c\u82f1\u6587\u7684\u591a\u6a21\u6001\u5bf9\u8bdd\u8bed\u8a00\u6a21\u578b\uff0c\u8bed\u8a00\u6a21\u578b\u57fa\u4e8e ChatGLM-6B\uff0c\u5177\u6709 62 \u4ebf\u53c2\u6570\uff1b\u56fe\u50cf\u90e8\u5206\u901a\u8fc7\u8bad\u7ec3 BLIP2-Qformer \u6784\u5efa\u8d77\u89c6\u89c9\u6a21\u578b\u4e0e\u8bed\u8a00\u6a21\u578b\u7684\u6865\u6881\uff0c\u6574\u4f53\u6a21\u578b\u517178\u4ebf\u53c2\u6570\u3002<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

LLM\u7684\u6570\u636e\u96c6<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u6b67\u4e49\u6570\u636e\u96c6<\/td>\u80fd\u5426\u6b63\u786e\u7684\u6d88\u9664\u6b67\u4e49\u662f\u8861\u91cf\u5927\u8bed\u8a00\u6a21\u578b\u7684\u4e00\u4e2a\u91cd\u8981\u6307\u6807\u3002\u4e0d\u8fc7\u4e00\u76f4\u6ca1\u6709\u4e00\u4e2a\u6807\u51c6\u5316\u7684\u8861\u91cf\u65b9\u6cd5\uff0c\u8fd9\u7bc7\u8bba\u6587\u63d0\u51fa\u4e86\u4e00\u4e2a\u5305\u542b1,645\u4e2a\u5177\u6709\u4e0d\u540c\u79cd\u7c7b\u6b67\u4e49\u7684\u6570\u636e\u96c6\u53ca\u5bf9\u5e94\u7684\u8bc4\u4f30\u65b9\u6cd5\u3002<\/td>github<\/a> paper<\/a><\/td><\/tr>
thu\u6307\u4ee4\u8bad\u7ec3\u6570\u636e<\/td>\u8bbe\u8ba1\u4e86\u4e00\u5957\u6d41\u7a0b\u6765\u81ea\u52a8\u4ea7\u751f\u591a\u6837\u5316\u9ad8\u8d28\u91cf\u7684\u591a\u8f6e\u6307\u4ee4\u5bf9\u8bdd\u6570\u636eUltraChat\uff0c\u5e76\u8fdb\u884c\u4e86\u7ec6\u81f4\u7684\u4eba\u5de5\u540e\u5904\u7406\u3002\u73b0\u5df2\u5c06\u82f1\u6587\u6570\u636e\u5168\u90e8\u5f00\u6e90\uff0c\u5171\u8ba1150\u4f59\u4e07\u6761\uff0c\u662f\u5f00\u6e90\u793e\u533a\u6570\u91cf\u6700\u591a\u7684\u9ad8\u8d28\u91cf\u6307\u4ee4\u6570\u636e\u4e4b\u4e00<\/td>github<\/a><\/td><\/tr>
\u591a\u6a21\u6001\u6570\u636e\u96c6MMC4<\/td>5.8\u4ebf\u56fe\u7247\uff0c1\u4ebf\u6587\u6863\uff0c400\u4ebftoken<\/td>github<\/a><\/td><\/tr>
EleutherAI \u6570\u636e<\/td>800g\u7684\u6587\u672c\u8bed\u6599\u7ed9\u4f60\u6574\u5408\u597d\u4e86\u514d\u8d39\u4e0b\u8f7d\uff0c\u4e0d\u77e5\u9053trian\u51fa\u6765\u7684model\u8d28\u91cf\u5982\u4f55\uff0c\u6253\u7b97\u8bd5\u8bd5\uff1a<\/td>pile data<\/a> paper<\/a><\/td><\/tr>
UltraChat<\/td>\u5927\u89c4\u6a21\u3001\u4fe1\u606f\u4e30\u5bcc\u3001\u591a\u6837\u5316\u7684\u591a\u8f6e\u5bf9\u8bdd\u6570\u636e<\/td>github<\/a><\/td><\/tr>
ConvFinQA\u91d1\u878d\u6570\u636e\u95ee\u7b54<\/td><\/td>github<\/a><\/td><\/tr>
The botbots dataset<\/td>\u4e00\u4e2a\u5305\u542b\u5bf9\u8bdd\u5185\u5bb9\u7684\u6570\u636e\u96c6\uff0c\u5bf9\u8bdd\u5185\u5bb9\u6765\u81ea\u4e8e\u4e24\u4e2aChatGPT\u5b9e\u4f8b(gpt-3.5-turbo)\uff0cCLT\u547d\u4ee4\u548c\u5bf9\u8bdd\u63d0\u793a\u6765\u81eaGPT-4\uff0c\u8986\u76d6\u591a\u79cd\u60c5\u5883\u548c\u4efb\u52a1\uff0c\u751f\u6210\u6210\u672c\u7ea6\u4e3a35\u7f8e\u5143\uff0c\u53ef\u7528\u4e8e\u7814\u7a76\u548c\u8bad\u7ec3\u66f4\u5c0f\u7684\u5bf9\u8bdd\u6a21\u578b(\u5982Alpaca)<\/td>github<\/a><\/td><\/tr>
alpaca_chinese_dataset – \u4eba\u5de5\u7cbe\u8c03\u7684\u4e2d\u6587\u5bf9\u8bdd\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
CodeGPT-data<\/td>\u63d0\u9ad8\u7f16\u7a0b\u80fd\u529b\u7684\u5173\u952e\u5728\u4e8e\u6570\u636e\u3002CodeGPT\u662f\u901a\u8fc7GPT\u751f\u6210\u7684\u7528\u4e8eGPT\u7684\u4ee3\u7801\u5bf9\u8bdd\u6570\u636e\u96c6\u3002\u73b0\u5728\u516c\u5f00\u4e8632K\u6761\u4e2d\u6587\u6570\u636e\uff0c\u8ba9\u6a21\u578b\u66f4\u64c5\u957f\u7f16\u7a0b<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\n\n\n\n

\u8bed\u6599\u5e93<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4eba\u540d\u8bed\u6599\u5e93<\/td><\/td>wainshine\/Chinese-Names-Corpus<\/a><\/td><\/tr>
Chinese-Word-Vectors<\/td>\u5404\u79cd\u4e2d\u6587\u8bcd\u5411\u91cf<\/td>github repo<\/a><\/td><\/tr>
\u4e2d\u6587\u804a\u5929\u8bed\u6599<\/td>\u8be5\u5e93\u641c\u96c6\u4e86\u5305\u542b\u8c46\u74e3\u591a\u8f6e, PTT\u516b\u5366\u8bed\u6599, \u9752\u4e91\u8bed\u6599, \u7535\u89c6\u5267\u5bf9\u767d\u8bed\u6599, \u8d34\u5427\u8bba\u575b\u56de\u5e16\u8bed\u6599,\u5fae\u535a\u8bed\u6599,\u5c0f\u9ec4\u9e21\u8bed\u6599<\/td>link<\/a><\/td><\/tr>
\u4e2d\u6587\u8c23\u8a00\u6570\u636e<\/td>\u8be5\u6570\u636e\u6587\u4ef6\u4e2d\uff0c\u6bcf\u4e00\u884c\u4e3a\u4e00\u6761json\u683c\u5f0f\u7684\u8c23\u8a00\u6570\u636e<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u95ee\u7b54\u6570\u636e\u96c6<\/td><\/td>\u94fe\u63a5<\/a> \u63d0\u53d6\u7801 2dva<\/td><\/tr>
\u5fae\u4fe1\u516c\u4f17\u53f7\u8bed\u6599<\/td>3G\u8bed\u6599\uff0c\u5305\u542b\u90e8\u5206\u7f51\u7edc\u6293\u53d6\u7684\u5fae\u4fe1\u516c\u4f17\u53f7\u7684\u6587\u7ae0\uff0c\u5df2\u7ecf\u53bb\u9664HTML\uff0c\u53ea\u5305\u542b\u4e86\u7eaf\u6587\u672c\u3002\u6bcf\u884c\u4e00\u7bc7\uff0c\u662fJSON\u683c\u5f0f\uff0cname\u662f\u5fae\u4fe1\u516c\u4f17\u53f7\u540d\u5b57\uff0caccount\u662f\u5fae\u4fe1\u516c\u4f17\u53f7ID\uff0ctitle\u662f\u9898\u76ee\uff0ccontent\u662f\u6b63\u6587<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406 \u8bed\u6599\u3001\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4efb\u52a1\u578b\u5bf9\u8bdd\u82f1\u6587\u6570\u636e\u96c6<\/td>\u3010\u6700\u5168\u4efb\u52a1\u578b\u5bf9\u8bdd\u6570\u636e\u96c6\u3011\u4e3b\u8981\u4ecb\u7ecd\u4e86\u4e00\u4efd\u4efb\u52a1\u578b\u5bf9\u8bdd\u6570\u636e\u96c6\u5927\u5168\uff0c\u8fd9\u4efd\u6570\u636e\u96c6\u5927\u5168\u6db5\u76d6\u4e86\u5230\u76ee\u524d\u5728\u4efb\u52a1\u578b\u5bf9\u8bdd\u9886\u57df\u7684\u6240\u6709\u5e38\u7528\u6570\u636e\u96c6\u7684\u4e3b\u8981\u4fe1\u606f\u3002\u6b64\u5916\uff0c\u4e3a\u4e86\u5e2e\u52a9\u7814\u7a76\u8005\u66f4\u597d\u7684\u628a\u63e1\u9886\u57df\u8fdb\u5c55\u7684\u8109\u7edc\uff0c\u6211\u4eec\u4ee5Leaderboard\u7684\u5f62\u5f0f\u7ed9\u51fa\u4e86\u51e0\u4e2a\u6570\u636e\u96c6\u4e0a\u7684State-of-the-art\u5b9e\u9a8c\u7ed3\u679c\u3002<\/td>github<\/a><\/td><\/tr>
\u8bed\u97f3\u8bc6\u522b\u8bed\u6599\u751f\u6210\u5de5\u5177<\/td>\u4ece\u5177\u6709\u97f3\u9891\/\u5b57\u5e55\u7684\u5728\u7ebf\u89c6\u9891\u521b\u5efa\u81ea\u52a8\u8bed\u97f3\u8bc6\u522b(ASR)\u8bed\u6599\u5e93<\/td>github<\/a><\/td><\/tr>
LitBankNLP\u6570\u636e\u96c6<\/td>\u652f\u6301\u81ea\u7136\u8bed\u8a00\u5904\u7406\u548c\u8ba1\u7b97\u4eba\u6587\u5b66\u79d1\u4efb\u52a1\u7684100\u90e8\u5e26\u6807\u8bb0\u82f1\u6587\u5c0f\u8bf4\u8bed\u6599<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587ULMFiT<\/td>\u60c5\u611f\u5206\u6790 \u6587\u672c\u5206\u7c7b \u8bed\u6599\u53ca\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
\u7701\u5e02\u533a\u9547\u884c\u653f\u533a\u5212\u6570\u636e\u5e26\u62fc\u97f3\u6807\u6ce8<\/td><\/td>github<\/a><\/td><\/tr>
\u6559\u80b2\u884c\u4e1a\u65b0\u95fb \u81ea\u52a8\u6587\u6458 \u8bed\u6599\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u7ef4\u57fa\u5927\u89c4\u6a21\u5e73\u884c\u6587\u672c\u8bed\u6599<\/td>85\u79cd\u8bed\u8a00\u30011620\u79cd\u8bed\u8a00\u5bf9\u3001135M\u5bf9\u7167\u53e5<\/td>github<\/a><\/td><\/tr>
\u53e4\u8bd7\u8bcd\u5e93<\/td><\/td>github repo<\/a>
\u66f4\u5168\u7684\u53e4\u8bd7\u8bcd\u5e93<\/a><\/td><\/tr>
\u4f4e\u5185\u5b58\u52a0\u8f7d\u7ef4\u57fa\u767e\u79d1\u6570\u636e<\/td>\u7528\u65b0\u7248nlp\u5e93\u52a0\u8f7d17GB+\u82f1\u6587\u7ef4\u57fa\u8bed\u6599\u53ea\u5360\u75289MB\u5185\u5b58\u904d\u5386\u901f\u5ea62-3 Gbit\/s<\/td>github<\/a><\/td><\/tr>
\u5bf9\u8054\u6570\u636e<\/td>700,000 couplets, \u8d85\u8fc770\u4e07\u5bf9\u5bf9\u8054<\/td>github<\/a><\/td><\/tr>
\u300a\u914d\u8272\u8f9e\u5178\u300b\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
42GB\u7684JD\u5ba2\u670d\u5bf9\u8bdd\u6570\u636e(CSDD)<\/td><\/td>github<\/a><\/td><\/tr>
70\u4e07\u5bf9\u8054\u6570\u636e<\/td><\/td>link<\/a><\/td><\/tr>
\u7528\u6237\u540d\u9ed1\u540d\u5355\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u4f9d\u5b58\u53e5\u6cd5\u5206\u6790\u8bed\u6599<\/td>4\u4e07\u53e5\u9ad8\u8d28\u91cf\u6807\u6ce8\u6570\u636e<\/td>Homepage<\/a><\/td><\/tr>
\u4eba\u6c11\u65e5\u62a5\u8bed\u6599\u5904\u7406\u5de5\u5177\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u865a\u5047\u65b0\u95fb\u6570\u636e\u96c6 fake news corpus<\/td><\/td>github<\/a><\/td><\/tr>
\u8bd7\u6b4c\u8d28\u91cf\u8bc4\u4ef7\/\u7ec6\u7c92\u5ea6\u60c5\u611f\u8bd7\u6b4c\u8bed\u6599\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u76f8\u5173\u7684\u5f00\u653e\u4efb\u52a1<\/td>\u6570\u636e\u96c6\u4ee5\u53ca\u5f53\u524d\u6700\u4f73\u7ed3\u679c<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u7f29\u5199\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u4efb\u52a1\u57fa\u51c6\u6d4b\u8bc4<\/td>\u4ee3\u8868\u6027\u7684\u6570\u636e\u96c6-\u57fa\u51c6(\u9884\u8bad\u7ec3)\u6a21\u578b-\u8bed\u6599\u5e93-baseline-\u5de5\u5177\u5305-\u6392\u884c\u699c<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u8c23\u8a00\u6570\u636e\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
CLUEDatasetSearch<\/td>\u4e2d\u82f1\u6587NLP\u6570\u636e\u96c6\u641c\u7d22\u6240\u6709\u4e2d\u6587NLP\u6570\u636e\u96c6\uff0c\u9644\u5e38\u7528\u82f1\u6587NLP\u6570\u636e\u96c6<\/td>github<\/a><\/td><\/tr>
\u591a\u6587\u6863\u6458\u8981\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u8ba9\u4eba\u4eba\u90fd\u53d8\u5f97\u201c\u5f6c\u5f6c\u6709\u793c\u201d\u793c\u8c8c\u8fc1\u79fb\u4efb\u52a1<\/td>\u5728\u4fdd\u7559\u610f\u4e49\u7684\u540c\u65f6\u5c06\u975e\u793c\u8c8c\u8bed\u53e5\u8f6c\u6362\u4e3a\u793c\u8c8c\u8bed\u53e5\uff0c\u63d0\u4f9b\u5305\u542b139M + \u5b9e\u4f8b\u7684\u6570\u636e\u96c6<\/td>paper and code<\/a><\/td><\/tr>
\u7ca4\u8bed\/\u82f1\u8bed\u4f1a\u8bdd\u53cc\u8bed\u8bed\u6599\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587NLP\u6570\u636e\u96c6\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u7c7b\u4eba\u540d\/\u5730\u540d\/\u7ec4\u7ec7\u673a\u6784\u540d\u7684\u547d\u540d\u4f53\u8bc6\u522b\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u8bed\u8a00\u7406\u89e3\u6d4b\u8bc4\u57fa\u51c6<\/td>\u5305\u62ec\u4ee3\u8868\u6027\u7684\u6570\u636e\u96c6&\u57fa\u51c6\u6a21\u578b&\u8bed\u6599\u5e93&\u6392\u884c\u699c<\/td>github<\/a><\/td><\/tr>
OpenCLaP\u591a\u9886\u57df\u5f00\u6e90\u4e2d\u6587\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u4ed3\u5e93<\/td>\u6c11\u4e8b\u6587\u4e66\u3001\u5211\u4e8b\u6587\u4e66\u3001\u767e\u5ea6\u767e\u79d1<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u5168\u8bcd\u8986\u76d6BERT\u53ca\u4e24\u4efd\u9605\u8bfb\u7406\u89e3\u6570\u636e<\/td>DRCD\u6570\u636e\u96c6\uff1a\u7531\u4e2d\u56fd\u53f0\u6e7e\u53f0\u8fbe\u7814\u7a76\u9662\u53d1\u5e03\uff0c\u5176\u5f62\u5f0f\u4e0eSQuAD\u76f8\u540c\uff0c\u662f\u57fa\u4e8e\u7e41\u4f53\u4e2d\u6587\u7684\u62bd\u53d6\u5f0f\u9605\u8bfb\u7406\u89e3\u6570\u636e\u96c6\u3002
