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{
"prompts": {
"STS": "Retrieve semantically similar text.",
"BitextMining": "Retrieve translations of the following text.",
"Classification": "Classify the topic of the given text.",
"MultilabelClassification": "Classify the topic of the given text.",
"Clustering": "Classify the topic of the given text.",
"PairClassification": "Retrieve semantically entailed text.",
"query": "Given a question, retrieve passages that can help answer the question.",
"document": "",
"BulgarianStoreReviewSentimentClassfication": "Classify the sentiment of the given text.",
"CzechProductReviewSentimentClassification": "Classify the sentiment of the given text.",
"FinancialPhrasebankClassification": "Classify the sentiment of the given text.",
"PoemSentimentClassification": "Classify the sentiment of the given text.",
"EstonianValenceClassification": "Classify the sentiment of the given text.",
"FilipinoShopeeReviewsClassification": "Classify the sentiment of the given text.",
"SentimentAnalysisHindi": "Classify the sentiment of the given text.",
"KurdishSentimentClassification": "Classify the sentiment of the given text.",
"MacedonianTweetSentimentClassification": "Classify the sentiment of the given text.",
"AfriSentiClassification": "Classify the sentiment of the given text.",
"CataloniaTweetClassification": "Classify the sentiment of the given text.",
"MultiHateClassification": "Classify the sentiment of the given text.",
"NusaParagraphEmotionClassification": "Classify the sentiment of the given text.",
"NusaX-senti": "Classify the sentiment of the given text.",
"SwissJudgementClassification": "Classify the sentiment of the given text.",
"PolEmo2.0-OUT": "Classify the sentiment of the given text.",
"CSFDSKMovieReviewSentimentClassification": "Classify the sentiment of the given text.",
"SlovakMovieReviewSentimentClassification": "Classify the sentiment of the given text.",
"CyrillicTurkicLangClassification": "Classify the text into its language.",
"IndicLangClassification": "Classify the text into its language.",
"NordicLangClassification": "Classify the text into its language.",
"ScalaClassification": "Classify the given sentence as linguistically acceptable or not acceptable.",
"DalajClassification": "Classify the given sentence as linguistically acceptable or not acceptable.",
"ToxicConversationsClassification": "Classify the given comments as either toxic or not toxic.",
"IndonesianIdClickbaitClassification": "Classify the given text as either clickbait or not clickbait.",
"KorSarcasmClassification": "Classify the given text as either sarcasm or not sarcasm.",
"AmazonCounterfactualClassification": "Classify a given Amazon customer review text as either counterfactual or not counterfactual.",
"MassiveIntentClassification": "Given a user utterance as query, find the user intents.",
"PAC": "Classify the given clause as either abusive or not abusive.",
"Banking77Classification": "Given an online banking query, find the corresponding intents.",
"ImdbClassification": "Classify the sentiment expressed in the given movie review text from the IMDB dataset.",
"MTOPDomainClassification": "Classify the intent domain of the given utterance in task-oriented conversation.",
"MassiveScenarioClassification": "Given a user utterance as query, find the user scenarios.",
"TweetSentimentExtractionClassification": "Classify the sentiment of a given tweet as either positive, negative, or neutral",
"WikiCitiesClustering": "Classify the following city description by country.",
"ArXivHierarchicalClusteringP2P": "Identify the main and secondary category of arXiv papers based on the titles and abstracts.",
"ArXivHierarchicalClusteringS2S": "Identify the main and secondary category of arXiv papers based on the titles.",
"BiorxivClusteringP2P.v2": "Identify the main category of bioRxiv papers based on the titles and abstracts.",
"MedrxivClusteringP2P.v2": "Identify the main category of medRxiv papers based on the titles and abstracts.",
"StackExchangeClustering.v2": "Identify the topic or theme of StackExchange posts based on the titles.",
"StackExchangeClusteringP2P.v2": "Identify the topic or theme of StackExchange posts based on the given paragraphs.",
