task_id large_string | slug large_string | definition large_string | categories list | domains list | source list | reasoning list | input_language list | output_language list | instruction_language list | contributors list | positive_examples large_string | negative_examples large_string | lora_path large_string | dataset_path large_string | description_short large_string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1246 | task1246_ted_translation_gl_pt | You are given a sentence in Galician. Your job is to translate the Galician sentence into Portugese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"Portuguese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "A Mi\u00f1a esperanza \u00e9 que a beleza e prop\u00f3sito deste universo microsc\u00f3pico poida inspirar enfoques novos e creativos na investigaci\u00f3n do cancro.", "output": "No final, espero que a beleza e prop\u00f3sito deste universo microsc\u00f3pico inspire novas e criativas abordagens no futuro d... | [{"input": "Xa sabedes, se \u00eda a un partido de rugby ga\u00f1ar\u00edamos n\u00f3s.", "output": "Como as pessoas podiam tirar fotos dos seus telem\u00f3veis do que estava acontecendo nas urnas, foi imposs\u00edvel para o Primeiro Ministro viciar aquela elei\u00e7\u00e3o da maneira que ele queria.", "explanation": "... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1246 | https://huggingface.co/datasets/Lots-of-LoRAs/task1246_ted_translation_gl_pt | ted translation gl pt |
1662 | task1662_cedr_ru_classification | You will be given a text in the Russian language, and you should classify the given input text to one of the emotion labels from this list of emotion labels- ['joy', 'sadness', 'surprise', 'fear', 'anger']. Make sure your output label (i) is strictly present in the given list of emotion labels. (ii) is unambiguous. | [
"Sentiment Analysis"
] | [
"Social Media"
] | [
"cedr"
] | [] | [
"Russian"
] | [
"English"
] | [
"English"
] | [
"Saradhi Kiran Amarthi"
] | [{"input": "\u041a\u043e\u043c\u0443 \u043e\u043d\u0438 \u0442\u0430\u043a \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b, \u044d\u0442\u0438 \u0441\u0442\u0440\u0430\u0434\u0430\u043d\u0438\u044f?\u00bb \u0410 \u0443 \u043c\u0435\u043d\u044f \u0441\u043f\u0438\u043d\u0430 \u0431\u043e\u043b\u0438\u0442, ... | [{"input": "\u041c\u044b \u0432 \u0443\u0436\u0430\u0441\u0435 \u043e\u0442 \u0442\u043e\u0433\u043e, \u0447\u0442\u043e \u043d\u0430 \u044d\u0442\u043e\u0442 \u0440\u0430\u0437 \u0431\u044b\u043b \u0443\u0431\u0438\u0442 \u0447\u0435\u043b\u043e\u0432\u0435\u043a.", "output": "anger", "explanation": "The input text st... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1662 | https://huggingface.co/datasets/Lots-of-LoRAs/task1662_cedr_ru_classification | cedr ru classification |
293 | task293_storycommonsense_emotion_text_generation | In this task, you're given a context, a sentence, and a character. The sentence describes an action or job of the given character. Also, the context provides more information about the sentence or the character. Your task is to return one of the emotions which are expressed by the Character in the given sentence. For ... | [
"Sentiment Analysis"
] | [
"Story"
] | [
"storycommonsense"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mirali Purohit"
] | [{"input": "Context: A cook was carrying an armful of oranged in the kitchen. \n Sentence: He dropped one on the floor by accident. \n Character: Cook", "output": "annoyed", "explanation": "The cook dropped one orange on the floor, so, he must feel annoyed at that time."}, {"input": "Context: None \n Sentence: Valerie ... | [{"input": "Context: A cook was carrying an armful of oranged in the kitchen. \n Sentence: He dropped one on the floor by accident. \n Character: Cook", "output": "productive", "explanation": "After dropping orange, cook must be angry at himself or annoyed, disgusted. However, productive is not correct answer."}, {"inp... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task293 | https://huggingface.co/datasets/Lots-of-LoRAs/task293_storycommonsense_emotion_text_generation | storycommonsense emotion text generation |
1544 | task1544_conll2002_named_entity_recognition_answer_generation | In this task, you will be presented with a question in Dutch language, and you have to write the named entities from the question if present. B denotes the first item of a phrase and an I any non-initial word. Here is the list of terms used: person names (PER), organizations (ORG), locations (LOC) and miscellaneous nam... | [
"Named Entity Recognition"
] | [
"Miscellaneous"
] | [
"conll2022"
] | [] | [
"Dutch"
] | [
"Dutch",
"English"
] | [
"English"
] | [
"Manikanta Ellenki"