CMRC 2018\u6570\u636e\u96c6:\u54c8\u5de5\u5927\u8baf\u98de\u8054\u5408\u5b9e\u9a8c\u5ba4\u53d1\u5e03\u7684\u4e2d\u6587\u673a\u5668\u9605\u8bfb\u7406\u89e3\u6570\u636e\u3002\u6839\u636e\u7ed9\u5b9a\u95ee\u9898\uff0c\u7cfb\u7edf\u9700\u8981\u4ece\u7bc7\u7ae0\u4e2d\u62bd\u53d6\u51fa\u7247\u6bb5\u4f5c\u4e3a\u7b54\u6848\uff0c\u5f62\u5f0f\u4e0eSQuAD\u76f8\u540c\u3002<\/td>		github<\/a><\/td><\/tr>
Dakshina\u6570\u636e\u96c6<\/td>\u5341\u4e8c\u79cd\u5357\u4e9a\u8bed\u8a00\u7684\u62c9\u4e01\/\u672c\u5730\u6587\u5b57\u5e73\u884c\u6570\u636e\u96c6\u5408<\/td>github<\/a><\/td><\/tr>
OPUS-100<\/td>\u4ee5\u82f1\u6587\u4e3a\u4e2d\u5fc3\u7684\u591a\u8bed(100\u79cd)\u5e73\u884c\u8bed\u6599<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u9605\u8bfb\u7406\u89e3\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5411\u91cf\u5408\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u8bed\u8a00\u7406\u89e3\u6d4b\u8bc4\u57fa\u51c6<\/td>\u5305\u62ec\u4ee3\u8868\u6027\u7684\u6570\u636e\u96c6\u3001\u57fa\u51c6(\u9884\u8bad\u7ec3)\u6a21\u578b\u3001\u8bed\u6599\u5e93\u3001\u6392\u884c\u699c<\/td>github<\/a><\/td><\/tr>
NLP\u6570\u636e\u96c6\/\u57fa\u51c6\u4efb\u52a1\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
LitBankNLP\u6570\u636e\u96c6<\/td>\u652f\u6301\u81ea\u7136\u8bed\u8a00\u5904\u7406\u548c\u8ba1\u7b97\u4eba\u6587\u5b66\u79d1\u4efb\u52a1\u7684100\u90e8\u5e26\u6807\u8bb0\u82f1\u6587\u5c0f\u8bf4\u8bed\u6599<\/td>github<\/a><\/td><\/tr>
70\u4e07\u5bf9\u8054\u6570\u636e<\/td><\/td>github<\/a><\/td><\/tr>
\u6587\u8a00\u6587\uff08\u53e4\u6587\uff09-\u73b0\u4ee3\u6587\u5e73\u884c\u8bed\u6599<\/td>\u77ed\u7bc7\u7ae0\u4e2d\u5305\u62ec\u4e86\u300a\u8bba\u8bed\u300b\u3001\u300a\u5b5f\u5b50\u300b\u3001\u300a\u5de6\u4f20\u300b\u7b49\u7bc7\u5e45\u8f83\u77ed\u7684\u53e4\u7c4d\uff0c\u5df2\u548c\u300a\u8d44\u6cbb\u901a\u9274\u300b\u5408\u5e76<\/td>github<\/a><\/td><\/tr>
COLDDateset\uff0c\u4e2d\u6587\u5192\u72af\u6027\u8bed\u8a00\u68c0\u6d4b\u6570\u636e\u96c6<\/td>\u6db5\u76d6\u4e86\u79cd\u65cf\u3001\u6027\u522b\u548c\u5730\u533a\u7b49\u8bdd\u9898\u5185\u5bb9\uff0c\u6570\u636e\u5f85\u8bba\u6587\u53d1\u8868\u540e\u653e\u51fa<\/td>paper<\/a><\/td><\/tr>
GAOKAO-bench\uff1a\u4ee5\u4e2d\u56fd\u9ad8\u8003\u9898\u76ee\u4f5c\u4e3a\u6570\u636e\u96c6<\/td>\u4ee5\u4e2d\u56fd\u9ad8\u8003\u9898\u76ee\u4f5c\u4e3a\u6570\u636e\u96c6\uff0c\u8bc4\u4f30\u5927\u8bed\u8a00\u6a21\u578b\u7684\u8bed\u8a00\u7406\u89e3\u80fd\u529b\u548c\u903b\u8f91\u63a8\u7406\u80fd\u529b\u7684\u6d4b\u8bc4\u6846\u67b6\uff0c\u5305\u542b1781\u9053\u9009\u62e9\u9898\u3001218\u9053\u586b\u7a7a\u9898\u548c812\u9053\u89e3\u7b54\u9898<\/td>github<\/a><\/td><\/tr>
zero to nlp – \u4e2d\u6587nlp\u5e94\u7528\u6570\u636e\u3001\u6a21\u578b\u3001\u8bad\u7ec3\u3001\u63a8\u7406<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u8bcd\u5e93\u53ca\u8bcd\u6cd5\u5de5\u5177<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
textfilter<\/td>\u4e2d\u82f1\u6587\u654f\u611f\u8bcd\u8fc7\u6ee4<\/td>observerss\/textfilter<\/a><\/td><\/tr>
\u4eba\u540d\u62bd\u53d6\u529f\u80fd<\/td>\u4e2d\u6587\uff08\u73b0\u4ee3\u3001\u53e4\u4ee3\uff09\u540d\u5b57\u3001\u65e5\u6587\u540d\u5b57\u3001\u4e2d\u6587\u7684\u59d3\u548c\u540d\u3001\u79f0\u547c\uff08\u5927\u59e8\u5988\u3001\u5c0f\u59e8\u5988\u7b49\uff09\u3001\u82f1\u6587->\u4e2d\u6587\u540d\u5b57\uff08\u674e\u7ea6\u7ff0\uff09\u3001\u6210\u8bed\u8bcd\u5178<\/td>cocoNLP<\/a><\/td><\/tr>
\u4e2d\u6587\u7f29\u5199\u5e93<\/td>\u5168\u56fd\u4eba\u5927: \u5168\u56fd \u4eba\u6c11 \u4ee3\u8868\u5927\u4f1a; \u4e2d\u56fd: \u4e2d\u534e\u4eba\u6c11\u5171\u548c\u56fd;\u5973\u7f51\u8d5b: \u5973\u5b50\/n \u7f51\u7403\/n \u6bd4\u8d5b\/vn<\/td>github<\/a><\/td><\/tr>
\u6c49\u8bed\u62c6\u5b57\u8bcd\u5178<\/td>\u6f22\u5b57 \u62c6\u6cd5 (\u4e00) \u62c6\u6cd5 (\u4e8c) \u62c6\u6cd5 (\u4e09) \u62c6 \u624b \u65a5 \u624c \u65a5 \u624d \u65a5<\/td>kfcd\/chaizi<\/a><\/td><\/tr>
\u8bcd\u6c47\u60c5\u611f\u503c<\/td>\u5c71\u6cc9\u6c34:0.400704566541
\u5145\u6c9b: 0.37006739587<\/td>		rainarch\/SentiBridge<\/a><\/td><\/tr>
\u4e2d\u6587\u8bcd\u5e93\u3001\u505c\u7528\u8bcd\u3001\u654f\u611f\u8bcd<\/td><\/td>dongxiexidian\/Chinese<\/a><\/td><\/tr>
python-pinyin<\/td>\u6c49\u5b57\u8f6c\u62fc\u97f3<\/td>mozillazg\/python-pinyin<\/a><\/td><\/tr>
zhtools<\/td>\u4e2d\u6587\u7e41\u7b80\u4f53\u4e92\u8f6c<\/td>skydark\/nstools<\/a><\/td><\/tr>
\u82f1\u6587\u6a21\u62df\u4e2d\u6587\u53d1\u97f3\u5f15\u64ce<\/td>say wo i ni #\u8bf4\uff1a\u6211\u7231\u4f60<\/td>tinyfool\/ChineseWithEnglish<\/a><\/td><\/tr>
chinese_dictionary<\/td>\u540c\u4e49\u8bcd\u5e93\u3001\u53cd\u4e49\u8bcd\u5e93\u3001\u5426\u5b9a\u8bcd\u5e93<\/td>guotong1988\/chinese_dictionary<\/a><\/td><\/tr>
wordninja<\/td>\u65e0\u7a7a\u683c\u82f1\u6587\u4e32\u5206\u5272\u3001\u62bd\u53d6\u5355\u8bcd<\/td>wordninja<\/a><\/td><\/tr>
\u6c7d\u8f66\u54c1\u724c\u3001\u6c7d\u8f66\u96f6\u4ef6\u76f8\u5173\u8bcd\u6c47<\/td><\/td>data<\/a><\/td><\/tr>
THU\u6574\u7406\u7684\u8bcd\u5e93<\/td>IT\u8bcd\u5e93\u3001\u8d22\u7ecf\u8bcd\u5e93\u3001\u6210\u8bed\u8bcd\u5e93\u3001\u5730\u540d\u8bcd\u5e93\u3001\u5386\u53f2\u540d\u4eba\u8bcd\u5e93\u3001\u8bd7\u8bcd\u8bcd\u5e93\u3001\u533b\u5b66\u8bcd\u5e93\u3001\u996e\u98df\u8bcd\u5e93\u3001\u6cd5\u5f8b\u8bcd\u5e93\u3001\u6c7d\u8f66\u8bcd\u5e93\u3001\u52a8\u7269\u8bcd\u5e93<\/td>link<\/a><\/td><\/tr>
\u7f6a\u540d\u6cd5\u52a1\u540d\u8bcd\u53ca\u5206\u7c7b\u6a21\u578b<\/td>\u5305\u542b856\u9879\u7f6a\u540d\u77e5\u8bc6\u56fe\u8c31, \u57fa\u4e8e280\u4e07\u7f6a\u540d\u8bad\u7ec3\u5e93\u7684\u7f6a\u540d\u9884\u6d4b,\u57fa\u4e8e20W\u6cd5\u52a1\u95ee\u7b54\u5bf9\u768413\u7c7b\u95ee\u9898\u5206\u7c7b\u4e0e\u6cd5\u5f8b\u8d44\u8baf\u95ee\u7b54\u529f\u80fd<\/td>github<\/a><\/td><\/tr>
\u5206\u8bcd\u8bed\u6599\u5e93+\u4ee3\u7801<\/td><\/td>\u767e\u5ea6\u7f51\u76d8\u94fe\u63a5<\/a> – \u63d0\u53d6\u7801 pea6<\/td><\/tr>
\u57fa\u4e8eBi-LSTM + CRF\u7684\u4e2d\u6587\u5206\u8bcd+\u8bcd\u6027\u6807\u6ce8<\/td>keras\u5b9e\u73b0<\/td>link<\/a><\/td><\/tr>
\u57fa\u4e8eUniversal Transformer + CRF \u7684\u4e2d\u6587\u5206\u8bcd\u548c\u8bcd\u6027\u6807\u6ce8<\/td><\/td>link<\/a><\/td><\/tr>
\u5feb\u901f\u795e\u7ecf\u7f51\u7edc\u5206\u8bcd\u5305<\/td>java version<\/td><\/a><\/td><\/tr>
chinese-xinhua<\/td>\u4e2d\u534e\u65b0\u534e\u5b57\u5178\u6570\u636e\u5e93\u53caapi\uff0c\u5305\u62ec\u5e38\u7528\u6b47\u540e\u8bed\u3001\u6210\u8bed\u3001\u8bcd\u8bed\u548c\u6c49\u5b57<\/td>github<\/a><\/td><\/tr>
SpaCy \u4e2d\u6587\u6a21\u578b<\/td>\u5305\u542bParser, NER, \u8bed\u6cd5\u6811\u7b49\u529f\u80fd\u3002\u6709\u4e00\u4e9b\u82f1\u6587package\u4f7f\u7528spacy\u7684\u82f1\u6587\u6a21\u578b\u7684\uff0c\u5982\u679c\u8981\u9002\u914d\u4e2d\u6587\uff0c\u53ef\u80fd\u9700\u8981\u4f7f\u7528spacy\u4e2d\u6587\u6a21\u578b\u3002<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u5b57\u7b26\u6570\u636e<\/td><\/td>github<\/a><\/td><\/tr>
Synonyms\u4e2d\u6587\u8fd1\u4e49\u8bcd\u5de5\u5177\u5305<\/td><\/td>github<\/a><\/td><\/tr>
HarvestText<\/td>\u9886\u57df\u81ea\u9002\u5e94\u6587\u672c\u6316\u6398\u5de5\u5177\uff08\u65b0\u8bcd\u53d1\u73b0-\u60c5\u611f\u5206\u6790-\u5b9e\u4f53\u94fe\u63a5\u7b49\uff09<\/td>github<\/a><\/td><\/tr>
word2word<\/td>\u65b9\u4fbf\u6613\u7528\u7684\u591a\u8bed\u8a00\u8bcd-\u8bcd\u5bf9\u96c662\u79cd\u8bed\u8a00\/3,564\u4e2a\u591a\u8bed\u8a00\u5bf9<\/td>github<\/a><\/td><\/tr>
\u591a\u97f3\u5b57\u8bcd\u5178\u6570\u636e\u53ca\u4ee3\u7801<\/td><\/td>github<\/a><\/td><\/tr>
\u6c49\u5b57\u3001\u8bcd\u8bed\u3001\u6210\u8bed\u67e5\u8be2\u63a5\u53e3<\/td><\/td>github<\/a><\/td><\/tr>
103976\u4e2a\u82f1\u8bed\u5355\u8bcd\u5e93\u5305<\/td>\uff08sql\u7248\uff0ccsv\u7248\uff0cExcel\u7248\uff09<\/td>github<\/a><\/td><\/tr>
\u82f1\u6587\u810f\u8bdd\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u8bcd\u8bed\u62fc\u97f3\u6570\u636e<\/td><\/td>github<\/a><\/td><\/tr>
186\u79cd\u8bed\u8a00\u7684\u6570\u5b57\u53eb\u6cd5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u4e16\u754c\u5404\u56fd\u5927\u89c4\u6a21\u4eba\u540d\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u6c49\u5b57\u5b57\u7b26\u7279\u5f81\u63d0\u53d6\u5668 (featurizer)<\/td>\u63d0\u53d6\u6c49\u5b57\u7684\u7279\u5f81\uff08\u53d1\u97f3\u7279\u5f81\u3001\u5b57\u5f62\u7279\u5f81\uff09\u7528\u505a\u6df1\u5ea6\u5b66\u4e60\u7684\u7279\u5f81<\/td>github<\/a><\/td><\/tr>
char_featurizer – \u6c49\u5b57\u5b57\u7b26\u7279\u5f81\u63d0\u53d6\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u65e5\u97e9\u5206\u8bcd\u5e93mecab\u7684Python\u63a5\u53e3\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
g2pC\u57fa\u4e8e\u4e0a\u4e0b\u6587\u7684\u6c49\u8bed\u8bfb\u97f3\u81ea\u52a8\u6807\u8bb0\u6a21\u5757<\/td><\/td>github<\/a><\/td><\/tr>
ssc, Sound Shape Code<\/td>\u97f3\u5f62\u7801 – \u57fa\u4e8e\u201c\u97f3\u5f62\u7801\u201d\u7684\u4e2d\u6587\u5b57\u7b26\u4e32\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u65b9\u6cd5<\/td>version 1<\/a>
version 2<\/a>
blog\/introduction<\/a><\/td><\/tr>
\u57fa\u4e8e\u767e\u79d1\u77e5\u8bc6\u5e93\u7684\u4e2d\u6587\u8bcd\u8bed\u591a\u8bcd\u4e49\/\u4e49\u9879\u83b7\u53d6\u4e0e\u7279\u5b9a\u53e5\u5b50\u8bcd\u8bed\u8bed\u4e49\u6d88\u6b67<\/td><\/td>github<\/a><\/td><\/tr>
Tokenizer\u5feb\u901f\u3001\u53ef\u5b9a\u5236\u7684\u6587\u672c\u8bcd\u6761\u5316\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
Tokenizers<\/td>\u6ce8\u91cd\u6027\u80fd\u4e0e\u591a\u529f\u80fd\u6027\u7684\u6700\u5148\u8fdb\u5206\u8bcd\u5668<\/td>github<\/a><\/td><\/tr>
\u901a\u8fc7\u540c\u4e49\u8bcd\u66ff\u6362\u5b9e\u73b0\u6587\u672c\u201c\u53d8\u8138\u201d<\/td><\/td>github<\/a><\/td><\/tr>
token2index\u4e0ePyTorch\/Tensorflow\u517c\u5bb9\u7684\u5f3a\u5927\u8f7b\u91cf\u8bcd\u6761\u7d22\u5f15\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u7e41\u7b80\u4f53\u8f6c\u6362<\/td><\/td>github<\/a><\/td><\/tr>