"MedrxivClusteringS2S.v2": "Identify the main category of medRxiv papers based on the titles.",
"TwentyNewsgroupsClustering.v2": "Identify the topic or theme of the given news articles.",
"SprintDuplicateQuestions": "Retrieve duplicate questions from Sprint forum.",
"TwitterURLCorpus": "Retrieve tweets that are semantically similar to the given tweet.",
"ArmenianParaphrasePC": "Retrieve paraphrases of the given sentence.",
"OpusparcusPC": "Retrieve paraphrases of the given sentence.",
"PawsXPairClassification": "Retrieve paraphrases of the given sentence.",
"PpcPC": "Retrieve paraphrases of the given sentence.",
"TwitterSemEval2015": "Retrieve tweets that are semantically similar to the given tweet.",
"KorHateSpeechMLClassification": "Classify the sentiment of the given text.",
"CEDRClassification": "Classify the emotion expressed in the given comment into: joy, sadness, surprise, fear, and anger.",
"SummEvalSummarization.v2": "Given a news summary, retrieve other semantically similar summaries.",
"AppsRetrieval": "Retrieve the most relevant code snippet for the given query.",
"CodeEditSearchRetrieval": "Retrieve the most relevant code edit.",
"CodeFeedbackMT": "Retrieve the most relevant response for the given query.",
"CodeFeedbackST": "Retrieve the most relevant response for the given query.",
"CodeSearchNetCCRetrieval": "Retrieve the most relevant code snippet for the given code snippet.",
"CodeSearchNetRetrieval": "Retrieve the most relevant code snippet for the given query.",
"CodeTransOceanContest": "Retrieve similar code to the given source code.",
"CodeTransOceanDL": "Retrieve similar code to the given source code.",
"CosQA": "Retrieve the most relevant code snippet for the given query.",
"COIRCodeSearchNetRetrieval": "Retrieve the most relevant code summary for the given code snippet.",
"StackOverflowQA": "Retrieve the most relevant response for the given query.",
"SyntheticText2SQL": "Retrieve the most relevant sql code snippet for the given query.",
"AILAStatutes": "Identify the most relevant statutes for the given situation.",
"ArguAna": "Given a claim, find documents that refute the claim.",
"LegalBenchCorporateLobbying": "Given a bill title, retrieve the corresponding bill summary.",
"SCIDOCS": "Given a scientific paper title, retrieve paper abstracts that are cited by the given paper.",
"TRECCOVID": "Given a query on COVID-19, retrieve documents that answer the query.",
"CovidRetrieval": "Given a query on COVID-19, retrieve documents that answer the query.",
"CQADupstackGamingRetrieval": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackUnixRetrieval": "Given a question, retrieve questions that are semantically equivalent.",
"ClimateFEVERHardNegatives": "Given a claim about climate change, retrieve documents that support or refute the claim.",
"FEVERHardNegatives": "Given a claim, retrieve documents that support or refute the claim.",
"FiQA2018": "Given a financial question, retrieve passages that answer the question.",
"HotpotQAHardNegatives": "Given a multi-hop question, retrieve passages that answer the question.",
"Touche2020Retrieval.v3": "Given a question, retrieve passages that answer the question.",
"WebLINXCandidatesReranking": "Given a web navigation step, retrieve relevant elements.",
"AskUbuntuDupQuestions": "Retrieve duplicate questions from AskUbuntu forum.",
"MindSmallReranking": "Retrieve relevant news articles based on user browsing history.",
"NFCorpus": "Given a question, retrieve passages that answer the question.",
"TRECCOVID-PL": "Given a query on COVID-19, retrieve documents that answer the query.",
"SciFact": "Given a scientific claim, retrieve passages that support or refute the claim.",
"SciFact-PL": "Given a scientific claim, retrieve passages that support or refute the claim.",
"CmedqaRetrieval": "Given a question, retrieve passages that answer the question.",
"CMedQAv2-reranking": "Given a question, retrieve passages that answer the question.",
"AngryTweetsClassification": "Classify the sentiment of the given text.",
"DanishPoliticalCommentsClassification": "Classify the sentiment of the given text.",