] | [{"input": "En daarom wordt er in Changli nu aan een nieuwe kerk gebouwd.", "output": "Changli: B-LOC", "explanation": "In the given sentence, Changli is identified as the location entity."}, {"input": "71 concerten tijdens Marktrock in Leuven", "output": "Marktrock: B-MISC, Leuven: B-LOC", "explanation": "In this sent... | [{"input": "Het graf van Pu shenfu ziet er niet uit alsof het ruim vijftig jaar oud is.", "output": "Pu: B-PER, shenfu: I-LOC", "explanation": "In the given sentence, shenfu is identified as the location instead of the person entity."}, {"input": "Galatasaray heeft op de transfermarkt enkele kleppers gestrikt.", "outpu... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1544 | https://huggingface.co/datasets/Lots-of-LoRAs/task1544_conll2002_named_entity_recognition_answer_generation | conll2002 named entity recognition answer generation |
1235 | task1235_ted_translation_he_ja | You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Japanese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Hebrew"
] | [
"Japanese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u05de\u05d4 \u05de\u05d9\u05d9\u05d7\u05d3 \u05d0\u05ea \u05d4\u05de\u05d5\u05d7 \u05d4\u05d0\u05e0\u05d5\u05e9\u05d9?", "output": "\u4eba\u306e\u8133\u306e\u4f55\u304c\u305d\u3093\u306a\u306b\u7279\u5225\u306a\u306e\u3067\u3057\u3087\u3046\u304b \uff1f", "explanation": "The Hebrew sentence is correctly tr... | [{"input": "\u05de\u05d4 \u05d0\u05d1\u05d0 \u05e9\u05dc\u05da?", "output": "\u300c\u4f55\u3088\u30de\u30de \uff1f \u300d", "explanation": "The Hebrew sentence is not correctly translated into Japanese. The translation refers to `mom` but the original is about `dad`"}, {"input": "\u05db\u05dc \u05d4\u05de\u05db\u05d5\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1235 | https://huggingface.co/datasets/Lots-of-LoRAs/task1235_ted_translation_he_ja | ted translation he ja |
367 | task367_synthetic_remove_floats | In this task you will be given a list of numbers. You should remove any number that is not an integer (whole number). If every number is not an whole number then an empty list ("[]") should be returned. Otherwise, answer with the list of whole numbers separated by comma inside brackets. | [
"Program Execution"
] | [
"Code",
"Mathematics"
] | [
"synthetic"
] | [
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[73.059, 7, 10.659, 18.459, 11]", "output": "[7, 11]", "explanation": "7 and 11 are the only whole numbers in the list."}, {"input": "[-49.103, 58.234, 4.3, -43.473]", "output": "[]", "explanation": "Every value in the input list is not an integer, so an empty list is returned."}] | [{"input": "[2, 0, 3.667, 9, -0.527]", "output": "[3.667, -0.527]", "explanation": "The output contains only numbers that are not integers."}, {"input": "[14.829, 6.5, -77.181, -52.664]", "output": "[15, 7, -77, -53]", "explanation": "The output rounded all of the non integers to the closest integer."}, {"input": "[-49... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task367 | https://huggingface.co/datasets/Lots-of-LoRAs/task367_synthetic_remove_floats | synthetic remove floats |
1254 | task1254_ted_translation_it_fa | You are given a sentence in Italian. Your job is to translate the Italian sentence into Farsi. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Italian"
] | [
"Persian"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Cos\u00ec diventa un igloo.", "output": "\u0627\u06cc\u0646 \u06cc\u06a9 \u062e\u0627\u0646\u0647 \u06cc \u0627\u0633\u06a9\u06cc\u0645\u0648 \u0645\u06cc \u0634\u0648\u062f.", "explanation": "The Italian sentence is correctly translated into Farsi, because the meaning is preserved."}, {"input": "Questi dat... | [{"input": "I miei colleghi in Google cominciarono una campagna di ricerca per trovarmi, e gli altri manifestanti nella piazza richiesero il mio rilascio.", "output": "\u062e\u06cc\u0644\u06cc \u062e\u0648\u0628 \u061b \u0628\u0647 \u0646\u062a\u06cc\u062c\u0647 \u0645\u0637\u0644\u0648\u0628 \u0631\u0633\u06cc\u062f\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1254 | https://huggingface.co/datasets/Lots-of-LoRAs/task1254_ted_translation_it_fa | ted translation it fa |
913 | task913_bianet_translation | In this task, we can are given an english sentence and the goal is to generate a text in 'turkish' language that is a faithful translation of the input sentence | [
"Translation"
] | [
"News"
] | [
"bianet"
] | [] | [
"English"
] | [
"Turkish"
] | [
"English"
] | [
"Vivek Bellalacharvu Srinivasa Rao"
] | [{"input": "It turned out the polling station subjected to FEMEN protest was where PM Recep Tayyip Erdo\u011fan would cast his vote in \u0130stanbul.", "output": "FEMEN aktivistleri Erdo\u011fan'\u0131n \u0130stanbul'da oy kullanaca\u011f\u0131 yerde oy zarflar\u0131n\u0131 f\u0131rlatt\u0131. #Erdo\u011fan\u0131Yasakl... | [{"input": "Previously, FEMEN Turkey protested against the twitter ban in Turkey with a FEMEN activist sharing her bare-breast photo with \"#DNS\" and \"#DirenTwitter\u201d (ResistTwitter) and DNS numbers written on it. (EA/BD)", "output": "Y\u00fcksekovahaber sitesinin haberine g\u00f6re Hakkari'nin Ba\u011flar mahall... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task913 | https://huggingface.co/datasets/Lots-of-LoRAs/task913_bianet_translation | bianet translation |