\u7ca4\u8bedNLP\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u9886\u57df\u8bcd\u5178\u5e93<\/td>\u6db5\u76d668\u4e2a\u9886\u57df\u3001\u5171\u8ba1916\u4e07\u8bcd\u7684\u4e13\u4e1a\u8bcd\u5178\u77e5\u8bc6\u5e93<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b&\u5927\u6a21\u578b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
BMList<\/td>\u5927\u6a21\u578b\u5927\u5217\u8868<\/td>github<\/a><\/td><\/tr>
bert\u8bba\u6587\u4e2d\u6587\u7ffb\u8bd1<\/td><\/td>link<\/a><\/td><\/tr>
bert\u539f\u4f5c\u8005\u7684slides<\/td><\/td>link<\/a><\/td><\/tr>
\u6587\u672c\u5206\u7c7b\u5b9e\u8df5<\/td><\/td>github<\/a><\/td><\/tr>
bert tutorial\u6587\u672c\u5206\u7c7b\u6559\u7a0b<\/td><\/td>github<\/a><\/td><\/tr>
bert pytorch\u5b9e\u73b0<\/td><\/td>github<\/a><\/td><\/tr>
bert pytorch\u5b9e\u73b0<\/td><\/td>github<\/a><\/td><\/tr>
BERT\u751f\u6210\u53e5\u5411\u91cf\uff0cBERT\u505a\u6587\u672c\u5206\u7c7b\u3001\u6587\u672c\u76f8\u4f3c\u5ea6\u8ba1\u7b97<\/td><\/td>github<\/a><\/td><\/tr>
bert\u3001ELMO\u7684\u56fe\u89e3<\/td><\/td>github<\/a><\/td><\/tr>
BERT Pre-trained models and downstream applications<\/td><\/td>github<\/a><\/td><\/tr>
\u8bed\u8a00\/\u77e5\u8bc6\u8868\u793a\u5de5\u5177BERT & ERNIE<\/td><\/td>github<\/a><\/td><\/tr>
Kashgari\u4e2d\u4f7f\u7528gpt-2\u8bed\u8a00\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
Facebook LAMA<\/td>\u7528\u4e8e\u5206\u6790\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u4e2d\u5305\u542b\u7684\u4e8b\u5b9e\u548c\u5e38\u8bc6\u77e5\u8bc6\u7684\u63a2\u9488\u3002\u8bed\u8a00\u6a21\u578b\u5206\u6790\uff0c\u63d0\u4f9bTransformer-XL\/BERT\/ELMo\/GPT\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u7684\u7edf\u4e00\u8bbf\u95ee\u63a5\u53e3<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u7684GPT2\u8bad\u7ec3\u4ee3\u7801<\/td><\/td>github<\/a><\/td><\/tr>
XLMFacebook\u7684\u8de8\u8bed\u8a00\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
\u6d77\u91cf\u4e2d\u6587\u9884\u8bad\u7ec3ALBERT\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
Transformers 20<\/td>\u652f\u6301TensorFlow 20 \u548c PyTorch \u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b(BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet\u2026) 8\u79cd\u67b6\u6784\/33\u79cd\u9884\u8bad\u7ec3\u6a21\u578b\/102\u79cd\u8bed\u8a00<\/td>github<\/a><\/td><\/tr>
8\u7bc7\u8bba\u6587\u68b3\u7406BERT\u76f8\u5173\u6a21\u578b\u8fdb\u5c55\u4e0e\u53cd\u601d<\/td><\/td>github<\/a><\/td><\/tr>
\u6cd5\u6587RoBERTa\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b<\/td>\u7528138GB\u8bed\u6599\u8bad\u7ec3\u7684\u6cd5\u6587RoBERTa\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b<\/td>link<\/a><\/td><\/tr>
\u4e2d\u6587\u9884\u8bad\u7ec3 ELECTREA \u6a21\u578b<\/td>\u57fa\u4e8e\u5bf9\u6297\u5b66\u4e60 pretrain Chinese Model<\/td>github<\/a><\/td><\/tr>
albert-chinese-ner<\/td>\u7528\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578bALBERT\u505a\u4e2d\u6587NER<\/td>github<\/a><\/td><\/tr>
\u5f00\u6e90\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u5408\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587ELECTRA\u9884\u8bad\u7ec3\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
\u7528Transformers(BERT, XLNet, Bart, Electra, Roberta, XLM-Roberta)\u9884\u6d4b\u4e0b\u4e00\u4e2a\u8bcd(\u6a21\u578b\u6bd4\u8f83)<\/td><\/td>github<\/a><\/td><\/tr>
TensorFlow Hub<\/td>40+\u79cd\u8bed\u8a00\u7684\u65b0\u8bed\u8a00\u6a21\u578b(\u5305\u62ec\u4e2d\u6587)<\/td>link<\/a><\/td><\/tr>
UER<\/td>\u57fa\u4e8e\u4e0d\u540c\u8bed\u6599\u3001\u7f16\u7801\u5668\u3001\u76ee\u6807\u4efb\u52a1\u7684\u4e2d\u6587\u9884\u8bad\u7ec3\u6a21\u578b\u4ed3\u5e93\uff08\u5305\u62ecBERT\u3001GPT\u3001ELMO\u7b49\uff09<\/td>github<\/a><\/td><\/tr>
\u5f00\u6e90\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u5408\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u591a\u8bed\u8a00\u53e5\u5411\u91cf\u5305<\/td><\/td>github<\/a><\/td><\/tr>
Language Model as a Service (LMaaS)<\/td>\u8bed\u8a00\u6a21\u578b\u5373\u670d\u52a1<\/td>github<\/a><\/td><\/tr>
\u5f00\u6e90\u8bed\u8a00\u6a21\u578bGPT-NeoX-20B<\/td>200\u4ebf\u53c2\u6570\uff0c\u662f\u76ee\u524d\u6700\u5927\u7684\u53ef\u516c\u5f00\u8bbf\u95ee\u7684\u9884\u8bad\u7ec3\u901a\u7528\u81ea\u56de\u5f52\u8bed\u8a00\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u79d1\u5b66\u6587\u732e\u6570\u636e\u96c6\uff08CSL\uff09<\/td>\u5305\u542b 396,209 \u7bc7\u4e2d\u6587\u6838\u5fc3\u671f\u520a\u8bba\u6587\u5143\u4fe1\u606f \uff08\u6807\u9898\u3001\u6458\u8981\u3001\u5173\u952e\u8bcd\u3001\u5b66\u79d1\u3001\u95e8\u7c7b\uff09\u3002CSL \u6570\u636e\u96c6\u53ef\u4ee5\u4f5c\u4e3a\u9884\u8bad\u7ec3\u8bed\u6599\uff0c\u4e5f\u53ef\u4ee5\u6784\u5efa\u8bb8\u591aNLP\u4efb\u52a1\uff0c\u4f8b\u5982\u6587\u672c\u6458\u8981\uff08\u6807\u9898\u9884\u6d4b\uff09\u3001 \u5173\u952e\u8bcd\u751f\u6210\u548c\u6587\u672c\u5206\u7c7b\u7b49\u3002<\/td>github<\/a><\/td><\/tr>
\u5927\u6a21\u578b\u5f00\u53d1\u795e\u5668<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u62bd\u53d6<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u65f6\u95f4\u62bd\u53d6<\/td>\u5df2\u96c6\u6210\u5230 python package cocoNLP<\/a>\u4e2d\uff0c\u6b22\u8fce\u8bd5\u7528<\/td>java version<\/a>
python version<\/a><\/td><\/tr>
\u795e\u7ecf\u7f51\u7edc\u5173\u7cfb\u62bd\u53d6 pytorch<\/td>\u6682\u4e0d\u652f\u6301\u4e2d\u6587<\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8ebert\u7684\u547d\u540d\u5b9e\u4f53\u8bc6\u522b pytorch<\/td>\u6682\u4e0d\u652f\u6301\u4e2d\u6587<\/td>github<\/a><\/td><\/tr>
\u5173\u952e\u8bcd(Keyphrase)\u62bd\u53d6\u5305 pke<\/td><\/td>github<\/a><\/td><\/tr>
BLINK\u6700\u5148\u8fdb\u7684\u5b9e\u4f53\u94fe\u63a5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
BERT\/CRF\u5b9e\u73b0\u7684\u547d\u540d\u5b9e\u4f53\u8bc6\u522b<\/td><\/td>github<\/a><\/td><\/tr>
\u652f\u6301\u6279\u5e76\u884c\u7684LatticeLSTM\u4e2d\u6587\u547d\u540d\u5b9e\u4f53\u8bc6\u522b<\/td><\/td>github<\/a><\/td><\/tr>
\u6784\u5efa\u533b\u7597\u5b9e\u4f53\u8bc6\u522b\u7684\u6a21\u578b<\/td>\u5305\u542b\u8bcd\u5178\u548c\u8bed\u6599\u6807\u6ce8\uff0c\u57fa\u4e8epython<\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eTensorFlow\u548cBERT\u7684\u7ba1\u9053\u5f0f\u5b9e\u4f53\u53ca\u5173\u7cfb\u62bd\u53d6<\/td>– Entity and Relation Extraction Based on TensorFlow and BERT \u57fa\u4e8eTensorFlow\u548cBERT\u7684\u7ba1\u9053\u5f0f\u5b9e\u4f53\u53ca\u5173\u7cfb\u62bd\u53d6\uff0c2019\u8bed\u8a00\u4e0e\u667a\u80fd\u6280\u672f\u7ade\u8d5b\u4fe1\u606f\u62bd\u53d6\u4efb\u52a1\u89e3\u51b3\u65b9\u6848\u3002Schema based Knowledge Extraction, SKE 2019<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u547d\u540d\u5b9e\u4f53\u8bc6\u522bNeuroNER vs BertNER<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eBERT\u7684\u4e2d\u6587\u547d\u540d\u5b9e\u4f53\u8bc6\u522b<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u5173\u952e\u77ed\u8bed\u62bd\u53d6\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
bert<\/td>\u7528\u4e8e\u4e2d\u6587\u547d\u540d\u5b9e\u4f53\u8bc6\u522b tensorflow\u7248\u672c<\/td>github<\/a><\/td><\/tr>
bert-Kashgari<\/td>\u57fa\u4e8e keras \u7684\u5c01\u88c5\u5206\u7c7b\u6807\u6ce8\u6846\u67b6 Kashgari\uff0c\u51e0\u5206\u949f\u5373\u53ef\u642d\u5efa\u4e00\u4e2a\u5206\u7c7b\u6216\u8005\u5e8f\u5217\u6807\u6ce8\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
cocoNLP<\/td>\u4eba\u540d\u3001\u5730\u5740\u3001\u90ae\u7bb1\u3001\u624b\u673a\u53f7\u3001\u624b\u673a\u5f52\u5c5e\u5730 \u7b49\u4fe1\u606f\u7684\u62bd\u53d6\uff0crake\u77ed\u8bed\u62bd\u53d6\u7b97\u6cd5\u3002<\/td>github<\/a><\/td><\/tr>
Microsoft\u591a\u8bed\u8a00\u6570\u5b57\/\u5355\u4f4d\/\u5982\u65e5\u671f\u65f6\u95f4\u8bc6\u522b\u5305<\/td><\/td>github<\/a><\/td><\/tr>
\u767e\u5ea6\u5f00\u6e90\u7684\u57fa\u51c6\u4fe1\u606f\u62bd\u53d6\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u5730\u5740\u5206\u8bcd\uff08\u5730\u5740\u5143\u7d20\u8bc6\u522b\u4e0e\u62bd\u53d6\uff09\uff0c\u901a\u8fc7\u5e8f\u5217\u6807\u6ce8\u8fdb\u884cNER<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u4f9d\u5b58\u53e5\u6cd5\u7684\u5f00\u653e\u57df\u6587\u672c\u77e5\u8bc6\u4e09\u5143\u7ec4\u62bd\u53d6\u548c\u77e5\u8bc6\u5e93\u6784\u5efa<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u9884\u8bad\u7ec3\u6a21\u578b\u7684\u4e2d\u6587\u5173\u952e\u8bcd\u62bd\u53d6\u65b9\u6cd5<\/td><\/td>github<\/a><\/td><\/tr>
chinese_keyphrase_extractor (CKPE)<\/td>A tool for chinese keyphrase extraction \u4e00\u4e2a\u5feb\u901f\u4ece\u81ea\u7136\u8bed\u8a00\u6587\u672c\u4e2d\u63d0\u53d6\u548c\u8bc6\u522b\u5173\u952e\u77ed\u8bed\u7684\u5de5\u5177<\/td>github<\/a><\/td><\/tr>
\u7b80\u5355\u7684\u7b80\u5386\u89e3\u6790\u5668\uff0c\u7528\u6765\u4ece\u7b80\u5386\u4e2d\u63d0\u53d6\u5173\u952e\u4fe1\u606f<\/td><\/td>github<\/a><\/td><\/tr>
BERT-NER-Pytorch\u4e09\u79cd\u4e0d\u540c\u6a21\u5f0f\u7684BERT\u4e2d\u6587NER\u5b9e\u9a8c<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u77e5\u8bc6\u56fe\u8c31<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u6e05\u534e\u5927\u5b66XLORE\u4e2d\u82f1\u6587\u8de8\u8bed\u8a00\u767e\u79d1\u77e5\u8bc6\u56fe\u8c31<\/td>\u767e\u5ea6\u3001\u4e2d\u6587\u7ef4\u57fa\u3001\u82f1\u6587\u7ef4\u57fa<\/td>link<\/a><\/td><\/tr>
\u6587\u6863\u56fe\u8c31\u81ea\u52a8\u751f\u6210<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u533b\u7597\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u7684\u95ee\u7b54\u7cfb\u7edf<\/td><\/td>github<\/a>
\u8be5repo\u53c2\u8003\u4e86github<\/a><\/td><\/tr>
\u4e2d\u6587\u4eba\u7269\u5173\u7cfb\u77e5\u8bc6\u56fe\u8c31\u9879\u76ee<\/td><\/td>github<\/a><\/td><\/tr>
AmpliGraph \u77e5\u8bc6\u56fe\u8c31\u8868\u793a\u5b66\u4e60(Python)\u5e93\u77e5\u8bc6\u56fe\u8c31\u6982\u5ff5\u94fe\u63a5\u9884\u6d4b<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31\u8d44\u6599\u3001\u6570\u636e\u53ca\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u767e\u5ea6\u767e\u79d1\u7684\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31<\/td>\u62bd\u53d6\u4e09\u5143\u7ec4\u4fe1\u606f\uff0c\u6784\u5efa\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31<\/td>github<\/a><\/td><\/tr>
