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troupe-standup/wizard-work/ledger/top-python-repos-2026-10-26.json

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News\u6587\u7ae0\u6807\u9898\u81ea\u52a8\u751f\u6210\u8bc4\u8bba\u3001\u7528BERT\u8fdb\u884c\u5e8f\u5217\u6807\u8bb0\u548c\u6587\u672c\u5206\u7c7b\u7684\u6a21\u677f\u4ee3\u7801\u3001LitBank\uff1aNLP\u6570\u636e\u96c6\u2014\u2014\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\u3001\u767e\u5ea6\u5f00\u6e90\u7684\u57fa\u51c6\u4fe1\u606f\u62bd\u53d6\u7cfb\u7edf\u3001\u865a\u5047\u65b0\u95fb\u6570\u636e\u96c6\u3001Facebook: LAMA\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\u3001CommonsenseQA\uff1a\u9762\u5411\u5e38\u8bc6\u7684\u82f1\u6587QA\u6311\u6218\u3001\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31\u8d44\u6599\u3001\u6570\u636e\u53ca\u5de5\u5177\u3001\u5404\u5927\u516c\u53f8\u5185\u90e8\u91cc\u5927\u725b\u5206\u4eab\u7684\u6280\u672f\u6587\u6863 PDF \u6216\u8005 PPT\u3001\u81ea\u7136\u8bed\u8a00\u751f\u6210SQL\u8bed\u53e5\uff08\u82f1\u6587\uff09\u3001\u4e2d\u6587NLP\u6570\u636e\u589e\u5f3a\uff08EDA\uff09\u5de5\u5177\u3001\u82f1\u6587NLP\u6570\u636e\u589e\u5f3a\u5de5\u5177 \u3001\u57fa\u4e8e\u533b\u836f\u77e5\u8bc6\u56fe\u8c31\u7684\u667a\u80fd\u95ee\u7b54\u7cfb\u7edf\u3001\u4eac\u4e1c\u5546\u54c1\u77e5\u8bc6\u56fe\u8c31\u3001\u57fa\u4e8emongodb\u5b58\u50a8\u7684\u519b\u4e8b\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u95ee\u7b54\u9879\u76ee\u3001\u57fa\u4e8e\u8fdc\u76d1\u7763\u7684\u4e2d\u6587\u5173\u7cfb\u62bd\u53d6\u3001\u8bed\u97f3\u60c5\u611f\u5206\u6790\u3001\u4e2d\u6587ULMFiT-\u60c5\u611f\u5206\u6790-\u6587\u672c\u5206\u7c7b-\u8bed\u6599\u53ca\u6a21\u578b\u3001\u4e00\u4e2a\u62cd\u7167\u505a\u9898\u7a0b\u5e8f\u3001\u4e16\u754c\u5404\u56fd\u5927\u89c4\u6a21\u4eba\u540d\u5e93\u3001\u4e00\u4e2a\u5229\u7528\u6709\u8da3\u4e2d\u6587\u8bed\u6599\u5e93 qingyun 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Learning)NLP\u9762\u8bd5\u4e2d\u5e38\u8003\u5230\u7684\u77e5\u8bc6\u70b9\u548c\u4ee3\u7801\u5b9e\u73b0\u3001nlp4han:\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\u67e5\u3001XLM\uff1aFacebook\u7684\u8de8\u8bed\u8a00\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u3001\u7528\u57fa\u4e8eBERT\u7684\u5fae\u8c03\u548c\u7279\u5f81\u63d0\u53d6\u65b9\u6cd5\u6765\u8fdb\u884c\u77e5\u8bc6\u56fe\u8c31\u767e\u5ea6\u767e\u79d1\u4eba\u7269\u8bcd\u6761\u5c5e\u6027\u62bd\u53d6\u3001\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u76f8\u5173\u7684\u5f00\u653e\u4efb\u52a1-\u6570\u636e\u96c6-\u5f53\u524d\u6700\u4f73\u7ed3\u679c\u3001CoupletAI - \u57fa\u4e8eCNN+Bi-LSTM+Attention \u7684\u81ea\u52a8\u5bf9\u5bf9\u8054\u7cfb\u7edf\u3001\u62bd\u8c61\u77e5\u8bc6\u56fe\u8c31\u3001MiningZhiDaoQACorpus - 580\u4e07\u767e\u5ea6\u77e5\u9053\u95ee\u7b54\u6570\u636e\u6316\u6398\u9879\u76ee\u3001brat rapid annotation tool: \u5e8f\u5217\u6807\u6ce8\u5de5\u5177\u3001\u5927\u89c4\u6a21\u4e2d\u6587\u77e5\u8bc6\u56fe\u8c31\u6570\u636e\uff1a1.4\u4ebf\u5b9e\u4f53\u3001\u6570\u636e\u589e\u5f3a\u5728\u673a\u5668\u7ffb\u8bd1\u53ca\u5176\u4ed6nlp\u4efb\u52a1\u4e2d\u7684\u5e94\u7528\u53ca\u6548\u679c\u3001allennlp\u9605\u8bfb\u7406\u89e3:\u652f\u6301\u591a\u79cd\u6570\u636e\u548c\u6a21\u578b\u3001PDF\u8868\u683c\u6570\u636e\u63d0\u53d6\u5de5\u5177 \u3001 Graphbrain\uff1aAI\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\u3001\u7b80\u5386\u81ea\u52a8\u7b5b\u9009\u7cfb\u7edf\u3001\u57fa\u4e8e\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u7684\u7b80\u5386\u81ea\u52a8\u6458\u8981\u3001\u4e2d\u6587\u8bed\u8a00\u7406\u89e3\u6d4b\u8bc4\u57fa\u51c6\uff0c\u5305\u62ec\u4ee3\u8868\u6027\u7684\u6570\u636e\u96c6&\u57fa\u51c6\u6a21\u578b&\u8bed\u6599\u5e93&\u6392\u884c\u699c\u3001\u6811\u6d1e OCR \u6587\u5b57\u8bc6\u522b \u3001\u4ece\u5305\u542b\u8868\u683c\u7684\u626b\u63cf\u56fe\u7247\u4e2d\u8bc6\u522b\u8868\u683c\u548c\u6587\u5b57\u3001\u8bed\u58f0\u8fc1\u79fb\u3001Python\u53e3\u8bed\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u96c6(\u82f1\u6587)\u3001 similarity\uff1a\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u5de5\u5177\u5305\uff0cjava\u7f16\u5199\u3001\u6d77\u91cf\u4e2d\u6587\u9884\u8bad\u7ec3ALBERT\u6a21\u578b \u3001Transformers 2.0 \u3001\u57fa\u4e8e\u5927\u89c4\u6a21\u97f3\u9891\u6570\u636e\u96c6Audioset\u7684\u97f3\u9891\u589e\u5f3a \u3001Poplar\uff1a\u7f51\u9875\u7248\u81ea\u7136\u8bed\u8a00\u6807\u6ce8\u5de5\u5177\u3001\u56fe\u7247\u6587\u5b57\u53bb\u9664\uff0c\u53ef\u7528\u4e8e\u6f2b\u753b\u7ffb\u8bd1 \u3001186\u79cd\u8bed\u8a00\u7684\u6570\u5b57\u53eb\u6cd5\u5e93\u3001Amazon\u53d1\u5e03\u57fa\u4e8e\u77e5\u8bc6\u7684\u4eba-\u4eba\u5f00\u653e\u9886\u57df\u5bf9\u8bdd\u6570\u636e\u96c6 \u3001\u4e2d\u6587\u6587\u672c\u7ea0\u9519\u6a21\u5757\u4ee3\u7801\u3001\u7e41\u7b80\u4f53\u8f6c\u6362 \u3001 Python\u5b9e\u73b0\u7684\u591a\u79cd\u6587\u672c\u53ef\u8bfb\u6027\u8bc4\u4ef7\u6307\u6807\u3001\u7c7b\u4f3c\u4e8e\u4eba\u540d/\u5730\u540d/\u7ec4\u7ec7\u673a\u6784\u540d\u7684\u547d\u540d\u4f53\u8bc6\u522b\u6570\u636e\u96c6 \u3001\u4e1c\u5357\u5927\u5b66\u300a\u77e5\u8bc6\u56fe\u8c31\u300b\u7814\u7a76\u751f\u8bfe\u7a0b(\u8d44\u6599)\u3001. \u82f1\u6587\u62fc\u5199\u68c0\u67e5\u5e93 \u3001 wwsearch\u662f\u4f01\u4e1a\u5fae\u4fe1\u540e\u53f0\u81ea\u7814\u7684\u5168\u6587\u68c0\u7d22\u5f15\u64ce\u3001CHAMELEON\uff1a\u6df1\u5ea6\u5b66\u4e60\u65b0\u95fb\u63a8\u8350\u7cfb\u7edf\u5143\u67b6\u6784 \u3001 8\u7bc7\u8bba\u6587\u68b3\u7406BERT\u76f8\u5173\u6a21\u578b\u8fdb\u5c55\u4e0e\u53cd\u601d\u3001DocSearch\uff1a\u514d\u8d39\u6587\u6863\u641c\u7d22\u5f15\u64ce\u3001 LIDA\uff1a\u8f7b\u91cf\u4ea4\u4e92\u5f0f\u5bf9\u8bdd\u6807\u6ce8\u5de5\u5177 \u3001aili - the fastest in-memory index in the East \u4e1c\u534a\u7403\u6700\u5feb\u5e76\u53d1\u7d22\u5f15 \u3001\u77e5\u8bc6\u56fe\u8c31\u8f66\u97f3\u5de5\u4f5c\u9879\u76ee\u3001\u81ea\u7136\u8bed\u8a00\u751f\u6210\u8d44\u6e90\u5927\u5168 \u3001\u4e2d\u65e5\u97e9\u5206\u8bcd\u5e93mecab\u7684Python\u63a5\u53e3\u5e93\u3001\u4e2d\u6587\u6587\u672c\u6458\u8981/\u5173\u952e\u8bcd\u63d0\u53d6\u3001\u6c49\u5b57\u5b57\u7b26\u7279\u5f81\u63d0\u53d6\u5668 (featurizer)\uff0c\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\u3001\u4e2d\u6587\u751f\u6210\u4efb\u52a1\u57fa\u51c6\u6d4b\u8bc4 \u3001\u4e2d\u6587\u7f29\u5199\u6570\u636e\u96c6\u3001\u4e2d\u6587\u4efb\u52a1\u57fa\u51c6\u6d4b\u8bc4 - \u4ee3\u8868\u6027\u7684\u6570\u636e\u96c6-\u57fa\u51c6(\u9884\u8bad\u7ec3)\u6a21\u578b-\u8bed\u6599\u5e93-baseline-\u5de5\u5177\u5305-\u6392\u884c\u699c\u3001PySS3\uff1a\u9762\u5411\u53ef\u89e3\u91caAI\u7684SS3\u6587\u672c\u5206\u7c7b\u5668\u673a\u5668\u53ef\u89c6\u5316\u5de5\u5177 \u3001\u4e2d\u6587NLP\u6570\u636e\u96c6\u5217\u8868\u3001COPE - \u683c\u5f8b\u8bd7\u7f16\u8f91\u7a0b\u5e8f\u3001doccano\uff1a\u57fa\u4e8e\u7f51\u9875\u7684\u5f00\u6e90\u534f\u540c\u591a\u8bed\u8a00\u6587\u672c\u6807\u6ce8\u5de5\u5177 \u3001PreNLP\uff1a\u81ea\u7136\u8bed\u8a00\u9884\u5904\u7406\u5e93\u3001\u7b80\u5355\u7684\u7b80\u5386\u89e3\u6790\u5668\uff0c\u7528\u6765\u4ece\u7b80\u5386\u4e2d\u63d0\u53d6\u5173\u952e\u4fe1\u606f\u3001\u7528\u4e8e\u4e2d\u6587\u95f2\u804a\u7684GPT2\u6a21\u578b\uff1aGPT2-chitchat\u3001\u57fa\u4e8e\u68c0\u7d22\u804a\u5929\u673a\u5668\u4eba\u591a\u8f6e\u54cd\u5e94\u9009\u62e9\u76f8\u5173\u8d44\u6e90\u5217\u8868(Leaderboards\u3001Datasets\u3001Papers)\u3001(Colab)\u62bd\u8c61\u6587\u672c\u6458\u8981\u5b9e\u73b0\u96c6\u9526(\u6559\u7a0b \u3001\u8bcd\u8bed\u62fc\u97f3\u6570\u636e\u3001\u9ad8\u6548\u6a21\u7cca\u641c\u7d22\u5de5\u5177\u3001NLP\u6570\u636e\u589e\u5e7f\u8d44\u6e90\u96c6\u3001\u5fae\u8f6f\u5bf9\u8bdd\u673a\u5668\u4eba\u6846\u67b6 \u3001 GitHub Typo Corpus\uff1a\u5927\u89c4\u6a21GitHub\u591a\u8bed\u8a00\u62fc\u5199\u9519\u8bef/\u8bed\u6cd5\u9519\u8bef\u6570\u636e\u96c6\u3001TextCluster\uff1a\u77ed\u6587\u672c\u805a\u7c7b\u9884\u5904\u7406\u6a21\u5757 Short text cluster\u3001\u9762\u5411\u8bed\u97f3\u8bc6\u522b\u7684\u4e2d\u6587\u6587\u672c\u89c4\u8303\u5316\u3001BLINK\uff1a\u6700\u5148\u8fdb\u7684\u5b9e\u4f53\u94fe\u63a5\u5e93\u3001BertPunc\uff1a\u57fa\u4e8eBERT\u7684\u6700\u5148\u8fdb\u6807\u70b9\u4fee\u590d\u6a21\u578b\u3001Tokenizer\uff1a\u5feb\u901f\u3001\u53ef\u5b9a\u5236\u7684\u6587\u672c\u8bcd\u6761\u5316\u5e93\u3001\u4e2d\u6587\u8bed\u8a00\u7406\u89e3\u6d4b\u8bc4\u57fa\u51c6\uff0c\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\u3001spaCy \u533b\u5b66\u6587\u672c\u6316\u6398\u4e0e\u4fe1\u606f\u63d0\u53d6 \u3001 NLP\u4efb\u52a1\u793a\u4f8b\u9879\u76ee\u4ee3\u7801\u96c6\u3001 python\u62fc\u5199\u68c0\u67e5\u5e93\u3001chatbot-list - \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\u3001\u8bed\u97f3\u8d28\u91cf\u8bc4\u4ef7\u6307\u6807(MOSNet, BSSEval, STOI, PESQ, SRMR)\u3001 \u7528138GB\u8bed\u6599\u8bad\u7ec3\u7684\u6cd5\u6587RoBERTa\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b \u3001BERT-NER-Pytorch\uff1a\u4e09\u79cd\u4e0d\u540c\u6a21\u5f0f\u7684BERT\u4e2d\u6587NER\u5b9e\u9a8c\u3001\u65e0\u9053\u8bcd\u5178 - \u6709\u9053\u8bcd\u5178\u7684\u547d\u4ee4\u884c\u7248\u672c\uff0c\u652f\u6301\u82f1\u6c49\u4e92\u67e5\u548c\u5728\u7ebf\u67e5\u8be2\u30012019\u5e74NLP\u4eae\u70b9\u56de\u987e\u3001 Chinese medical dialogue data \u4e2d\u6587\u533b\u7597\u5bf9\u8bdd\u6570\u636e\u96c6 \u3001\u6700\u597d\u7684\u6c49\u5b57\u6570\u5b57(\u4e2d\u6587\u6570\u5b57)-\u963f\u62c9\u4f2f\u6570\u5b57\u8f6c\u6362\u5de5\u5177\u3001 \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\u3001awesome-nlp-sentiment-analysis - \u60c5\u611f\u5206\u6790\u3001\u60c5\u7eea\u539f\u56e0\u8bc6\u522b\u3001\u8bc4\u4ef7\u5bf9\u8c61\u548c\u8bc4\u4ef7\u8bcd\u62bd\u53d6\u3001LineFlow\uff1a\u9762\u5411\u6240\u6709\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u7684NLP\u6570\u636e\u9ad8\u6548\u52a0\u8f7d\u5668\u3001\u4e2d\u6587\u533b\u5b66NLP\u516c\u5f00\u8d44\u6e90\u6574\u7406 \u3001MedQuAD\uff1a(\u82f1\u6587)\u533b\u5b66\u95ee\u7b54\u6570\u636e\u96c6\u3001\u5c06\u81ea\u7136\u8bed\u8a00\u6570\u5b57\u4e32\u89e3\u6790\u8f6c\u6362\u4e3a\u6574\u6570\u548c\u6d6e\u70b9\u6570\u3001Transfer Learning in Natural Language Processing (NLP) 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