133 | task133_winowhy_reason_plausibility_detection | In this task you need to indicate the plausibility of reasoning for the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and a sentence that justifies which noun phrase the pronoun refers to. Correct reasons do not need to use all the knowledge from the sentence. The ... | [
"Coreference Resolution"
] | [
"Commonsense -> Concepts and Relations"
] | [
"winowhy"
] | [
"Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Xinran Zhao",
"Hongming Zhang",
"Yangqiu Song"
] | [{"input": "Sentence: The city councilmen refused the demonstrators a permit because they feared violence. \n Reason: The 'they' refers to the city councilmen because city councilmen are administrative so they are more likely to fear. \n Question: Is the above reasoning correct or wrong? ", "output": "Correct", "explan... | [{"input": "Sentence: The city councilmen refused the demonstrators a permit because they feared violence. \n Reason: The 'they' refers to the city councilmen because of the city's history of racial discrimination. \n Question: Is the above reasoning correct or wrong? ", "output": "Wrong Reason", "explanation": "This i... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task133 | https://huggingface.co/datasets/Lots-of-LoRAs/task133_winowhy_reason_plausibility_detection | winowhy reason plausibility detection |
1279 | task1279_ted_translation_pt_gl | You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Galician. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Portuguese"
] | [
"Galician"
] | [
"English"
] | [
"David Stap"
] | [{"input": "No final, espero que a beleza e prop\u00f3sito deste universo microsc\u00f3pico inspire novas e criativas abordagens no futuro da pesquisa do cancro.", "output": "A Mi\u00f1a esperanza \u00e9 que a beleza e prop\u00f3sito deste universo microsc\u00f3pico poida inspirar enfoques novos e creativos na investig... | [{"input": "Se ele fosse a um jogo de r\u00e2guebi, a nossa equipa ganhava.", "output": "Debido a que a xente puido tomar fotos cos seus mobiles do que estaba acontecendo nos postos electorais, foi imposible que o primer ministro arranxara as elecci\u00f3ns na forma que quer\u00eda facelo.", "explanation": "The Portuge... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1279 | https://huggingface.co/datasets/Lots-of-LoRAs/task1279_ted_translation_pt_gl | ted translation pt gl |
1549 | task1549_wiqa_answer_generation_missing_step | Given a list of steps and an additional step, determine where the step fits into the original list of steps. A correct answer, correctly places the given step into the set of steps so that it creates a new plausible set of steps. Output must be formatted as 'After step n', where n is the step number after which the giv... | [
"Sentence Ordering"
] | [
"Natural Science"
] | [
"wiqa"
] | [
"Temporal Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Hadi Mazboudi"
] | [{"input": "Steps: (1) Solar radiation reaches Earth's atmosphere (2) Some is reflected back into space (3) The rest of the energy is absorbed by land and oceans, heating the Earth (4) Some of this heat is trapped by greenhouse gases in the atmosphere (5) Human activities such as burning fuel are increasing the amount ... | [{"input": "Steps: (1) Water from the surface seeps below the soil (2) The water comes into contact with the rock below (3) The rock over the years carves through the rock (4) The space in the rock becomes larger and forms into a cave \nWhere does the following step fit into the given list of steps: As more rather rus... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1549 | https://huggingface.co/datasets/Lots-of-LoRAs/task1549_wiqa_answer_generation_missing_step | wiqa answer generation missing step |
1213 | task1213_atomic_classification_desires | In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | [
"Commonsense Classification"
] | [
"Sociology",
"Commonsense -> Concepts and Relations -> Social Commonsense"
] | [
"atomic"
] | [
"Relational Reasoning",
"Reasoning on Social Interactions",
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "Head: person<sep>Tail: complaints to addressed", "output": "Yes", "explanation": "This is a good example. The Head desires the Tail."}, {"input": "Head: PersonX accepts the offer<sep>Tail: smiles", "output": "No", "explanation": "In this example, \"PersonX accepts the offer desires smiles\" doesn't make sen... | [{"input": "Head: PersonX affords PersonY protection<sep>Tail: gets involved", "output": "Yes", "explanation": "In this example, \"PersonX affords PersonY protection desires getting involved\" doesn't make sense. To have a positive answer, the Head should be an entity. So the output should be \"No\"."}, {"input": "Head... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1213 | https://huggingface.co/datasets/Lots-of-LoRAs/task1213_atomic_classification_desires | atomic classification desires |
358 | task358_casino_classification_negotiation_uv_part | The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | [
"Negotiation Strategy Detection"
] | [
"Dialogue"
] | [