Zincbase \u77e5\u8bc6\u56fe\u8c31\u6784\u5efa\u5de5\u5177\u5305<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u77e5\u8bc6\u56fe\u8c31\u7684\u95ee\u7b54\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
\u77e5\u8bc6\u56fe\u8c31\u6df1\u5ea6\u5b66\u4e60\u76f8\u5173\u8d44\u6599\u6574\u7406<\/td><\/td>github<\/a><\/td><\/tr>
\u4e1c\u5357\u5927\u5b66\u300a\u77e5\u8bc6\u56fe\u8c31\u300b\u7814\u7a76\u751f\u8bfe\u7a0b(\u8d44\u6599)<\/td><\/td>github<\/a><\/td><\/tr>
\u77e5\u8bc6\u56fe\u8c31\u8f66\u97f3\u5de5\u4f5c\u9879\u76ee<\/td><\/td>github<\/a><\/td><\/tr>
\u300a\u6d77\u8d3c\u738b\u300b\u77e5\u8bc6\u56fe\u8c31<\/td><\/td>github<\/a><\/td><\/tr>
132\u4e2a\u77e5\u8bc6\u56fe\u8c31\u7684\u6570\u636e\u96c6<\/td>\u6db5\u76d6\u5e38\u8bc6\u3001\u57ce\u5e02\u3001\u91d1\u878d\u3001\u519c\u4e1a\u3001\u5730\u7406\u3001\u6c14\u8c61\u3001\u793e\u4ea4\u3001\u7269\u8054\u7f51\u3001\u533b\u7597\u3001\u5a31\u4e50\u3001\u751f\u6d3b\u3001\u5546\u4e1a\u3001\u51fa\u884c\u3001\u79d1\u6559<\/td>link<\/a><\/td><\/tr>
\u5927\u89c4\u6a21\u3001\u7ed3\u6784\u5316\u3001\u4e2d\u82f1\u6587\u53cc\u8bed\u7684\u65b0\u51a0\u77e5\u8bc6\u56fe\u8c31(COKG-19)<\/td><\/td>link<\/a><\/td><\/tr>
\u57fa\u4e8e\u4f9d\u5b58\u53e5\u6cd5\u4e0e\u8bed\u4e49\u89d2\u8272\u6807\u6ce8\u7684\u4e8b\u4ef6\u4e09\u5143\u7ec4\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
\u62bd\u8c61\u77e5\u8bc6\u56fe\u8c31<\/td>\u76ee\u524d\u89c4\u6a2150\u4e07\uff0c\u652f\u6301\u540d\u8bcd\u6027\u5b9e\u4f53\u3001\u72b6\u6001\u6027\u63cf\u8ff0\u3001\u4e8b\u4ef6\u6027\u52a8\u4f5c\u8fdb\u884c\u62bd\u8c61<\/td>github<\/a><\/td><\/tr>
\u5927\u89c4\u6a21\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31\u6570\u636e14\u4ebf\u5b9e\u4f53<\/td><\/td>github<\/a><\/td><\/tr>
Jiagu\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177<\/td>\u4ee5BiLSTM\u7b49\u6a21\u578b\u4e3a\u57fa\u7840\uff0c\u63d0\u4f9b\u77e5\u8bc6\u56fe\u8c31\u5173\u7cfb\u62bd\u53d6 \u4e2d\u6587\u5206\u8bcd \u8bcd\u6027\u6807\u6ce8 \u547d\u540d\u5b9e\u4f53\u8bc6\u522b \u60c5\u611f\u5206\u6790 \u65b0\u8bcd\u53d1\u73b0 \u5173\u952e\u8bcd \u6587\u672c\u6458\u8981 \u6587\u672c\u805a\u7c7b\u7b49\u529f\u80fd<\/td>github<\/a><\/td><\/tr>
medical_NER – \u4e2d\u6587\u533b\u5b66\u77e5\u8bc6\u56fe\u8c31\u547d\u540d\u5b9e\u4f53\u8bc6\u522b<\/td><\/td>github<\/a><\/td><\/tr>
\u77e5\u8bc6\u56fe\u8c31\u76f8\u5173\u5b66\u4e60\u8d44\u6599\/\u6570\u636e\u96c6\/\u5de5\u5177\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
LibKGE\u9762\u5411\u53ef\u590d\u73b0\u7814\u7a76\u7684\u77e5\u8bc6\u56fe\u8c31\u5d4c\u5165\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8emongodb\u5b58\u50a8\u7684\u519b\u4e8b\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u95ee\u7b54\u9879\u76ee<\/td>\u5305\u62ec\u98de\u884c\u5668\u3001\u592a\u7a7a\u88c5\u5907\u7b498\u5927\u7c7b\uff0c100\u4f59\u5c0f\u7c7b\uff0c\u5171\u8ba15800\u9879\u7684\u519b\u4e8b\u6b66\u5668\u77e5\u8bc6\u5e93\uff0c\u8be5\u9879\u76ee\u4e0d\u4f7f\u7528\u56fe\u6570\u636e\u5e93\u8fdb\u884c\u5b58\u50a8\uff0c\u901a\u8fc7jieba\u8fdb\u884c\u95ee\u53e5\u89e3\u6790\uff0c\u95ee\u53e5\u5b9e\u4f53\u9879\u8bc6\u522b\uff0c\u57fa\u4e8e\u67e5\u8be2\u6a21\u677f\u5b8c\u6210\u591a\u7c7b\u95ee\u9898\u7684\u67e5\u8be2\uff0c\u4e3b\u8981\u662f\u63d0\u4f9b\u4e00\u79cd\u5de5\u4e1a\u754c\u7684\u95ee\u7b54\u601d\u60f3demo\u3002<\/td>github<\/a><\/td><\/tr>
\u4eac\u4e1c\u5546\u54c1\u77e5\u8bc6\u56fe\u8c31<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u8fdc\u76d1\u7763\u7684\u4e2d\u6587\u5173\u7cfb\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u533b\u836f\u77e5\u8bc6\u56fe\u8c31\u7684\u667a\u80fd\u95ee\u7b54\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
BLINK\u6700\u5148\u8fdb\u7684\u5b9e\u4f53\u94fe\u63a5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u4e00\u4e2a\u5c0f\u578b\u7684\u8bc1\u5238\u77e5\u8bc6\u56fe\u8c31\/\u77e5\u8bc6\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
dstlr\u975e\u7ed3\u6784\u5316\u6587\u672c\u53ef\u6269\u5c55\u77e5\u8bc6\u56fe\u8c31\u6784\u5efa\u5e73\u53f0<\/td><\/td>github<\/a><\/td><\/tr>
\u767e\u5ea6\u767e\u79d1\u4eba\u7269\u8bcd\u6761\u5c5e\u6027\u62bd\u53d6<\/td>\u7528\u57fa\u4e8eBERT\u7684\u5fae\u8c03\u548c\u7279\u5f81\u63d0\u53d6\u65b9\u6cd5\u6765\u8fdb\u884c\u77e5\u8bc6\u56fe\u8c31<\/td>github<\/a><\/td><\/tr>
\u65b0\u51a0\u80ba\u708e\u76f8\u5173\u6570\u636e<\/td>\u65b0\u51a0\u53ca\u5176\u4ed6\u7c7b\u578b\u80ba\u708e\u4e2d\u6587\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6\uff1b\u6e05\u534e\u5927\u5b66\u7b49\u673a\u6784\u7684\u5f00\u653e\u6570\u636e\u6e90\uff08COVID-19\uff09<\/td>github<\/a>
github<\/a><\/td><\/tr>
DGL-KE \u56fe\u5d4c\u5165\u8868\u793a\u5b66\u4e60\u7b97\u6cd5<\/td><\/td>github<\/a><\/td><\/tr>
\u56e0\u679c\u5173\u7cfb\u56fe\u8c31<\/td><\/td>method<\/a> data<\/a><\/td><\/tr>
\u57fa\u4e8e\u591a\u9886\u57df\u6587\u672c\u6570\u636e\u96c6\u7684\u56e0\u679c\u4e8b\u4ef6\u5bf9<\/td><\/td>link<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u751f\u6210<\/h1>\n\n\n\n

<\/a><\/p>\n\n\n\n

\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Texar<\/td>Toolkit for Text Generation and Beyond<\/td>github<\/a><\/td><\/tr>
Ehud Reiter\u6559\u6388\u7684\u535a\u5ba2<\/td><\/td>link<\/a> \u5317\u5927\u4e07\u5c0f\u519b\u6559\u6388\u5f3a\u529b\u63a8\u8350\uff0c\u8be5\u535a\u5ba2\u5bf9NLG\u6280\u672f\u3001\u8bc4\u4ef7\u4e0e\u5e94\u7528\u8fdb\u884c\u4e86\u6df1\u5165\u7684\u63a2\u8ba8\u4e0e\u53cd\u601d\u3002<\/td><\/tr>
\u6587\u672c\u751f\u6210\u76f8\u5173\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u5f00\u653e\u57df\u5bf9\u8bdd\u751f\u6210\u53ca\u5728\u5fae\u8f6f\u5c0f\u51b0\u4e2d\u7684\u5b9e\u8df5<\/td>\u81ea\u7136\u8bed\u8a00\u751f\u6210\u8ba9\u673a\u5668\u638c\u63e1\u81ea\u52a8\u521b\u4f5c\u7684\u672c\u9886<\/td>link<\/a><\/td><\/tr>
\u6587\u672c\u751f\u6210\u63a7\u5236<\/td><\/td>github<\/a><\/td><\/tr>
\u81ea\u7136\u8bed\u8a00\u751f\u6210\u76f8\u5173\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u7528BLEURT\u8bc4\u4ef7\u81ea\u7136\u8bed\u8a00\u751f\u6210<\/td><\/td>link<\/a><\/td><\/tr>
\u81ea\u52a8\u5bf9\u8054\u6570\u636e\u53ca\u673a\u5668\u4eba<\/td><\/td>\u4ee3\u7801 link<\/a>
70\u4e07\u5bf9\u8054\u6570\u636e<\/a><\/td><\/tr>
\u81ea\u52a8\u751f\u6210\u8bc4\u8bba<\/td>\u7528Transformer\u7f16\u89e3\u7801\u6a21\u578b\u5b9e\u73b0\u7684\u6839\u636eHacker News\u6587\u7ae0\u6807\u9898\u751f\u6210\u8bc4\u8bba<\/td>github<\/a><\/td><\/tr>
\u81ea\u7136\u8bed\u8a00\u751f\u6210SQL\u8bed\u53e5\uff08\u82f1\u6587\uff09<\/td><\/td>github<\/a><\/td><\/tr>
\u81ea\u7136\u8bed\u8a00\u751f\u6210\u8d44\u6e90\u5927\u5168<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u751f\u6210\u4efb\u52a1\u57fa\u51c6\u6d4b\u8bc4<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eGPT2\u7684\u7279\u5b9a\u4e3b\u9898\u6587\u672c\u751f\u6210\/\u6587\u672c\u589e\u5e7f<\/td><\/td>github<\/a><\/td><\/tr>
\u7f16\u7801\u3001\u6807\u8bb0\u548c\u5b9e\u73b0\u4e00\u79cd\u53ef\u63a7\u9ad8\u6548\u7684\u6587\u672c\u751f\u6210\u65b9\u6cd5<\/td><\/td>github<\/a><\/td><\/tr>
TextFooler\u9488\u5bf9\u6587\u672c\u5206\u7c7b\/\u63a8\u7406\u7684\u5bf9\u6297\u6587\u672c\u751f\u6210\u6a21\u5757<\/td><\/td>github<\/a><\/td><\/tr>
SimBERT<\/td>\u57fa\u4e8eUniLM\u601d\u60f3\u3001\u878d\u68c0\u7d22\u4e0e\u751f\u6210\u4e8e\u4e00\u4f53\u7684BERT\u6a21\u578b<\/td>github<\/a><\/td><\/tr>
\u65b0\u8bcd\u751f\u6210\u53ca\u9020\u53e5<\/td>\u4e0d\u5b58\u5728\u7684\u8bcd\u7528GPT-2\u53d8\u4f53\u4ece\u5934\u751f\u6210\u65b0\u8bcd\u53ca\u5176\u5b9a\u4e49\u3001\u4f8b\u53e5<\/td>github<\/a><\/td><\/tr>
\u7531\u6587\u672c\u81ea\u52a8\u751f\u6210\u591a\u9879\u9009\u62e9\u9898<\/td><\/td>github<\/a><\/td><\/tr>
\u5408\u6210\u6570\u636e\u751f\u6210\u57fa\u51c6<\/td><\/td>github<\/a><\/td><\/tr>
<\/td><\/td><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u6458\u8981<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u6587\u672c\u6458\u8981\/\u5173\u952e\u8bcd\u63d0\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u7684\u7b80\u5386\u81ea\u52a8\u6458\u8981<\/td><\/td>github<\/a><\/td><\/tr>
\u6587\u672c\u81ea\u52a8\u6458\u8981\u5e93TextTeaser<\/td>\u4ec5\u652f\u6301\u82f1\u6587<\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eBERT\u7b49\u6700\u65b0\u8bed\u8a00\u6a21\u578b\u7684\u62bd\u53d6\u5f0f\u6458\u8981\u63d0\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
Python\u5229\u7528\u6df1\u5ea6\u5b66\u4e60\u8fdb\u884c\u6587\u672c\u6458\u8981\u7684\u7efc\u5408\u6307\u5357<\/td><\/td>link<\/a><\/td><\/tr>
(Colab)\u62bd\u8c61\u6587\u672c\u6458\u8981\u5b9e\u73b0\u96c6\u9526(\u6559\u7a0b<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u667a\u80fd\u95ee\u7b54<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u804a\u5929\u673a\u5668\u4eba<\/td>\u6839\u636e\u81ea\u5df1\u7684\u8bed\u6599\u8bad\u7ec3\u51fa\u81ea\u5df1\u60f3\u8981\u7684\u804a\u5929\u673a\u5668\u4eba\uff0c\u53ef\u4ee5\u7528\u4e8e\u667a\u80fd\u5ba2\u670d\u3001\u5728\u7ebf\u95ee\u7b54\u3001\u667a\u80fd\u804a\u5929\u7b49\u573a\u666f<\/td>github<\/a><\/td><\/tr>
\u6709\u8da3\u7684\u60c5\u8da3robot qingyun<\/td>qingyun \u8bad\u7ec3\u51fa\u6765\u7684\u4e2d\u6587\u804a\u5929\u673a\u5668\u4eba<\/td>github<\/a><\/td><\/tr>
\u5f00\u653e\u4e86\u5bf9\u8bdd\u673a\u5668\u4eba\u3001\u77e5\u8bc6\u56fe\u8c31\u3001\u8bed\u4e49\u7406\u89e3\u3001\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u53ca\u6570\u636e<\/td><\/td>github<\/a><\/td><\/tr>
qa\u5bf9\u7684\u673a\u5668\u4eba<\/td>Amodel-for-Retrivalchatbot – \u5ba2\u670d\u673a\u5668\u4eba\uff0cChinese Retreival chatbot\uff08\u4e2d\u6587\u68c0\u7d22\u5f0f\u673a\u5668\u4eba\uff09<\/td>git<\/a><\/td><\/tr>
ConvLab\u5f00\u6e90\u591a\u57df\u7aef\u5230\u7aef\u5bf9\u8bdd\u7cfb\u7edf\u5e73\u53f0<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u6700\u65b0\u7248\u672crasa\u642d\u5efa\u7684\u5bf9\u8bdd\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u91d1\u878d-\u53f8\u6cd5\u9886\u57df(\u517c\u6709\u95f2\u804a\u6027\u8d28)\u7684\u804a\u5929\u673a\u5668\u4eba<\/td><\/td>github<\/a><\/td><\/tr>
\u7aef\u5230\u7aef\u7684\u5c01\u95ed\u57df\u5bf9\u8bdd\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