"DKHateClassification": "Classify the given comments as either offensive or not offensive.",
"LccSentimentClassification": "Classify the sentiment of the given text.",
"NoRecClassification": "Classify the sentiment of the given text.",
"NorwegianParliamentClassification": "Classify the sentiment of the given text.",
"SwedishSentimentClassification": "Classify the sentiment of the given text.",
"SweRecClassification": "Classify the sentiment of the given text.",
"DanFeverRetrieval": "Given a claim, retrieve documents that support or refute the claim.",
"SNLRetrieval": "Given a summary, retrieve the original article.",
"SwednRetrieval": "Given a summary, retrieve the original article.",
"TV2Nordretrieval": "Given a news summary, retrieve the original article.",
"BengaliSentimentAnalysis": "Classify the sentiment of the given text.",
"HindiDiscourseClassification": "Classify the given text into one of the five discourse modes: argumentative, narrative, descriptive, dialogic, and informative.",
"MTOPIntentClassification": "Classify the intent of the given utterance in task-oriented conversation.",
"TweetSentimentClassification": "Classify the sentiment of the given text.",
"UrduRomanSentimentClassification": "Classify the sentiment of the given text as either positive, negative, or neutral.",
"AmazonReviewsClassification": "Classify the given Amazon review into its appropriate rating category.",
"BlurbsClusteringP2P": "Classify the given book title and blurb into its genre.",
"BlurbsClusteringS2S": "Classify the given book title into its genre.",
"FalseFriendsGermanEnglish": "Retrieve translations of the following text.",
"XMarket": "Given a product name search, retrieve the corresponding product description.",
"GerDaLIR": "Retrieve documents that are referenced by the given text.",
"MLSUMClusteringP2P": "Classify the topic of the given news article.",
"SummEvalFr": "Given a news summary, retrieve other semantically similar summaries.",
"AllegroReviews": "Classify the sentiment of the given text.",
"CBD": "Classify the given text as either cyberbullying or not.",
"PolEmo2.0-IN": "Classify the sentiment of the given text.",
"PSC": "Retrieve semantically similar text.",
"EcomRetrieval": "Given a product name query, retrieve the corresponding product description.",
"MedicalRetrieval": "Retrieve the most relevant response for the given query.",
"VideoRetrieval": "Given a video search query, retrieve the titles of relevant videos.",
"CMedQAv1-reranking": "Retrieve the most relevant response for the given query.",
"Waimai": "Classify the sentiment of the given review as either positive or negative.",
"OnlineShopping": "Classify the sentiment of the given review as either positive or negative.",
"JDReview": "Classify the sentiment of the given review as either positive or negative.",
"MultilingualSentiment": "Classify the sentiment of the given review as either positive, negative, or neutral.",
"ToxicChatClassification": "Classify the given text as either toxic or not toxic.",
"JapaneseSentimentClassification": "Classify the sentiment of the given text.",
"WRIMEClassification": "Classify the sentiment of the given text.",
"NLPJournalTitleAbsRetrieval.V2": "Given a paper's title, retrieve the corresponding abstract.",
"NLPJournalTitleIntroRetrieval.V2": "Given a paper's title, retrieve the corresponding introduction.",
"NLPJournalAbsIntroRetrieval.V2": "Given a paper's abstract, retrieve the corresponding introduction.",
"NLPJournalAbsArticleRetrieval.V2": "Given a paper's abstract, retrieve the corresponding paper.",
"ESCIReranking": "Given a product name query, retrieve the corresponding product description.",
"DutchBookReviewSentimentClassification.v2": "Classify the sentiment of the given text.",
"VaccinChatNLClassification": "Classify the intent of the given utterance.",
"DutchColaClassification": "Classify the given sentence as linguistically acceptable or not acceptable.",
"DutchGovernmentBiasClassification": "Classify the given government document as biased or unbiased.",
"DutchSarcasticHeadlinesClassification": "Classify the given newspaper headline as sarcastic or not sarcastic.",
"XLWICNLPairClassification": "Retrieve semantically similar text.",