"casino"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kushal Chawla"
] | [{"input": "Context: 'Well maybe we can work something out between us. Our food and water was in the bags they loss so I really need those. Do you think you could make do with 1 food and some water?' 'I really need 2 foods. I can do with 1 water or if you are in a giving mood then maybe I can have 2 waters? \ud83d\ud... | [{"input": "Context: 'I believe that we have the same priorities. So we have a large family including children that need the food, but my wife also needs firewood due to poor circulation. She is susceptible to frost bite and limb loss' 'Okay so how about one of us takes 2 of the food and 1 of the firewood, and the ot... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task358 | https://huggingface.co/datasets/Lots-of-LoRAs/task358_casino_classification_negotiation_uv_part | casino classification negotiation uv part |
1537 | task1537_tamil_offenseval_dravidian_classification | In this task, you're given statements in native Tamil language. The statement can be written with the Tamil alphabet or the English alphabet. Your job is to evaluate if the statement is offensive or not. Label the post as "Not offensive" if the post does not contain offense or insult. Non-offensive posts do not includ... | [
"Toxic Language Detection"
] | [
"Social Media"
] | [
"offenseval_dravidian"
] | [] | [
"Tamil"
] | [
"English"
] | [
"English"
] | [
"Mamatha Juluru"
] | [{"input": "Handsome hunk keri vaa thalaivaa", "output": "Not offensive", "explanation": "The prediction of offensiveness is based on the following sentence \"Handsome hunk keri vaa thalaivaa\". It evaluates the understanding that the adjective \"Handsome\" is not offensive to any gender or thing or place in the sent... | [{"input": "Vera level BGM .. semma trailer. \ud83e\udd1e", "output": "Offensive", "explanation": "The statement is a positive comment about a movie and it background music."}, {"input": "\u0ba4\u0bbf\u0bb0\u0bc1\u0baa\u0bcd\u0baa\u0ba4\u0bcd\u0ba4\u0bc2\u0bb0\u0bcd \u0bae\u0bbe\u0bb5\u0b9f\u0bcd\u0b9f \u0bb5\u0ba9\u0... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1537 | https://huggingface.co/datasets/Lots-of-LoRAs/task1537_tamil_offenseval_dravidian_classification | tamil offenseval dravidian classification |
523 | task523_find_if_numbers_or_alphabets_are_more_in_list | In this task, you are given an input list A. If the count of numbers is more than that of alphabets in the list, answer 'Numbers Win'. If the count of alphabets is more than that of numbers in the list, answer 'Alphabets Win'. If the count of numbers is same as that of alphabets in the list, answer 'Numbers and Alphabe... | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [
"Mathematics -> Counting"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Pulkit Verma"
] | [{"input": "['238', 'h', '92', 'U', '2799']", "output": "Numbers Win", "explanation": "Here, the count of alphabets is 2, and that of numbers is 3. Since there are more numbers than alphabets, hence the answer is 'Numbers Win'."}, {"input": "['789', 'l', '2, 'E', 'n', '67']", "output": "Numbers and Alphabets are Tied",... | [{"input": "['7475', 'B', '2459', 'm', '8349', 'O', 'q']", "output": "Numbers and Alphabets are Tied", "explanation": "Here, the answer should have been 'Alphabets Win' as the count of alphabets is 4, and that of numbers is 3. Since there are less numbers than alphabets, hence the answer is 'Alphabets Win'."}, {"input"... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task523 | https://huggingface.co/datasets/Lots-of-LoRAs/task523_find_if_numbers_or_alphabets_are_more_in_list | find if numbers or alphabets are more in list |
286 | task286_olid_offense_judgment | In this task you are given a tweet and you must identify whether the tweet contains any offense or any form of (untargeted) profanity. Label the post as NOT if the post does not contain offense or profanity. Non-offensive posts do not include any form of offense or profanity. label the post as OFFENSIVE if the post co... | [
"Toxic Language Detection"
] | [
"Social Media -> Twitter"
] | [
"olid"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Amirreza Mirzaei"
] | [{"input": "@USER Someone should'veTaken\" this piece of shit to a volcano. \ud83d\ude02\"", "output": "OFFENSIVE", "explanation": "tweet contains offensive language."}, {"input": "@USER @USER Go home you\u2019re drunk!!! @USER #MAGA #Trump2020 \ud83d\udc4a\ud83c\uddfa\ud83c\uddf8\ud83d\udc4a URL", "output": "OFFENSIVE... | [{"input": "@USER @USER Go home you\u2019re drunk!!! @USER #MAGA #Trump2020 \ud83d\udc4a\ud83c\uddfa\ud83c\uddf8\ud83d\udc4a URL", "output": "I can't decide.", "explanation": "Do not generate anything else apart from one of the following characters: 'OFFENSIVE', 'NOT'."}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task286 | https://huggingface.co/datasets/Lots-of-LoRAs/task286_olid_offense_judgment | olid offense judgment |