MiningZhiDaoQACorpus<\/td>580\u4e07\u767e\u5ea6\u77e5\u9053\u95ee\u7b54\u6570\u636e\u6316\u6398\u9879\u76ee\uff0c\u767e\u5ea6\u77e5\u9053\u95ee\u7b54\u8bed\u6599\u5e93\uff0c\u5305\u62ec\u8d85\u8fc7580\u4e07\u7684\u95ee\u9898\uff0c\u6bcf\u4e2a\u95ee\u9898\u5e26\u6709\u95ee\u9898\u6807\u7b7e\u3002\u57fa\u4e8e\u8be5\u95ee\u7b54\u8bed\u6599\u5e93\uff0c\u53ef\u652f\u6301\u591a\u79cd\u5e94\u7528\uff0c\u5982\u903b\u8f91\u6316\u6398<\/td>github<\/a><\/td><\/tr>
\u7528\u4e8e\u4e2d\u6587\u95f2\u804a\u7684GPT2\u6a21\u578bGPT2-chitchat<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u68c0\u7d22\u804a\u5929\u673a\u5668\u4eba\u591a\u8f6e\u54cd\u5e94\u9009\u62e9\u76f8\u5173\u8d44\u6e90\u5217\u8868(Leaderboards\u3001Datasets\u3001Papers)<\/td><\/td>github<\/a><\/td><\/tr>
\u5fae\u8f6f\u5bf9\u8bdd\u673a\u5668\u4eba\u6846\u67b6<\/td><\/td>github<\/a><\/td><\/tr>
chatbot-list<\/td>\u884c\u4e1a\u5185\u5173\u4e8e\u667a\u80fd\u5ba2\u670d\u3001\u804a\u5929\u673a\u5668\u4eba\u7684\u5e94\u7528\u548c\u67b6\u6784\u3001\u7b97\u6cd5\u5206\u4eab\u548c\u4ecb\u7ecd<\/td>github<\/a><\/td><\/tr>
Chinese medical dialogue data \u4e2d\u6587\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e00\u4e2a\u5927\u89c4\u6a21\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6<\/td>\u5305\u542b110\u4e07\u533b\u5b66\u54a8\u8be2\uff0c400\u4e07\u6761\u533b\u60a3\u5bf9\u8bdd<\/td>github<\/a><\/td><\/tr>
\u5927\u89c4\u6a21\u8de8\u9886\u57df\u4e2d\u6587\u4efb\u52a1\u5bfc\u5411\u591a\u8f6e\u5bf9\u8bdd\u6570\u636e\u96c6\u53ca\u6a21\u578bCrossWOZ<\/td><\/td>paper & data<\/a><\/td><\/tr>
\u5f00\u6e90\u5bf9\u8bdd\u5f0f\u4fe1\u606f\u641c\u7d22\u5e73\u53f0<\/td><\/td>github<\/a><\/td><\/tr>
\u60c5\u5883\u4e92\u52a8\u591a\u6a21\u6001\u5bf9\u8bdd\u6311\u62182020(DSTC9 2020)<\/td><\/td>github<\/a><\/td><\/tr>
\u7528Quora\u95ee\u9898\u5bf9\u8bad\u7ec3\u7684T5\u95ee\u9898\u610f\u8bd1(Paraphrase)<\/td><\/td>github<\/a><\/td><\/tr>
Google\u53d1\u5e03Taskmaster-2\u81ea\u7136\u8bed\u8a00\u4efb\u52a1\u5bf9\u8bdd\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
Haystack\u7075\u6d3b\u3001\u5f3a\u5927\u7684\u53ef\u6269\u5c55\u95ee\u7b54(QA)\u6846\u67b6<\/td><\/td>github<\/a><\/td><\/tr>
\u7aef\u5230\u7aef\u7684\u5c01\u95ed\u57df\u5bf9\u8bdd\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
Amazon\u53d1\u5e03\u57fa\u4e8e\u77e5\u8bc6\u7684\u4eba-\u4eba\u5f00\u653e\u9886\u57df\u5bf9\u8bdd\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u767e\u5ea6webqa\u4e0edureader\u6570\u636e\u96c6\u8bad\u7ec3\u7684Albert Large QA\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
CommonsenseQA\u9762\u5411\u5e38\u8bc6\u7684\u82f1\u6587QA\u6311\u6218<\/td><\/td>link<\/a><\/td><\/tr>
MedQuAD(\u82f1\u6587)\u533b\u5b66\u95ee\u7b54\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eAlbert\u3001Electra\uff0c\u7528\u7ef4\u57fa\u767e\u79d1\u6587\u672c\u4f5c\u4e3a\u4e0a\u4e0b\u6587\u7684\u95ee\u7b54\u5f15\u64ce<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e14W\u6b4c\u66f2\u77e5\u8bc6\u5e93\u7684\u95ee\u7b54\u5c1d\u8bd5<\/td>\u529f\u80fd\u5305\u62ec\u6b4c\u8bcd\u63a5\u9f99\uff0c\u5df2\u77e5\u6b4c\u8bcd\u627e\u6b4c\u66f2\u4ee5\u53ca\u6b4c\u66f2\u6b4c\u624b\u6b4c\u8bcd\u4e09\u89d2\u5173\u7cfb\u7684\u95ee\u7b54<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u7ea0\u9519<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u6587\u672c\u7ea0\u9519\u6a21\u5757\u4ee3\u7801<\/td><\/td>github<\/a><\/td><\/tr>
\u82f1\u6587\u62fc\u5199\u68c0\u67e5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
python\u62fc\u5199\u68c0\u67e5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
GitHub Typo Corpus\u5927\u89c4\u6a21GitHub\u591a\u8bed\u8a00\u62fc\u5199\u9519\u8bef\/\u8bed\u6cd5\u9519\u8bef\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
BertPunc\u57fa\u4e8eBERT\u7684\u6700\u5148\u8fdb\u6807\u70b9\u4fee\u590d\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u5199\u4f5c\u6821\u5bf9\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u6587\u672c\u7ea0\u9519\u6587\u732e\u5217\u8868<\/td>Chinese Spell Checking (CSC) and Grammatical Error Correction (GEC)<\/td>github<\/a><\/td><\/tr>
\u6587\u672c\u667a\u80fd\u6821\u5bf9\u5927\u8d5b\u51a0\u519b\u65b9\u6848<\/td>\u5df2\u843d\u5730\u5e94\u7528\uff0c\u6765\u81ea\u82cf\u5dde\u5927\u5b66\u3001\u8fbe\u6469\u9662\u56e2\u961f<\/td>link<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u591a\u6a21\u6001<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u591a\u6a21\u6001\u6570\u636e\u96c6\u300c\u609f\u7a7a\u300d<\/td>\u534e\u4e3a\u8bfa\u4e9a\u65b9\u821f\u5b9e\u9a8c\u5ba4\u5f00\u6e90\u5927\u578b\uff0c\u5305\u542b1\u4ebf\u56fe\u6587\u5bf9<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u56fe\u6587\u8868\u5f81\u9884\u8bad\u7ec3\u6a21\u578bChinese-CLIP<\/td>\u4e2d\u6587\u7248\u672cCLIP\u9884\u8bad\u7ec3\u6a21\u578b\uff0c\u5f00\u6e90\u591a\u4e2a\u6a21\u578b\u89c4\u6a21\uff0c\u51e0\u884c\u4ee3\u7801\u641e\u5b9a\u4e2d\u6587\u56fe\u6587\u8868\u5f81\u63d0\u53d6 & \u56fe\u6587\u68c0\u7d22<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u8bed\u97f3\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
ASR \u8bed\u97f3\u6570\u636e\u96c6 + \u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u4e2d\u6587\u8bed\u97f3\u8bc6\u522b\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
\u6e05\u534e\u5927\u5b66THCHS30\u4e2d\u6587\u8bed\u97f3\u6570\u636e\u96c6<\/td><\/td>data_thchs30tgz-OpenSLR\u56fd\u5185\u955c\u50cf<\/a>
data_thchs30tgz<\/a>
test-noisetgz-OpenSLR\u56fd\u5185\u955c\u50cf<\/a>test-noisetgz<\/a>
resourcetgz-OpenSLR\u56fd\u5185\u955c\u50cf<\/a>
resourcetgz<\/a>
Free ST Chinese Mandarin Corpus<\/a>
Free ST Chinese Mandarin Corpus<\/a>
AIShell-1 \u5f00\u6e90\u7248\u6570\u636e\u96c6-OpenSLR\u56fd\u5185\u955c\u50cf<\/a>
AIShell-1 \u5f00\u6e90\u7248\u6570\u636e\u96c6<\/a>
Primewords Chinese Corpus Set 1-OpenSLR\u56fd\u5185\u955c\u50cf<\/a>
Primewords Chinese Corpus Set 1<\/a><\/td><\/tr>
\u7b11\u58f0\u68c0\u6d4b\u5668<\/td><\/td>github<\/a><\/td><\/tr>
Common Voice\u8bed\u97f3\u8bc6\u522b\u6570\u636e\u96c6\u65b0\u7248<\/td>\u5305\u62ec\u6765\u81ea42,000\u540d\u8d21\u732e\u8005\u8d85\u8fc71,400\u5c0f\u65f6\u7684\u8bed\u97f3\u6837\u672c\uff0c\u6db5github<\/td>link<\/a><\/td><\/tr>
speech-aligner<\/td>\u4ece\u201c\u4eba\u58f0\u8bed\u97f3\u201d\u53ca\u5176\u201c\u8bed\u8a00\u6587\u672c\u201d\uff0c\u4ea7\u751f\u97f3\u7d20\u7ea7\u522b\u65f6\u95f4\u5bf9\u9f50\u6807\u6ce8\u7684\u5de5\u5177<\/td>github<\/a><\/td><\/tr>
ASR\u8bed\u97f3\u5927\u8f9e\u5178\/\u8bcd\u5178<\/td><\/td>github<\/td><\/tr>
\u8bed\u97f3\u60c5\u611f\u5206\u6790<\/td><\/td>github<\/a><\/td><\/tr>
masr<\/td>\u4e2d\u6587\u8bed\u97f3\u8bc6\u522b\uff0c\u63d0\u4f9b\u9884\u8bad\u7ec3\u6a21\u578b\uff0c\u9ad8\u8bc6\u522b\u7387<\/td>github<\/a><\/td><\/tr>
\u9762\u5411\u8bed\u97f3\u8bc6\u522b\u7684\u4e2d\u6587\u6587\u672c\u89c4\u8303\u5316<\/td><\/td>github<\/a><\/td><\/tr>
\u8bed\u97f3\u8d28\u91cf\u8bc4\u4ef7\u6307\u6807(MOSNet, BSSEval, STOI, PESQ, SRMR)<\/td><\/td>github<\/a><\/td><\/tr>
\u9762\u5411\u8bed\u97f3\u8bc6\u522b\u7684\u4e2d\u6587\/\u82f1\u6587\u53d1\u97f3\u8f9e\u5178<\/td><\/td>github<\/a><\/td><\/tr>
CoVoSTFacebook\u53d1\u5e03\u7684\u591a\u8bed\u79cd\u8bed\u97f3-\u6587\u672c\u7ffb\u8bd1\u8bed\u6599\u5e93<\/td>\u5305\u62ec11\u79cd\u8bed\u8a00(\u6cd5\u8bed\u3001\u5fb7\u8bed\u3001\u8377\u5170\u8bed\u3001\u4fc4\u8bed\u3001\u897f\u73ed\u7259\u8bed\u3001\u610f\u5927\u5229\u8bed\u3001\u571f\u8033\u5176\u8bed\u3001\u6ce2\u65af\u8bed\u3001\u745e\u5178\u8bed\u3001\u8499\u53e4\u8bed\u548c\u4e2d\u6587)\u7684\u8bed\u97f3\u3001\u6587\u5b57\u8f6c\u5f55\u53ca\u82f1\u6587\u8bd1\u6587<\/td>github<\/a><\/td><\/tr>
Parakeet\u57fa\u4e8ePaddlePaddle\u7684\u6587\u672c-\u8bed\u97f3\u5408\u6210<\/td><\/td>github<\/a><\/td><\/tr>
(Java)\u51c6\u786e\u7684\u8bed\u97f3\u81ea\u7136\u8bed\u8a00\u68c0\u6d4b\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
CoVoSTFacebook\u53d1\u5e03\u7684\u591a\u8bed\u79cd\u8bed\u97f3-\u6587\u672c\u7ffb\u8bd1\u8bed\u6599\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
TensorFlow 2 \u5b9e\u73b0\u7684\u6587\u672c\u8bed\u97f3\u5408\u6210<\/td><\/td>github<\/a><\/td><\/tr>
Python\u97f3\u9891\u7279\u5f81\u63d0\u53d6\u5305<\/td><\/td>github<\/a><\/td><\/tr>
ViSQOL\u97f3\u9891\u8d28\u91cf\u611f\u77e5\u5ba2\u89c2\u3001\u5b8c\u6574\u53c2\u8003\u6307\u6807\uff0c\u5206\u97f3\u9891\u3001\u8bed\u97f3\u4e24\u79cd\u6a21\u5f0f<\/td><\/td>github<\/a><\/td><\/tr>
zhrtvc<\/td>\u597d\u7528\u7684\u4e2d\u6587\u8bed\u97f3\u514b\u9686\u517c\u4e2d\u6587\u8bed\u97f3\u5408\u6210\u7cfb\u7edf<\/td>github<\/a><\/td><\/tr>
aukit<\/td>\u597d\u7528\u7684\u8bed\u97f3\u5904\u7406\u5de5\u5177\u7bb1\uff0c\u5305\u542b\u8bed\u97f3\u964d\u566a\u3001\u97f3\u9891\u683c\u5f0f\u8f6c\u6362\u3001\u7279\u5f81\u9891\u8c31\u751f\u6210\u7b49\u6a21\u5757<\/td>github<\/a><\/td><\/tr>
phkit<\/td>\u597d\u7528\u7684\u97f3\u7d20\u5904\u7406\u5de5\u5177\u7bb1\uff0c\u5305\u542b\u4e2d\u6587\u97f3\u7d20\u3001\u82f1\u6587\u97f3\u7d20\u3001\u6587\u672c\u8f6c\u62fc\u97f3\u3001\u6587\u672c\u6b63\u5219\u5316\u7b49\u6a21\u5757<\/td>github<\/a><\/td><\/tr>
zhvoice<\/td>\u4e2d\u6587\u8bed\u97f3\u8bed\u6599\uff0c\u8bed\u97f3\u66f4\u52a0\u6e05\u6670\u81ea\u7136\uff0c\u5305\u542b8\u4e2a\u5f00\u6e90\u6570\u636e\u96c6\uff0c3200\u4e2a\u8bf4\u8bdd\u4eba\uff0c900\u5c0f\u65f6\u8bed\u97f3\uff0c1300\u4e07\u5b57<\/td>github<\/a><\/td><\/tr>
audio\u9762\u5411\u8bed\u97f3\u884c\u4e3a\u68c0\u6d4b<\/td>\u3001\u4e8c\u503c\u5316\u3001\u8bf4\u8bdd\u4eba\u8bc6\u522b\u3001\u81ea\u52a8\u8bed\u97f3\u8bc6\u522b\u3001\u60c5\u611f\u8bc6\u522b\u7b49\u4efb\u52a1\u7684\u97f3\u9891\u6807\u6ce8\u5de5\u5177<\/td>github<\/a><\/td><\/tr>
\u6df1\u5ea6\u5b66\u4e60\u60c5\u611f\u6587\u672c\u8bed\u97f3\u5408\u6210<\/td><\/td>github<\/a><\/td><\/tr>
Python\u97f3\u9891\u6570\u636e\u589e\u5e7f\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u5927\u89c4\u6a21\u97f3\u9891\u6570\u636e\u96c6Audioset\u7684\u97f3\u9891\u589e\u5f3a<\/td><\/td>github<\/a><\/td><\/tr>
\u8bed\u58f0\u8fc1\u79fb<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u6863\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
LayoutLM-v3\u6587\u6863\u7406\u89e3\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