"CovidDisinformationNLMultiLabelClassification": "Classify the given social media post related to COVID-19 into its misinformation category.",
"VABBClusteringS2S": "Identify the main category of the given paper based on the title.",
"VABBClusteringP2P": "Identify the main category of the given paper based on the title and abstract.",
"ArguAna-NL.v2": "Given a claim, find documents that refute the claim.",
"SCIDOCS-NL.v2": "Given a scientific paper title, retrieve paper abstracts that are cited by the given paper.",
"SciFact-NL.v2": "Given a scientific claim, retrieve passages that support or refute the claim.",
"DutchNewsArticlesRetrieval": "Given a news title, retrieve the original article.",
"OpenTenderRetrieval": "Given a title, retrieve the corresponding article.",
"VABBRetrieval": "Given a paper's title, retrieve the corresponding abstract.",
"GeoreviewClassification": "Classify the given review into its appropriate rating category.",
"InappropriatenessClassification": "Classify the given message as either sensitive topic or not.",
"KinopoiskClassification": "Classify the sentiment of the given movie review.",
"RuReviewsClassification": "Classify the sentiment of the given review as either positive, negative, or neutral.",
"RuSciBenchGRNTIClassification": "Identify the main category of the given paper based on the title and abstract.",
"RuSciBenchOECDClassification": "Identify the main category of the given paper based on the title and abstract.",
"GeoreviewClusteringP2P": "Identify the organization category based on the given review.",
"RuSciBenchGRNTIClusteringP2P": "Identify the main category of the given paper based on the title and abstract.",
"RuSciBenchOECDClusteringP2P": "Identify the main category of the given paper based on the title and abstract.",
"SensitiveTopicsClassification": "Classify the given text into sensitive topics.",
"RiaNewsRetrievalHardNegatives.v2": "Given a news title, retrieve the original article.",
"PersianFoodSentimentClassification": "Classify the sentiment of the given text as either positive or negative.",
"SynPerChatbotConvSAClassification": "Classify the sentiment of the given text.",
"SynPerChatbotConvSAToneChatbotClassification": "Classify the sentiment of the given text.",
"SynPerChatbotConvSAToneUserClassification": "Classify the sentiment of the given text.",
"SynPerChatbotSatisfactionLevelClassification": "Classify the satisfaction level of the given text.",
"SynPerTextToneClassification.v3": "Classify the tone of the given text.",
"DeepSentiPers.v2": "Classify the sentiment of the given text.",
"PersianTextEmotion.v2": "Classify the emotion expressed in the given text into: joy, sadness, surprise, fear, anger, and love.",
"StyleClassification": "Classify the style of the given text as either formal or informal.",
"PerShopDomainClassification": "Classify the domain of the given utterance in shopping dialogue.",
"PerShopIntentClassification": "Classify the intent of the given utterance in shopping dialogue.",
"SynPerChatbotRAGFAQPC": "Retrieve the most relevant response for the given query.",
"FarsiParaphraseDetection": "Retrieve semantically similar text.",
"SynPerTextKeywordsPC": "Identify keywords in the given text.",
"SynPerQAPC": "Retrieve the most relevant response for the given query.",
"ParsinluQueryParaphPC": "Retrieve semantically similar text.",
"SynPerChatbotRAGFAQRetrieval": "Retrieve the most relevant response for the given query.",
"HotpotQA-FaHardNegatives": "Given a multi-hop question, retrieve passages that answer the question.",
"ArguAna-Fa.v2": "Given a claim, find documents that refute the claim.",
"QuoraRetrieval-Fa.v2": "Retrieve questions that are semantically equivalent to the given one.",
"SCIDOCS-Fa.v2": "Given a scientific paper title, retrieve paper abstracts that are cited by the given paper.",
"SciFact-Fa.v2": "Given a scientific claim, retrieve passages that support or refute the claim.",
"TRECCOVID-Fa.v2": "Given a query on COVID-19, retrieve documents that answer the query.",
"FEVER-FaHardNegatives": "Given a claim, retrieve documents that support or refute the claim.",
"SAMSumFa": "Retrieve the most relevant summary for the given conversation.",