327 | task327_jigsaw_classification_toxic | In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: toxic and non-toxic. Toxicity is defiend as anything that is rude, disrespectful, or unreasonable that would make someone want to leave a converation. | [
"Toxic Language Detection"
] | [
"Social Media"
] | [
"jigsaw"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Xudong Shen"
] | [{"input": "Comment: i am just sorry that khadr didnt get a bullet in the head before he blew the head off that innocent father because his islamic boogie skywizard told him to.", "output": "Toxic", "explanation": "This is a toxic comment because it advocates acts of violence."}, {"input": "Comment: This is excellent n... | [{"input": "Comment: \"racism\" -appears to be the only card in your deck!?", "output": "Toxic", "explanation": "This should be non-toxic because the comment only speaks of racism but does not disrespect any race."}, {"input": "Comment: Fat ass, go eat another do-nut.", "output": "Non-toxic", "explanation": "This shoul... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task327 | https://huggingface.co/datasets/Lots-of-LoRAs/task327_jigsaw_classification_toxic | jigsaw classification toxic |
902 | task902_deceptive_opinion_spam_classification | Classify the given hotel review based on the sentiment it expresses into two classes: negative and positive. | [
"Sentiment Analysis"
] | [
"Reviews"
] | [
"deceptive_opinion_spam_dataset"
] | [
"Reasoning on Social Interactions",
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Megh Patel"
] | [{"input": "I stayed at the Hilton Chicago for my cousins wedding. The service was impeccable. Not only was the staff attentive, they were respectful and careful not to interrupt the guests or make themselves known when serving dinner. I had the chicken wellington and it was to die for! The chicken was perfect and mois... | [{"input": "We had a great experience at this hotel. The hotel is Huge! The rooms were very clean, well appointed, and our room was very roomy with a great view of the snow covered park. The Staff was so nice and very helpfull. Donald, at the the Concierge desk scored us tickets to WICKED the day of the performance, an... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task902 | https://huggingface.co/datasets/Lots-of-LoRAs/task902_deceptive_opinion_spam_classification | deceptive opinion spam classification |
899 | task899_freebase_qa_topic_generation | Given a factoid/trivia type question, generate the topic of the question. The topic is the entity the question talks about. | [
"Question Understanding"
] | [
"Wikipedia"
] | [
"freebase_qa"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Karthik Murugesan"
] | [{"input": "Who was the first American President?", "output": "president of the united states", "explanation": "The question talks about the president of the USA."}, {"input": "The Dutch duo of Ray Slijngaard and Anita Dels, who had 8 top ten hits in the 90s, were better known by what name?", "output": "anita doth", "e... | [{"input": "Anna Smashnova played which sport professionally until 2007?", "output": "sport", "explanation": "The question is about Anna Smashnova, but it is generalized as a sport topic. This is a bad example."}, {"input": "Rob Davis, Les Gray, Dave Mount and Ray Stiles are members of which pop group?", "output": "dav... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task899 | https://huggingface.co/datasets/Lots-of-LoRAs/task899_freebase_qa_topic_generation | freebase qa topic generation |
1159 | task1159_bard_analogical_reasoning_containers | Two analogies that relate items to the associated containers is given in the form "A : B. C : ?". "A : B" relates item A to its associated container B. Your task is to replace the question mark (?) with the appropriate container for the given item C, following the "A : B" relation. | [
"Word Analogy"
] | [
"Commonsense"
] | [
"bard"
] | [
"Relational Reasoning",
"Commonsense Reasoning",
"Analogical Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Arjun Ashok"
] | [{"input": "soda : can. water : ?", "output": "bottle", "explanation": "The given analogy relates items to their containers. Soda can be stored in a can. Water can be stored in a bottle."}, {"input": "jam : jar. cereal : ?", "output": "box", "explanation": "The given analogy relates items to their containers. Jam can b... | [{"input": "trash : can. plates : ?", "output": "wash", "explanation": "The given analogy relates items to their containers. Trash can be stored in a can. But, wash is not the correct answer to plates, since wash is not a container. Further, the answer models an affordance"}, {"input": "detergent : bottle. cereal : ?",... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1159 | https://huggingface.co/datasets/Lots-of-LoRAs/task1159_bard_analogical_reasoning_containers | bard analogical reasoning containers |
1218 | task1218_ted_translation_en_ja | You are given a sentence in English. Your job is to translate the English sentence into Japanese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"English"
] | [