PyLaia\u9762\u5411\u624b\u5199\u6587\u6863\u5206\u6790\u7684\u6df1\u5ea6\u5b66\u4e60\u5de5\u5177\u5305<\/td><\/td>github<\/a><\/td><\/tr>
\u5355\u6587\u6863\u975e\u76d1\u7763\u7684\u5173\u952e\u8bcd\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
DocSearch\u514d\u8d39\u6587\u6863\u641c\u7d22\u5f15\u64ce<\/td><\/td>github<\/a><\/td><\/tr>
fdfgen<\/td>\u80fd\u591f\u81ea\u52a8\u521b\u5efapdf\u6587\u6863\uff0c\u5e76\u586b\u5199\u4fe1\u606f<\/td>link<\/a><\/td><\/tr>
pdfx<\/td>\u81ea\u52a8\u62bd\u53d6\u51fa\u5f15\u7528\u53c2\u8003\u6587\u732e\uff0c\u5e76\u4e0b\u8f7d\u5bf9\u5e94\u7684pdf\u6587\u4ef6<\/td>link<\/a><\/td><\/tr>
invoice2data<\/td>\u53d1\u7968pdf\u4fe1\u606f\u62bd\u53d6<\/td>invoice2data<\/a><\/td><\/tr>
pdf\u6587\u6863\u4fe1\u606f\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
PDFMiner<\/td>PDFMiner\u80fd\u83b7\u53d6\u9875\u9762\u4e2d\u6587\u672c\u7684\u51c6\u786e\u4f4d\u7f6e\uff0c\u4ee5\u53ca\u5b57\u4f53\u6216\u884c\u7b49\u5176\u4ed6\u4fe1\u606f\u3002\u5b83\u8fd8\u6709\u4e00\u4e2aPDF\u8f6c\u6362\u5668\uff0c\u53ef\u4ee5\u5c06PDF\u6587\u4ef6\u8f6c\u6362\u6210\u5176\u4ed6\u6587\u672c\u683c\u5f0f(\u5982HTML)\u3002\u8fd8\u6709\u4e00\u4e2a\u53ef\u6269\u5c55\u7684\u89e3\u6790\u5668PDF\uff0c\u53ef\u4ee5\u7528\u4e8e\u6587\u672c\u5206\u6790\u4ee5\u5916\u7684\u5176\u4ed6\u7528\u9014\u3002<\/td>link<\/a><\/td><\/tr>
PyPDF2<\/td>PyPDF 2\u662f\u4e00\u4e2apython PDF\u5e93\uff0c\u80fd\u591f\u5206\u5272\u3001\u5408\u5e76\u3001\u88c1\u526a\u548c\u8f6c\u6362PDF\u6587\u4ef6\u7684\u9875\u9762\u3002\u5b83\u8fd8\u53ef\u4ee5\u5411PDF\u6587\u4ef6\u4e2d\u6dfb\u52a0\u81ea\u5b9a\u4e49\u6570\u636e\u3001\u67e5\u770b\u9009\u9879\u548c\u5bc6\u7801\u3002\u5b83\u53ef\u4ee5\u4ecePDF\u68c0\u7d22\u6587\u672c\u548c\u5143\u6570\u636e\uff0c\u8fd8\u53ef\u4ee5\u5c06\u6574\u4e2a\u6587\u4ef6\u5408\u5e76\u5728\u4e00\u8d77\u3002<\/td>link<\/a><\/td><\/tr>
PyPDF2<\/td>PyPDF 2\u662f\u4e00\u4e2apython PDF\u5e93\uff0c\u80fd\u591f\u5206\u5272\u3001\u5408\u5e76\u3001\u88c1\u526a\u548c\u8f6c\u6362PDF\u6587\u4ef6\u7684\u9875\u9762\u3002\u5b83\u8fd8\u53ef\u4ee5\u5411PDF\u6587\u4ef6\u4e2d\u6dfb\u52a0\u81ea\u5b9a\u4e49\u6570\u636e\u3001\u67e5\u770b\u9009\u9879\u548c\u5bc6\u7801\u3002\u5b83\u53ef\u4ee5\u4ecePDF\u68c0\u7d22\u6587\u672c\u548c\u5143\u6570\u636e\uff0c\u8fd8\u53ef\u4ee5\u5c06\u6574\u4e2a\u6587\u4ef6\u5408\u5e76\u5728\u4e00\u8d77\u3002<\/td>link<\/a><\/td><\/tr>
ReportLab<\/td>ReportLab\u80fd\u5feb\u901f\u521b\u5efaPDF \u6587\u6863\u3002\u7ecf\u8fc7\u65f6\u95f4\u8bc1\u660e\u7684\u3001\u8d85\u597d\u7528\u7684\u5f00\u6e90\u9879\u76ee\uff0c\u7528\u4e8e\u521b\u5efa\u590d\u6742\u7684\u3001\u6570\u636e\u9a71\u52a8\u7684PDF\u6587\u6863\u548c\u81ea\u5b9a\u4e49\u77e2\u91cf\u56fe\u5f62\u3002\u5b83\u662f\u514d\u8d39\u7684\uff0c\u5f00\u6e90\u7684\uff0c\u7528Python\u7f16\u5199\u7684\u3002\u8be5\u8f6f\u4ef6\u5305\u6bcf\u6708\u4e0b\u8f7d5\u4e07\u591a\u6b21\uff0c\u662f\u6807\u51c6Linux\u53d1\u884c\u7248\u7684\u4e00\u90e8\u5206\uff0c\u5d4c\u5165\u5230\u8bb8\u591a\u4ea7\u54c1\u4e2d\uff0c\u5e76\u88ab\u9009\u4e2d\u4e3aWikipedia\u7684\u6253\u5370\/\u5bfc\u51fa\u529f\u80fd\u63d0\u4f9b\u52a8\u529b\u3002<\/td>link<\/a><\/td><\/tr>
SIMPdfPython\u5199\u7684\u7b80\u5355PDF\u6587\u4ef6\u6587\u5b57\u7f16\u8f91\u5668<\/td><\/td>github<\/a><\/td><\/tr>
pdf-diff<\/td>PDF\u6587\u4ef6diff\u5de5\u5177 \u53ef\u663e\u793a\u4e24\u4e2apdf\u6587\u6863\u7684\u5dee\u522b<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u8868\u683c\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u7528unet\u5b9e\u73b0\u5bf9\u6587\u6863\u8868\u683c\u7684\u81ea\u52a8\u68c0\u6d4b\uff0c\u8868\u683c\u91cd\u5efa<\/td><\/td>github<\/a><\/td><\/tr>
pdftabextract<\/td>\u7528\u4e8eOCR\u8bc6\u522b\u540e\u7684\u8868\u683c\u4fe1\u606f\u89e3\u6790\uff0c\u5f88\u5f3a\u5927<\/td>link<\/a><\/td><\/tr>
tabula-py<\/td>\u76f4\u63a5\u5c06pdf\u4e2d\u7684\u8868\u683c\u4fe1\u606f\u8f6c\u6362\u4e3apandas\u7684dataframe\uff0c\u6709java\u548cpython\u4e24\u79cd\u7248\u672c\u4ee3\u7801<\/td><\/a><\/td><\/tr>
camelot<\/td>pdf\u8868\u683c\u89e3\u6790<\/td>link<\/a><\/td><\/tr>
pdfplumber<\/td>pdf\u8868\u683c\u89e3\u6790<\/td><\/a><\/td><\/tr>
PubLayNet<\/td>\u80fd\u591f\u5212\u5206\u6bb5\u843d\u3001\u8bc6\u522b\u8868\u683c\u3001\u56fe\u7247<\/td>link<\/a><\/td><\/tr>
\u4ece\u8bba\u6587\u4e2d\u63d0\u53d6\u8868\u683c\u6570\u636e<\/td><\/td>github<\/a><\/td><\/tr>
\u7528BERT\u5728\u8868\u683c\u4e2d\u5bfb\u627e\u7b54\u6848<\/td><\/td>github<\/a><\/td><\/tr>
\u8868\u683c\u95ee\u7b54\u7684\u7cfb\u5217\u6587\u7ae0<\/td><\/td>\u7b80\u4ecb<\/a>
\u6a21\u578b<\/a>
\u5b8c\u7ed3\u7bc7<\/a><\/td><\/tr>
\u4f7f\u7528GAN\u751f\u6210\u8868\u683c\u6570\u636e\uff08\u4ec5\u652f\u6301\u82f1\u6587\uff09<\/td><\/td>github<\/a><\/td><\/tr>
carefree-learn(PyTorch)<\/td>\u8868\u683c\u6570\u636e\u96c6\u81ea\u52a8\u5316\u673a\u5668\u5b66\u4e60(AutoML)\u5305<\/td>github<\/a><\/td><\/tr>
\u5c01\u95ed\u57df\u5fae\u8c03\u8868\u683c\u68c0\u6d4b<\/td><\/td>github<\/a><\/td><\/tr>
PDF\u8868\u683c\u6570\u636e\u63d0\u53d6\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
TaBERT\u7406\u89e3\u8868\u683c\u6570\u636e\u67e5\u8be2\u7684\u65b0\u6a21\u578b<\/td><\/td>paper<\/a><\/td><\/tr>
\u8868\u683c\u5904\u7406<\/td>Awesome-Table-Recognition<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u5339\u914d<\/h1>\n\n\n\n

<\/a><\/p>\n\n\n\n

\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u53e5\u5b50\u3001QA\u76f8\u4f3c\u5ea6\u5339\u914dMatchZoo<\/td>\u6587\u672c\u76f8\u4f3c\u5ea6\u5339\u914d\u7b97\u6cd5\u7684\u96c6\u5408\uff0c\u5305\u542b\u591a\u4e2a\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\uff0c\u503c\u5f97\u5c1d\u8bd5\u3002<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u95ee\u9898\u53e5\u5b50\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u6bd4\u8d5b\u53ca\u65b9\u6848\u6c47\u603b<\/td><\/td>github<\/a><\/td><\/tr>
similarity\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u5de5\u5177\u5305<\/td>java\u7f16\u5199,\u7528\u4e8e\u8bcd\u8bed\u3001\u77ed\u8bed\u3001\u53e5\u5b50\u3001\u8bcd\u6cd5\u5206\u6790\u3001\u60c5\u611f\u5206\u6790\u3001\u8bed\u4e49\u5206\u6790\u7b49\u76f8\u5173\u7684\u76f8\u4f3c\u5ea6\u8ba1\u7b97<\/td>github<\/a><\/td><\/tr>
\u4e2d\u6587\u8bcd\u8bed\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u65b9\u6cd5<\/td>\u7efc\u5408\u4e86\u540c\u4e49\u8bcd\u8bcd\u6797\u6269\u5c55\u7248\u4e0e\u77e5\u7f51\uff08Hownet\uff09\u7684\u8bcd\u8bed\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u65b9\u6cd5\uff0c\u8bcd\u6c47\u8986\u76d6\u66f4\u591a\u3001\u7ed3\u679c\u66f4\u51c6\u786e\u3002<\/td>gihtub<\/a><\/td><\/tr>
Python\u5b57\u7b26\u4e32\u76f8\u4f3c\u6027\u7b97\u6cd5\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8eSiamese bilstm\u6a21\u578b\u7684\u76f8\u4f3c\u53e5\u5b50\u5224\u5b9a\u6a21\u578b,\u63d0\u4f9b\u8bad\u7ec3\u6570\u636e\u96c6\u548c\u6d4b\u8bd5\u6570\u636e\u96c6<\/td>\u63d0\u4f9b\u4e8610\u4e07\u4e2a\u8bad\u7ec3\u6837\u672c<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u6570\u636e\u589e\u5f3a<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587NLP\u6570\u636e\u589e\u5f3a\uff08EDA\uff09\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u82f1\u6587NLP\u6570\u636e\u589e\u5f3a\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u4e00\u952e\u4e2d\u6587\u6570\u636e\u589e\u5f3a\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u6570\u636e\u589e\u5f3a\u5728\u673a\u5668\u7ffb\u8bd1\u53ca\u5176\u4ed6nlp\u4efb\u52a1\u4e2d\u7684\u5e94\u7528\u53ca\u6548\u679c<\/td><\/td>link<\/a><\/td><\/tr>
NLP\u6570\u636e\u589e\u5e7f\u8d44\u6e90\u96c6<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u5e38\u7528\u6b63\u5219\u8868\u8fbe\u5f0f<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u62bd\u53d6email\u7684\u6b63\u5219\u8868\u8fbe\u5f0f<\/td><\/td>\u5df2\u96c6\u6210\u5230 python package cocoNLP<\/a>\u4e2d\uff0c\u6b22\u8fce\u8bd5\u7528<\/td><\/tr>
\u62bd\u53d6phone_number<\/td><\/td>\u5df2\u96c6\u6210\u5230 python package cocoNLP<\/a>\u4e2d\uff0c\u6b22\u8fce\u8bd5\u7528<\/td><\/tr>
\u62bd\u53d6\u8eab\u4efd\u8bc1\u53f7\u7684\u6b63\u5219\u8868\u8fbe\u5f0f<\/td>IDCards_pattern = r’^([1-9]\\d{5}[12]\\d{3}(0[1-9]|1[012])(0[1-9]|[12][0-9]|3[01])\\d{3}[0-9xX])
IDs = re.findall(IDCards_pattern, text, flags=0)<\/td>		<\/td><\/tr>
IP\u5730\u5740\u6b63\u5219\u8868\u8fbe\u5f0f<\/td>(25[0-5]| 2[0-4]\\d| [0-1]\\d{2}| [1-9]?\\d).(25[0-5]| 2[0-4]\\d| [0-1]\\d{2}| [1-9]?\\d).(25[0-5]| 2[0-4]\\d| [0-1]\\d{2}| [1-9]?\\d).(25[0-5]| 2[0-4]\\d| [0-1]\\d{2}| [1-9]?\\d)<\/td><\/td><\/tr>
\u817e\u8bafQQ\u53f7\u6b63\u5219\u8868\u8fbe\u5f0f<\/td>[1-9]([0-9]{5,11})<\/td><\/td><\/tr>
\u56fd\u5185\u56fa\u8bdd\u53f7\u7801\u6b63\u5219\u8868\u8fbe\u5f0f<\/td>[0-9-()\uff08\uff09]{7,18}<\/td><\/td><\/tr>
\u7528\u6237\u540d\u6b63\u5219\u8868\u8fbe\u5f0f<\/td>[A-Za-z0-9_-\\u4e00-\\u9fa5]+<\/td><\/td><\/tr>
\u56fd\u5185\u7535\u8bdd\u53f7\u7801\u6b63\u5219\u5339\u914d\uff08\u4e09\u5927\u8fd0\u8425\u5546+\u865a\u62df\u7b49\uff09<\/td><\/td>github<\/a><\/td><\/tr>
\u6b63\u5219\u8868\u8fbe\u5f0f\u6559\u7a0b<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u68c0\u7d22<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u9ad8\u6548\u6a21\u7cca\u641c\u7d22\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u9762\u5411\u5404\u8bed\u79cd\/\u4efb\u52a1\u7684BERT\u6a21\u578b\u5927\u5217\u8868\/\u641c\u7d22\u5f15\u64ce<\/td><\/td>link<\/a><\/td><\/tr>
Deepmatch\u9488\u5bf9\u63a8\u8350\u3001\u5e7f\u544a\u548c\u641c\u7d22\u7684\u6df1\u5ea6\u5339\u914d\u6a21\u578b\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
wwsearch\u662f\u4f01\u4e1a\u5fae\u4fe1\u540e\u53f0\u81ea\u7814\u7684\u5168\u6587\u68c0\u7d22\u5f15\u64ce<\/td><\/td>github<\/a><\/td><\/tr>
aili – the fastest in-memory index in the East \u4e1c\u534a\u7403\u6700\u5feb\u5e76\u53d1\u7d22\u5f15<\/td><\/td>github<\/a><\/td><\/tr>
\u9ad8\u6548\u7684\u5b57\u7b26\u4e32\u5339\u914d\u5de5\u5177 RapidFuzz<\/td>a fast string matching library for Python and C++, which is using the string similarity calculations from FuzzyWuzzy<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u9605\u8bfb\u7406\u89e3<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u9ad8\u6548\u6a21\u7cca\u641c\u7d22\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u9762\u5411\u5404\u8bed\u79cd\/\u4efb\u52a1\u7684BERT\u6a21\u578b\u5927\u5217\u8868\/\u641c\u7d22\u5f15\u64ce<\/td><\/td>link<\/a><\/td><\/tr>