"SynPerChatbotSumSRetrieval": "Retrieve the most relevant summary for the given conversation.",
"SynPerChatbotRAGSumSRetrieval": "Retrieve the most relevant summary for the given conversation.",
"ArguAna-VN": "Given a claim, find documents that refute the claim.",
"SciFact-VN": "Given a scientific claim, retrieve passages that support or refute the claim.",
"ClimateFEVER-VN": "Given a claim about climate change, retrieve documents that support or refute the claim.",
"FEVER-VN": "Given a claim, retrieve documents that support or refute the claim.",
"DBPedia-VN": "Given a query, retrieve relevant entity descriptions.",
"HotpotQA-VN": "Given a multi-hop question, retrieve passages that answer the question.",
"TRECCOVID-VN": "Given a query on COVID-19, retrieve documents that answer the query.",
"SCIDOCS-VN": "Given a scientific paper title, retrieve paper abstracts that are cited by the given paper.",
"Quora-VN": "Retrieve questions that are semantically equivalent to the given one.",
"CQADupstackAndroid-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackGis-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackMathematica-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackPhysics-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackProgrammers-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackStats-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackTex-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackUnix-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackWebmasters-VN": "Given a question, retrieve questions that are semantically equivalent.",
"CQADupstackWordpress-VN": "Given a question, retrieve questions that are semantically equivalent.",
"Banking77VNClassification": "Given an online banking query, find the corresponding intents.",
"EmotionVNClassification": "Classify the emotion expressed in the given Twitter message into one of the six emotions: anger, fear, joy, love, sadness, and surprise.",
"AmazonCounterfactualVNClassification": "Classify a given Amazon customer review text as either counterfactual or not counterfactual.",
"MTOPDomainVNClassification": "Classify the intent domain of the given utterance in task-oriented conversation.",
"TweetSentimentExtractionVNClassification": "Classify the sentiment of a given tweet as either positive, negative, or neutral",
"ToxicConversationsVNClassification": "Classify the given comments as either toxic or not toxic.",
"ImdbVNClassification": "Classify the sentiment expressed in the given movie review text from the IMDB dataset.",
"MTOPIntentVNClassification": "Classify the intent of the given utterance in task-oriented conversation.",
"MassiveScenarioVNClassification": "Given a user utterance as query, find the user scenarios.",
"MassiveIntentVNClassification": "Given a user utterance as query, find the user intents.",
"AmazonReviewsVNClassification": "Classify the given Amazon review into its appropriate rating category.",
"AmazonPolarityVNClassification": "Classify the given Amazon review as either positive or negative.",
"SprintDuplicateQuestions-VN": "Retrieve duplicate questions from Sprint forum.",
"TwitterSemEval2015-VN": "Retrieve tweets that are semantically similar to the given tweet.",
"TwitterURLCorpus-VN": "Retrieve tweets that are semantically similar to the given tweet.",
"TwentyNewsgroupsClustering-VN": "Identify the topic or theme of the given news articles.",
"RedditClusteringP2P-VN": "Identify the topic or theme of Reddit posts based on the titles and posts.",
"StackExchangeClusteringP2P-VN": "Identify the topic or theme of StackExchange posts based on the given titles and paragraphs.",
"StackExchangeClustering-VN": "Identify the topic or theme of StackExchange posts based on the titles.",
"RedditClustering-VN": "Identify the topic or theme of Reddit posts based on the titles.",
"SciDocsRR-VN": "Given a title of a scientific paper, retrieve the titles of other relevant papers.",
"AskUbuntuDupQuestions-VN": "Retrieve duplicate questions from AskUbuntu forum.",
"StackOverflowDupQuestions-VN": "Retrieve duplicate questions from StackOverflow forum."
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
}
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