"Japanese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "And it was primarily because Kiribati realized that this was in their own self-interest to do this.", "output": "\u7b2c\u4e00\u306b\u30ad\u30ea\u30d0\u30b9\u5171\u548c\u56fd\u304c\u5f7c\u3089\u81ea\u8eab\u306e\u5229\u76ca\u306b\u306a\u308b\u3068\u7406\u89e3\u3057\u305f\u304b\u3089\u3067\u3059", "explanation... | [{"input": "To you and me, that's a heart attack.", "output": "\u300c\u3042\u306a\u305f\u3068\u79c1\u306b\u3068\u3063\u3066\u3001\u305d\u308c\u306f\u5fc3\u81d3\u767a\u4f5c\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u300d", "explanation": "The English sentence is not correctly translated into Japanese, because the ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1218 | https://huggingface.co/datasets/Lots-of-LoRAs/task1218_ted_translation_en_ja | ted translation en ja |
1108 | task1108_ted_translation_ar_fa | You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Farsi. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Arabic"
] | [
"Persian"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u0648\u0642\u062f \u0643\u062a\u0628\u0646 \u0627\u0644\u0644\u063a\u0629 \u0648\u063a\u0627\u0644\u0628\u0627 \u0645\u0627 \u0643\u0627\u0646\u062a \u0644\u063a\u0629 \u0622\u0644\u0629 \u0648\u0623\u062d\u064a\u0627\u0646\u0627 \u0634\u0641\u0631\u0629 \u062b\u0646\u0627\u0626\u064a\u0629 \u062a\u0631\u0... | [{"input": "\u0644\u0627 \u0623\u062d\u062f \u064a\u0631\u064a\u062f \u0627\u0644\u062e\u0636\u0648\u0639 \u0644\u0639\u0645\u0644\u064a\u0629 \u062c\u0631\u0627\u062d\u064a\u0629.", "output": "\u062e\u0648\u0628 \u0633\u0644\u0648\u0644\u0647\u0627\u06cc \u0642\u0644\u0628 \u062e\u06cc\u0644\u06cc \u062d\u0631\u06cc\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1108 | https://huggingface.co/datasets/Lots-of-LoRAs/task1108_ted_translation_ar_fa | ted translation ar fa |
1250 | task1250_ted_translation_it_ar | You are given a sentence in Italian. Your job is to translate the Italian sentence into Arabic. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Italian"
] | [
"Arabic"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Penso che abbastanza presto vedrete pazienti curati con le cellule staminali derivanti dal proprio grasso o adipe.", "output": "\u0648\u0623\u0639\u062a\u0642\u062f \u0623\u0646\u0647 \u0641\u064a \u0627\u0644\u0642\u0631\u064a\u0628 \u0633\u0648\u0641 \u062a\u0631\u0649 \u0627\u0644\u0645\u0631\u0636\u0649... | [{"input": "Mi \u00e8 stata diagnosticata l'encefalomielite mialgica.", "output": "\u0648\u0647\u0630\u0627 \u064a\u0639\u0646\u064a \u0644\u0627\u0646\u0646\u0627 \u0630\u0647\u0628\u0646\u0627 \u0644\u0644\u0639\u0631\u0627\u0642 \u064a\u062c\u0628 \u0627\u0646 \u0646\u0628\u0642\u064a \u0647\u0646\u0627\u0643 \u0627... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1250 | https://huggingface.co/datasets/Lots-of-LoRAs/task1250_ted_translation_it_ar | ted translation it ar |
878 | task878_kde4_translation | Your task is to localize given English phrase into Telugu language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation... | [
"Translation"
] | [
"Computer Science"
] | [
"kde4"
] | [] | [
"English"
] | [
"Telugu"
] | [
"English"
] | [
"Subba Raja Kashyap Saligrama"
] | [{"input": "Information about available protocols", "output": "\u0c05\u0c02\u0c26\u0c41\u0c2c\u0c3e\u0c1f\u0c41\u0c32\u0c4b\u0c28\u0c3f \u0c28\u0c3f\u0c2d\u0c02\u0c26\u0c28\u0c32 \u0c17\u0c41\u0c30\u0c3f\u0c02\u0c1a\u0c3f \u0c38\u0c2e\u0c3e\u0c1a\u0c3e\u0c30\u0c02", "explanation": "The sentence is truly translated as a... | [{"input": "Configure the browser behavior", "output": "\u0c2c\u0c4d\u0c30\u0c4c\u0c1c\u0c30\u0c4d \u0c2a\u0c4d\u0c30\u0c35\u0c30\u0c4d\u0c24\u0c28\u0c28\u0c41 \u0c06\u0c15\u0c43\u0c24\u0c40\u0c15\u0c30\u0c3f\u0c02\u0c1a\u0c41\u0c2e\u0c41", "explanation": "The sentence is generic enough to translate word 'browser' inst... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task878 | https://huggingface.co/datasets/Lots-of-LoRAs/task878_kde4_translation | kde4 translation |
196 | task196_sentiment140_answer_generation | In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". | [
"Sentiment Analysis"
] | [
"Social Media -> Twitter"
] | [
"sentiment140"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "Tweet: @justinchuan Awww! I was thinking about you lot up there! Glad you enjoyed it Question: is it a positive tweet?", "output": "yes", "explanation": "There is an expression of happiness in this tweet text, hence, we can say it's positive. So answer is 'yes'."}, {"input": "Tweet: @jamiesmart I can't but... | [{"input": "Tweet: You know what i hate? When you are marathon comic reading only to find out that part 2 of a story is in a comic you dont get #Batman686 Question: is it a positive tweet?", "output": "yes", "explanation": "There is hateness in the tweet content, it is not a positive tweet."}, {"input": "Tweet: So Jas... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task196 | https://huggingface.co/datasets/Lots-of-LoRAs/task196_sentiment140_answer_generation | sentiment140 answer generation |