Deepmatch\u9488\u5bf9\u63a8\u8350\u3001\u5e7f\u544a\u548c\u641c\u7d22\u7684\u6df1\u5ea6\u5339\u914d\u6a21\u578b\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
allennlp\u9605\u8bfb\u7406\u89e3\u652f\u6301\u591a\u79cd\u6570\u636e\u548c\u6a21<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u60c5\u611f\u5206\u6790<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u65b9\u9762\u60c5\u611f\u5206\u6790\u5305<\/td><\/td>github<\/a><\/td><\/tr>
awesome-nlp-sentiment-analysis<\/td>\u60c5\u611f\u5206\u6790\u3001\u60c5\u7eea\u539f\u56e0\u8bc6\u522b\u3001\u8bc4\u4ef7\u5bf9\u8c61\u548c\u8bc4\u4ef7\u8bcd\u62bd\u53d6<\/td>github<\/a><\/td><\/tr>
\u60c5\u611f\u5206\u6790\u6280\u672f\u8ba9\u667a\u80fd\u5ba2\u670d\u66f4\u61c2\u4eba\u7c7b\u60c5\u611f<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u4e8b\u4ef6\u62bd\u53d6<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u4e8b\u4ef6\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
NLP\u4e8b\u4ef6\u63d0\u53d6\u6587\u732e\u8d44\u6e90\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
PyTorch\u5b9e\u73b0\u7684BERT\u4e8b\u4ef6\u62bd\u53d6(ACE 2005 corpus)<\/td><\/td>github<\/a><\/td><\/tr>
\u65b0\u95fb\u4e8b\u4ef6\u7ebf\u7d22\u62bd\u53d6<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u673a\u5668\u7ffb\u8bd1<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u65e0\u9053\u8bcd\u5178<\/td>\u6709\u9053\u8bcd\u5178\u7684\u547d\u4ee4\u884c\u7248\u672c\uff0c\u652f\u6301\u82f1\u6c49\u4e92\u67e5\u548c\u5728\u7ebf\u67e5\u8be2<\/td>github<\/a><\/td><\/tr>
NLLB<\/td>\u652f\u6301200+\u79cd\u8bed\u8a00\u4efb\u610f\u4e92\u8bd1\u7684\u8bed\u8a00\u6a21\u578bNLLB<\/td>link<\/a><\/td><\/tr>
Easy-Translate<\/td>\u5728\u672c\u5730\u7ffb\u8bd1\u5927\u6587\u672c\u6587\u4ef6\u7684\u811a\u672c\uff0c\u57fa\u4e8eFacebook\/Meta AI\u7684 M2M100\u6a21\u578b\u548cNLLB200\u6a21\u578b\uff0c\u652f\u6301200+\u79cd\u8bed\u8a00<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6570\u5b57\u8f6c\u6362<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u6700\u597d\u7684\u6c49\u5b57\u6570\u5b57(\u4e2d\u6587\u6570\u5b57)-\u963f\u62c9\u4f2f\u6570\u5b57\u8f6c\u6362\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u5feb\u901f\u8f6c\u5316\u300c\u4e2d\u6587\u6570\u5b57\u300d\u548c\u300c\u963f\u62c9\u4f2f\u6570\u5b57\u300d<\/td><\/td>github<\/a><\/td><\/tr>
\u5c06\u81ea\u7136\u8bed\u8a00\u6570\u5b57\u4e32\u89e3\u6790\u8f6c\u6362\u4e3a\u6574\u6570\u548c\u6d6e\u70b9\u6570<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6307\u4ee3\u6d88\u89e3<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u6307\u4ee3\u6d88\u89e3\u6570\u636e<\/td><\/td>github<\/a>
baidu ink<\/a> code a0qq<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u805a\u7c7b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
TextCluster\u77ed\u6587\u672c\u805a\u7c7b\u9884\u5904\u7406\u6a21\u5757 Short text cluster<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u5206\u7c7b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
NeuralNLP-NeuralClassifier\u817e\u8baf\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u6587\u672c\u5206\u7c7b\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u77e5\u8bc6\u63a8\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
GraphbrainAI\u5f00\u6e90\u8f6f\u4ef6\u5e93\u548c\u79d1\u7814\u5de5\u5177\uff0c\u76ee\u7684\u662f\u4fc3\u8fdb\u81ea\u52a8\u610f\u4e49\u63d0\u53d6\u548c\u6587\u672c\u7406\u89e3\u4ee5\u53ca\u77e5\u8bc6\u7684\u63a2\u7d22\u548c\u63a8\u65ad<\/td><\/td>github<\/a><\/td><\/tr>
(\u54c8\u4f5b)\u8bb2\u56e0\u679c\u63a8\u7406\u7684\u514d\u8d39\u4e66<\/td><\/td>pdf<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u53ef\u89e3\u91ca\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u6587\u672c\u673a\u5668\u5b66\u4e60\u6a21\u578b\u6700\u5148\u8fdb\u89e3\u91ca\u5668\u5e93<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u653b\u51fb<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
TextAttack\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6a21\u578b\u5bf9\u6297\u6027\u653b\u51fb\u6846\u67b6<\/td><\/td>github<\/a><\/td><\/tr>
OpenBackdoor: \u6587\u672c\u540e\u95e8\u653b\u9632\u5de5\u5177\u5305<\/td>OpenBackdoor\u57fa\u4e8ePython\u548cPyTorch\u5f00\u53d1\uff0c\u53ef\u7528\u4e8e\u590d\u73b0\u3001\u8bc4\u4f30\u548c\u5f00\u53d1\u6587\u672c\u540e\u95e8\u653b\u9632\u7684\u76f8\u5173\u7b97\u6cd5<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u53ef\u89c6\u5316<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Scattertext \u6587\u672c\u53ef\u89c6\u5316(python)<\/td><\/td>github<\/a><\/td><\/tr>
whatlies\u8bcd\u5411\u91cf\u4ea4\u4e92\u53ef\u89c6\u5316<\/td><\/td>spacy\u5de5\u5177<\/a><\/td><\/tr>
PySS3\u9762\u5411\u53ef\u89e3\u91caAI\u7684SS3\u6587\u672c\u5206\u7c7b\u5668\u673a\u5668\u53ef\u89c6\u5316\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u7528\u8bb0\u4e8b\u672c\u6e32\u67d33D\u56fe\u50cf<\/td><\/td>github<\/a><\/td><\/tr>
attnvisGPT2\u3001BERT\u7b49transformer\u8bed\u8a00\u6a21\u578b\u6ce8\u610f\u529b\u4ea4\u4e92\u53ef\u89c6\u5316<\/td><\/td>github<\/a><\/td><\/tr>
Texthero\u6587\u672c\u6570\u636e\u9ad8\u6548\u5904\u7406\u5305<\/td>\u5305\u62ec\u9884\u5904\u7406\u3001\u5173\u952e\u8bcd\u63d0\u53d6\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u5411\u91cf\u7a7a\u95f4\u5206\u6790\u3001\u6587\u672c\u53ef\u89c6\u5316\u7b49<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u6807\u6ce8\u5de5\u5177<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
NLP\u6807\u6ce8\u5e73\u53f0\u7efc\u8ff0<\/td><\/td>github<\/a><\/td><\/tr>
brat rapid annotation tool \u5e8f\u5217\u6807\u6ce8\u5de5\u5177<\/td><\/td>link<\/a><\/td><\/tr>
Poplar\u7f51\u9875\u7248\u81ea\u7136\u8bed\u8a00\u6807\u6ce8\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
LIDA\u8f7b\u91cf\u4ea4\u4e92\u5f0f\u5bf9\u8bdd\u6807\u6ce8\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
doccano\u57fa\u4e8e\u7f51\u9875\u7684\u5f00\u6e90\u534f\u540c\u591a\u8bed\u8a00\u6587\u672c\u6807\u6ce8\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
Datasaurai \u5728\u7ebf\u6570\u636e\u6807\u6ce8\u5de5\u4f5c\u6d41\u7ba1\u7406\u5de5\u5177<\/td><\/td>link<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u8bed\u8a00\u68c0\u6d4b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
langid<\/td>97\u79cd\u8bed\u8a00\u68c0\u6d4b<\/td>https:\/\/github.com\/saffsd\/langid.py<\/a><\/td><\/tr>
langdetect<\/td>\u8bed\u8a00\u68c0\u6d4b<\/td>https:\/\/code.google.com\/archive\/p\/language-detection\/<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u7efc\u5408\u5de5\u5177<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
jieba<\/td><\/td>jieba<\/a><\/td><\/tr>
hanlp<\/td><\/td>hanlp<\/a><\/td><\/tr>
nlp4han<\/td>\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u96c6(\u65ad\u53e5\/\u5206\u8bcd\/\u8bcd\u6027\u6807\u6ce8\/\u7ec4\u5757\/\u53e5\u6cd5\u5206\u6790\/\u8bed\u4e49\u5206\u6790\/NER\/N\u5143\u8bed\u6cd5\/HMM\/\u4ee3\u8bcd\u6d88\u89e3\/\u60c5\u611f\u5206\u6790\/\u62fc\u5199\u68c0<\/td>github<\/a><\/td><\/tr>
\u4ec7\u6068\u8a00\u8bba\u68c0\u6d4b\u8fdb\u5c55<\/td><\/td>link<\/a><\/td><\/tr>
\u57fa\u4e8ePytorch\u7684Bert\u5e94\u7528<\/td>\u5305\u62ec\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u60c5\u611f\u5206\u6790\u3001\u6587\u672c\u5206\u7c7b\u4ee5\u53ca\u6587\u672c\u76f8\u4f3c\u5ea6\u7b49<\/td>github<\/a><\/td><\/tr>
nlp4han\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u96c6<\/td>\u65ad\u53e5\/\u5206\u8bcd\/\u8bcd\u6027\u6807\u6ce8\/\u7ec4\u5757\/\u53e5\u6cd5\u5206\u6790\/\u8bed\u4e49\u5206\u6790\/NER\/N\u5143\u8bed\u6cd5\/HMM\/\u4ee3\u8bcd\u6d88\u89e3\/\u60c5\u611f\u5206\u6790\/\u62fc\u5199\u68c0\u67e5<\/td>github<\/a><\/td><\/tr>
\u4e00\u4e9b\u5173\u4e8e\u81ea\u7136\u8bed\u8a00\u7684\u57fa\u672c\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
\u7528BERT\u8fdb\u884c\u5e8f\u5217\u6807\u8bb0\u548c\u6587\u672c\u5206\u7c7b\u7684\u6a21\u677f\u4ee3\u7801<\/td><\/td>github<\/a><\/td><\/tr>
jieba_fast \u52a0\u901f\u7248\u7684jieba<\/td><\/td>github<\/a><\/td><\/tr>
StanfordNLP<\/td>\u7eafPython\u7248\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5305<\/td>link<\/a><\/td><\/tr>
Python\u53e3\u8bed\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u96c6(\u82f1\u6587)<\/td><\/td>github<\/a><\/td><\/tr>
PreNLP\u81ea\u7136\u8bed\u8a00\u9884\u5904\u7406\u5e93<\/td><\/td>github<\/a><\/td><\/tr>
nlp\u76f8\u5173\u7684\u4e00\u4e9b\u8bba\u6587\u53ca\u4ee3\u7801<\/td>\u5305\u62ec\u4e3b\u9898\u6a21\u578b\u3001\u8bcd\u5411\u91cf(Word Embedding)\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b(NER)\u3001\u6587\u672c\u5206\u7c7b(Text Classificatin)\u3001\u6587\u672c\u751f\u6210(Text Generation)\u3001\u6587\u672c\u76f8\u4f3c\u6027(Text Similarity)\u8ba1\u7b97\u7b49\uff0c\u6d89\u53ca\u5230\u5404\u79cd\u4e0enlp\u76f8\u5173\u7684\u7b97\u6cd5\uff0c\u57fa\u4e8ekeras\u548ctensorflow<\/td>github<\/a><\/td><\/tr>
Python\u6587\u672c\u6316\u6398\/NLP\u5b9e\u6218\u793a\u4f8b<\/td><\/td>github<\/a><\/td><\/tr>
Forte\u7075\u6d3b\u5f3a\u5927\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406pipeline\u5de5\u5177\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
stanza\u65af\u5766\u798f\u56e2\u961fNLP\u5de5\u5177<\/td>\u53ef\u5904\u7406\u516d\u5341\u591a\u79cd\u8bed\u8a00<\/td>github<\/a><\/td><\/tr>
Fancy-NLP\u7528\u4e8e\u5efa\u8bbe\u5546\u54c1\u753b\u50cf\u7684\u6587\u672c\u77e5\u8bc6\u6316\u6398\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u5168\u9762\u7b80\u4fbf\u7684\u4e2d\u6587 NLP \u5de5\u5177\u5305<\/td><\/td>github<\/a><\/td><\/tr>
\u5de5\u4e1a\u754c\u5e38\u7528\u57fa\u4e8eDSSM\u5411\u91cf\u5316\u53ec\u56depipeline\u590d\u73b0<\/td><\/td>github<\/a><\/td><\/tr>
Texthero\u6587\u672c\u6570\u636e\u9ad8\u6548\u5904\u7406\u5305<\/td>\u5305\u62ec\u9884\u5904\u7406\u3001\u5173\u952e\u8bcd\u63d0\u53d6\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u5411\u91cf\u7a7a\u95f4\u5206\u6790\u3001\u6587\u672c\u53ef\u89c6\u5316\u7b49<\/td>github<\/a><\/td><\/tr>