427 | task427_hindienglish_corpora_hi-en_language_identification | In this task, you are given a sentence which is either in the Hindi language or English language. You task is to identify the language of input sentence. Input sentence can be in Hindi or English language only and also it cannot have two languages at a time. | [
"Language Identification"
] | [
"News",
"TED Talks",
"Wikipedia"
] | [
"hindienglish_corpora"
] | [] | [
"Hindi",
"English"
] | [
"English"
] | [
"English"
] | [
"Mirali Purohit"
] | [{"input": "The first two were found unreliable and the prosecution case rested mainly on the evidence of the remaining five approvers .", "output": "English", "explanation": "Input sentence is in English language as all the characters are of English alphabets only."}, {"input": "\u092e\u0917\u0930 \u0909\u0928\u0915\u... | [{"input": "The first two were found unreliable and the prosecution case rested mainly on the evidence of the remaining five approvers .", "output": "English, Hindi", "explanation": "Input sentence can be in only one language; so, answer should be either Hindi or English only."}, {"input": "\u092e\u0917\u0930 \u0909\u0... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task427 | https://huggingface.co/datasets/Lots-of-LoRAs/task427_hindienglish_corpora_hi-en_language_identification | hindienglish corpora hi-en language identification |
788 | task788_pawsx_korean_japanese_translation | Given a sentence in Korean, provide an equivalent paraphrased translation in Japanese that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Korean"
] | [
"Japanese"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "1975 \ub144\ubd80\ud130 76 \ub144\uae4c\uc9c0 NBA \uc2dc\uc98c\uc740 \uc804\uad6d \ub18d\uad6c \ud611\ud68c (National Basketball Association)\uc758 30 \ubc88\uc9f8 \uc2dc\uc98c\uc774\uc5c8\ub2e4.", "output": "1975 - 76\u5e74\u306e\u5168\u7c73\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb\u5354\u4f1a\u30... | [{"input": "1560 \ub144 10 \uc6d4 \ud30c\ub9ac\uc5d0\uc11c \uadf8\ub294 \ube44\ubc00\ub9ac\uc5d0 \uc601\uad6d \ub300\uc0ac \uc778 \ub2c8\ucf5c\ub77c\uc2a4 \ud2b8\ub85d \ubaa8\ud2bc\uc744 \ub9cc\ub0ac\uace0 \uc2a4\ucf54\ud2c0\ub79c\ub4dc\ub97c \ud1b5\ud574 \uc601\uad6d\uc73c\ub85c \ub3cc\uc544\uac08 \uc5ec\uad8c\uc744 \... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task788 | https://huggingface.co/datasets/Lots-of-LoRAs/task788_pawsx_korean_japanese_translation | pawsx korean japanese translation |
1573 | task1573_samsum_classification | In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people. | [
"Coherence Classification"
] | [
"Dialogue",
"Commonsense -> Concepts and Relations -> Social Commonsense"
] | [
"samsum"
] | [
"Commonsense Reasoning -> Social Situations",
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Amrit Bhaskar"
] | [{"input": " Noah: When and where are we meeting? :), Madison: I thought you were busy...? ", "output": "True", "explanation": " The sentences are sequential here because other person is replying to the question asked and are in same context. So, it's a positive example."}, {"input": " Matt: Do you want to go for date?... | [{"input": " Ray: Hey guys, I don't know if you heard but someone stole my bike yesterday so I'm going to post it on fb and would appreciate if you share! THX, Sam: Let us know if you need someone to go dumpster diving with ", "output": "True", "explanation": " The sentences aren't sequential here as the two person are... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1573 | https://huggingface.co/datasets/Lots-of-LoRAs/task1573_samsum_classification | samsum classification |
439 | task439_eng_guj_parallel_corpus_gu_en_translation | In this task, you are given a sentence in the Gujarati language and your task is to convert Gujarati sentence into the English language. | [
"Translation"
] | [
"Captions -> Image Captions"
] | [
"eng_guj_parallel_corpus"
] | [] | [
"English"
] | [
"Gujarati"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "\u0a98\u0ac7\u0a9f\u0abe\u0a82\u0aa8\u0ac0 \u0a9f\u0acb\u0ab3\u0abe\u0a82 \u0a8f\u0a95 \u0a97\u0acb\u0a9a\u0ab0\u0aae\u0abe\u0a82 \u0a9a\u0ab0\u0abe\u0a88 \u0ab8\u0abe\u0aa5\u0ac7 \u0aae\u0ab3\u0ac0\u0aa8\u0ac7 \u0a8a\u0aad\u0abe \u0a9b\u0ac7.", "output": "A herd of sheep standing together grazing in a past... | [{"input": "\u0a98\u0ac7\u0a9f\u0abe\u0a82\u0aa8\u0ac0 \u0a9f\u0acb\u0ab3\u0abe\u0a82 \u0a8f\u0a95 \u0a97\u0acb\u0a9a\u0ab0\u0aae\u0abe\u0a82 \u0a9a\u0ab0\u0abe\u0a88 \u0ab8\u0abe\u0aa5\u0ac7 \u0aae\u0ab3\u0ac0\u0aa8\u0ac7 \u0a8a\u0aad\u0abe \u0a9b\u0ac7.", "output": "A herd of cow standing together grazing in a pastur... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task439 | https://huggingface.co/datasets/Lots-of-LoRAs/task439_eng_guj_parallel_corpus_gu_en_translation | eng guj parallel corpus gu en translation |