nlpgnn\u56fe\u795e\u7ecf\u7f51\u7edc\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u7bb1<\/td><\/td>github<\/a><\/td><\/tr>
Macadam<\/td>\u4ee5Tensorflow(Keras)\u548cbert4keras\u4e3a\u57fa\u7840\uff0c\u4e13\u6ce8\u4e8e\u6587\u672c\u5206\u7c7b\u3001\u5e8f\u5217\u6807\u6ce8\u548c\u5173\u7cfb\u62bd\u53d6\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u5305<\/td>github<\/a><\/td><\/tr>
LineFlow\u9762\u5411\u6240\u6709\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u7684NLP\u6570\u636e\u9ad8\u6548\u52a0\u8f7d\u5668<\/td><\/td>github<\/a><\/td><\/tr>
Arabica\uff1aPython\u6587\u672c\u6570\u636e\u63a2\u7d22\u6027\u5206\u6790\u5de5\u5177\u5305<\/td><\/td>github<\/a><\/td><\/tr>
Python \u538b\u529b\u6d4b\u8bd5\u5de5\u5177\uff1aSMSBoom<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6709\u8da3\u641e\u7b11\u5de5\u5177<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u6c6a\u5cf0\u6b4c\u8bcd\u751f\u6210\u5668<\/td><\/td>phunterlau\/wangfeng-rnn<\/a><\/td><\/tr>
\u5973\u53cb \u60c5\u611f\u6ce2\u52a8\u5206\u6790<\/td><\/td>github<\/a><\/td><\/tr>
NLP\u592a\u96be\u4e86\u7cfb\u5217<\/td><\/td>github<\/a><\/td><\/tr>
\u53d8\u91cf\u547d\u540d\u795e\u5668<\/td><\/td>github<\/a> link<\/a><\/td><\/tr>
\u56fe\u7247\u6587\u5b57\u53bb\u9664\uff0c\u53ef\u7528\u4e8e\u6f2b\u753b\u7ffb\u8bd1<\/td><\/td>github<\/a><\/td><\/tr>
CoupletAI – \u5bf9\u8054\u751f\u6210<\/td>\u57fa\u4e8eCNN+Bi-LSTM+Attention \u7684\u81ea\u52a8\u5bf9\u5bf9\u8054\u7cfb\u7edf<\/td>github<\/a><\/td><\/tr>
\u7528\u795e\u7ecf\u7f51\u7edc\u7b26\u53f7\u63a8\u7406\u6c42\u89e3\u590d\u6742\u6570\u5b66\u65b9\u7a0b<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e14W\u6b4c\u66f2\u77e5\u8bc6\u5e93\u7684\u95ee\u7b54\u673a\u5668\u4eba<\/td>\u529f\u80fd\u5305\u62ec\u6b4c\u8bcd\u63a5\u9f99\uff0c\u5df2\u77e5\u6b4c\u8bcd\u627e\u6b4c\u66f2\u4ee5\u53ca\u6b4c\u66f2\u6b4c\u624b\u6b4c\u8bcd\u4e09\u89d2\u5173\u7cfb\u7684\u95ee\u7b54<\/td>github<\/a><\/td><\/tr>
COPE – \u683c\u5f8b\u8bd7\u7f16\u8f91\u7a0b\u5e8f<\/td><\/td>github<\/a><\/td><\/tr>
Paper2GUI<\/td>\u4e00\u6b3e\u9762\u5411\u666e\u901a\u4eba\u7684AI\u684c\u9762APP\u5de5\u5177\u7bb1\uff0c\u514d\u5b89\u88c5\u5373\u5f00\u5373\u7528\uff0c\u5df2\u652f\u630118+AI\u6a21\u578b\uff0c\u5185\u5bb9\u6db5\u76d6\u8bed\u97f3\u5408\u6210\u3001\u89c6\u9891\u8865\u5e27\u3001\u89c6\u9891\u8d85\u5206\u3001\u76ee\u6807\u68c0\u6d4b\u3001\u56fe\u7247\u98ce\u683c\u5316\u3001OCR\u8bc6\u522b\u7b49\u9886\u57df<\/td>github<\/a><\/td><\/tr>
\u793c\u8c8c\u7a0b\u5ea6\u4f30\u7b97\u5668\uff08\u4f7f\u7528\u65b0\u6d6a\u5fae\u535a\u6570\u636e\u8bad\u7ec3\uff09<\/td><\/td>github<\/a> paper<\/a><\/td><\/tr>
\u8349\u87d2\uff08Python \u4e2d\u6587\u7248\uff09\u5165\u95e8\u6307\u5357<\/td>\u4e2d\u6587\u7f16\u7a0b\u8bed\u8a00<\/td>homepage<\/a> gitee<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u8bfe\u7a0b\u62a5\u544a\u9762\u8bd5\u7b49<\/a><\/h1>\n\n\n\n
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\u81ea\u52a8\u9a7e\u9a76\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u673a\u5668\u7ffb\u8bd1\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u533a\u5757\u94fe\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u673a\u5668\u4eba\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u8ba1\u7b97\u673a\u56fe\u5f62\u5b66\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
3D\u6253\u5370\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u4eba\u8138\u8bc6\u522b\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
\u4eba\u5de5\u667a\u80fd\u82af\u7247\u62a5\u544a<\/td><\/td>link<\/a><\/td><\/tr>
cs224n\u6df1\u5ea6\u5b66\u4e60\u81ea\u7136\u8bed\u8a00\u5904\u7406\u8bfe\u7a0b<\/td><\/td>link<\/a> \u8bfe\u7a0b\u4e2d\u6a21\u578b\u7684pytorch\u5b9e\u73b0 link<\/a><\/td><\/tr>
\u9762\u5411\u6df1\u5ea6\u5b66\u4e60\u7814\u7a76\u4eba\u5458\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5b9e\u4f8b\u6559\u7a0b<\/td><\/td>github<\/a><\/td><\/tr>
\u300aNatural Language Processing\u300bby Jacob Eisenstein<\/td><\/td>github<\/a><\/td><\/tr>
ML-NLP<\/td>\u673a\u5668\u5b66\u4e60(Machine Learning)\u3001NLP\u9762\u8bd5\u4e2d\u5e38\u8003\u5230\u7684\u77e5\u8bc6\u70b9\u548c\u4ee3\u7801\u5b9e\u73b0<\/td>github<\/a><\/td><\/tr>
NLP\u4efb\u52a1\u793a\u4f8b\u9879\u76ee\u4ee3\u7801\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
2019\u5e74NLP\u4eae\u70b9\u56de\u987e<\/td><\/td>download<\/a><\/td><\/tr>
nlp-recipes\u5fae\u8f6f\u51fa\u54c1–\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6700\u4f73\u5b9e\u8df5\u548c\u8303\u4f8b<\/td><\/td>github<\/a><\/td><\/tr>
\u9762\u5411\u6df1\u5ea6\u5b66\u4e60\u7814\u7a76\u4eba\u5458\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5b9e\u4f8b\u6559\u7a0b<\/td><\/td>github<\/a><\/td><\/tr>
Transfer Learning in Natural Language Processing (NLP)<\/td><\/td>youtube<\/a><\/td><\/tr>
\u300a\u673a\u5668\u5b66\u4e60\u7cfb\u7edf\u300b\u56fe\u4e66<\/td><\/td>link<\/a> github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6bd4\u8d5b<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
NLPer-Arsenal<\/td>NLP\u7ade\u8d5b\uff0c\u542b\u5f53\u524d\u8d5b\u4e8b\u4fe1\u606f\u3001\u8fc7\u5f80\u7ade\u8d5b\u65b9\u6848\u7b49\uff0c\u6301\u7eed\u66f4\u65b0\u4e2d<\/td>github<\/a><\/td><\/tr>
\u590d\u76d8\u6240\u6709NLP\u6bd4\u8d5b\u7684TOP\u65b9\u6848<\/td><\/td>github<\/a><\/td><\/tr>
2019\u5e74\u767e\u5ea6\u7684\u4e09\u5143\u7ec4\u62bd\u53d6\u6bd4\u8d5b\uff0c\u201c\u79d1\u5b66\u7a7a\u95f4\u961f\u201d\u6e90\u7801(\u7b2c7\u540d)<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u91d1\u878d\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
BDCI2019\u91d1\u878d\u8d1f\u9762\u4fe1\u606f\u5224\u5b9a<\/td><\/td>github<\/a><\/td><\/tr>
\u5f00\u6e90\u7684\u91d1\u878d\u6295\u8d44\u6570\u636e\u63d0\u53d6\u5de5\u5177<\/td><\/td>github<\/a><\/td><\/tr>
\u91d1\u878d\u9886\u57df\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7814\u7a76\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u91d1\u878d-\u53f8\u6cd5\u9886\u57df(\u517c\u6709\u95f2\u804a\u6027\u8d28)\u7684\u804a\u5929\u673a\u5668\u4eba<\/td><\/td>github<\/a><\/td><\/tr>
\u5c0f\u578b\u91d1\u878d\u77e5\u8bc6\u56fe\u8c31\u6784\u6d41\u7a0b\u793a\u8303<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u533b\u7597\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
\u4e2d\u6587\u533b\u5b66NLP\u516c\u5f00\u8d44\u6e90\u6574\u7406<\/td><\/td>github<\/a><\/td><\/tr>
spaCy \u533b\u5b66\u6587\u672c\u6316\u6398\u4e0e\u4fe1\u606f\u63d0\u53d6<\/td><\/td>github<\/a><\/td><\/tr>
\u6784\u5efa\u533b\u7597\u5b9e\u4f53\u8bc6\u522b\u7684\u6a21\u578b<\/td>\u5305\u542b\u8bcd\u5178\u548c\u8bed\u6599\u6807\u6ce8\uff0c\u57fa\u4e8epython<\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u533b\u7597\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u7684\u95ee\u7b54\u7cfb\u7edf<\/td><\/td>github<\/a> \u8be5repo\u53c2\u8003\u4e86github<\/a><\/td><\/tr>
Chinese medical dialogue data \u4e2d\u6587\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6<\/td><\/td>github<\/a><\/td><\/tr>
\u4e00\u4e2a\u5927\u89c4\u6a21\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6<\/td>\u5305\u542b110\u4e07\u533b\u5b66\u54a8\u8be2\uff0c400\u4e07\u6761\u533b\u60a3\u5bf9\u8bdd<\/td>github<\/a><\/td><\/tr>
\u65b0\u51a0\u80ba\u708e\u76f8\u5173\u6570\u636e<\/td>\u65b0\u51a0\u53ca\u5176\u4ed6\u7c7b\u578b\u80ba\u708e\u4e2d\u6587\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6\uff1b\u6e05\u534e\u5927\u5b66\u7b49\u673a\u6784\u7684\u5f00\u653e\u6570\u636e\u6e90\uff08COVID-19\uff09<\/td>github<\/a>
github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6cd5\u5f8b\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Blackstone\u9762\u5411\u975e\u7ed3\u6784\u5316\u6cd5\u5f8b\u6587\u672c\u7684spaCy pipeline\u548cNLP\u6a21\u578b<\/td><\/td>github<\/a><\/td><\/tr>
\u6cd5\u52a1\u667a\u80fd\u6587\u732e\u8d44\u6e90\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr>
\u57fa\u4e8e\u91d1\u878d-\u53f8\u6cd5\u9886\u57df(\u517c\u6709\u95f2\u804a\u6027\u8d28)\u7684\u804a\u5929\u673a\u5668\u4eba<\/td><\/td>github<\/a><\/td><\/tr>
\u7f6a\u540d\u6cd5\u52a1\u540d\u8bcd\u53ca\u5206\u7c7b\u6a21\u578b<\/td>\u5305\u542b856\u9879\u7f6a\u540d\u77e5\u8bc6\u56fe\u8c31, \u57fa\u4e8e280\u4e07\u7f6a\u540d\u8bad\u7ec3\u5e93\u7684\u7f6a\u540d\u9884\u6d4b,\u57fa\u4e8e20W\u6cd5\u52a1\u95ee\u7b54\u5bf9\u768413\u7c7b\u95ee\u9898\u5206\u7c7b\u4e0e\u6cd5\u5f8b\u8d44\u8baf\u95ee\u7b54\u529f\u80fd<\/td>github<\/a><\/td><\/tr>
\u6cd5\u5f8bNLP\u76f8\u5173\u8d44\u6e90\u5927\u5217\u8868<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u6587\u672c\u751f\u6210\u56fe\u50cf<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
Dalle-mini<\/td>\u6839\u636e\u6587\u672c\u63d0\u793a\u751f\u6210\u56fe\u7247\u7684\u8ff7\u4f60\u7248DALL\u00b7E<\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u5176\u4ed6<\/a><\/h1>\n\n\n\n
\u8d44\u6e90\u540d\uff08Name\uff09<\/th>\u63cf\u8ff0\uff08Description\uff09<\/th>\u94fe\u63a5<\/th><\/tr><\/thead>
phone<\/td>\u4e2d\u56fd\u624b\u673a\u5f52\u5c5e\u5730\u67e5\u8be2<\/td>ls0f\/phone<\/a><\/td><\/tr>
phone<\/td>\u56fd\u9645\u624b\u673a\u3001\u7535\u8bdd\u5f52\u5c5e\u5730\u67e5\u8be2<\/td>AfterShip\/phone<\/a><\/td><\/tr>
ngender<\/td>\u6839\u636e\u540d\u5b57\u5224\u65ad\u6027\u522b<\/td>observerss\/ngender<\/a><\/td><\/tr>
\u4e2d\u6587\u5bf9\u6bd4\u82f1\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406NLP\u7684\u533a\u522b\u7efc\u8ff0<\/td><\/td>link<\/a><\/td><\/tr>
\u5404\u5927\u516c\u53f8\u5185\u90e8\u91cc\u5927\u725b\u5206\u4eab\u7684\u6280\u672f\u6587\u6863 PDF \u6216\u8005 PPT<\/td><\/td>github<\/a><\/td><\/tr>
comparxiv \u7528\u4e8e\u6bd4\u8f83arXiv\u4e0a\u4e24\u63d0\u4ea4\u7248\u672c\u5dee\u5f02\u7684\u547d\u4ee4<\/td><\/td>pypi<\/a><\/td><\/tr>
CHAMELEON\u6df1\u5ea6\u5b66\u4e60\u65b0\u95fb\u63a8\u8350\u7cfb\u7edf\u5143\u67b6\u6784<\/td><\/td>github<\/a><\/td><\/tr>
\u7b80\u5386\u81ea\u52a8\u7b5b\u9009\u7cfb\u7edf<\/td><\/td>github<\/a><\/td><\/tr>
Python\u5b9e\u73b0\u7684\u591a\u79cd\u6587\u672c\u53ef\u8bfb\u6027\u8bc4\u4ef7\u6307\u6807<\/td><\/td>github<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

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