1367 | task1367_opustedtalks_translation | The provided text is in Croatian, and we ask you to translate the text to the English language. Please bear in mind the following guidelines while translating: 1) We are looking for the most naturally written and formal form of each sentence in the English language. 2) If you encounter any special characters like '#@%$... | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"opus_ted_talks"
] | [] | [
"Croatian"
] | [
"English"
] | [
"English"
] | [
"Vansh Patel"
] | [{"input": "\u017delim da sada zamislite nosiv robot koji vam daje nadljudske sposobnosti, ili neki drugi koji omogu\u010duje korisnicima invalidskih kolica da stoje i ponovno hodaju.", "output": "I want you now to imagine a wearable robot that gives you superhuman abilities, or another one that takes wheelchair users ... | [{"input": "Dakle, to je za ozbiljno.", "output": "so this is for real.", "explanation": "The input is not case-sensitive and completely lowercased."}, {"input": "Sada \u0107emo se okrenuti prema korisnicima invalidskih kolica ne\u0161to, oko \u010dega sam posebno strastven", "output": "now lets turn our heads towards ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1367 | https://huggingface.co/datasets/Lots-of-LoRAs/task1367_opustedtalks_translation | opustedtalks translation |
557 | task557_alt_translation_en_ba | In this task, given a sentence in the English language, your task is to convert it into the Bahasa (Indonesian) language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Indonesian"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "At its peak in the 1970s, the programme achieved nine million viewers.", "output": "Pada puncaknya di tahun 1970-an, program mencapai 9 juta pemirsa.", "explanation": "The above sentence is correctly translated from English to Bahasa Indonesia."}, {"input": "Oklahoma Senator Tom Coburn initially blocked Sen... | [{"input": "In 2003 this was 14.1 billion global hectares, or 2.2 global hectares per person (a global hectare is a hectare with world-average ability to produce resources and absorb wastes).", "output": "Bos IAG menyebut penjualan ini sebagai \"berita bagus untuk Inggris\" yang hasilnya akan \"bagus untuk bisnis di In... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task557 | https://huggingface.co/datasets/Lots-of-LoRAs/task557_alt_translation_en_ba | alt translation en ba |
1242 | task1242_ted_translation_gl_he | You are given a sentence in Galician. Your job is to translate the Galician sentence into Hebrew. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"Hebrew"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Pregunteille: \"\" \u00c9 coma un so\u00f1o? \"\" E dixo: \"\" Non, non \u00e9 coma un so\u00f1o. \u00c9 coma unha pel\u00edcula. Ten cor. Ten movemento.", "output": "\"\u05d0\u05d6,\" \u05d0\u05de\u05e8\u05ea\u05d9, \"\u05d6\u05d4 \u05db\u05de\u05d5 \u05d7\u05dc\u05d5\u05dd?\" \u05d5\u05d4\u05d9\u05d0 \u05... | [{"input": "Todo o mundo, sobre todo cando o brote comezou a estenderse globalmente, estaba tratando de aprender, participar, involucrarse.", "output": "\u05de\u05e6\u05d0\u05e0\u05d5 \u05d0\u05ea \u05d4\u05d0\u05d6\u05d5\u05e8 \u05d4\u05db\u05d7\u05d5\u05dc \u05d4\u05e9\u05e0\u05d9 \u05d1\u05e6\u05d3 \u05d4\u05e9\u05e... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1242 | https://huggingface.co/datasets/Lots-of-LoRAs/task1242_ted_translation_gl_he | ted translation gl he |
888 | task888_reviews_classification | Classify given movie review into two categories: positive, or negative based on its content. | [
"Sentiment Analysis"
] | [
"Reviews -> Movies"
] | [
"rotten_tomatoe"
] | [
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Saianirud Reddy Nellore"
] | [{"input": "if you sometimes like to go to the movies to have fun , wasabi is a good place to start .", "output": "positive", "explanation": "The author in the review recommends starting with wasabi, which has a positive sense. So, the given review is positive."}, {"input": "this is a film well worth seeing , talking a... | [{"input": "creepy but ultimately unsatisfying thriller .", "output": "positive", "explanation": "The author mentions that the movie is an unsatisfying thriller, which has a negative sense. So, the given review should be negative instead of positive."}, {"input": "the film often achieves a mesmerizing poetry .", "outpu... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task888 | https://huggingface.co/datasets/Lots-of-LoRAs/task888_reviews_classification | reviews classification |
877 | task877_kde4_translation | Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | [
"Translation"
] | [
"Computer Science"
] | [
"kde4"
] | [] | [
"English"
] | [
"Hindi"
] | [
"English"
] | [
"Subba Raja Kashyap Saligrama"
] | [{"input": "Displays the document relations of a document", "output": "\u0926\u0938\u094d\u0924\u093e\u0935\u0947\u091c\u093c \u0915\u093e \u0926\u0938\u094d\u0924\u093e\u0935\u0947\u091c\u093c \u0938\u092e\u094d\u092c\u0928\u094d\u0927 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0915\u0930\u0924\u093e \u0... | [{"input": "Show image file & name", "output": "\u091b\u0935\u093f \u092b\u093c\u093e\u0907\u0932 \u0928\u093e\u092e \u0926\u093f\u0916\u093e\u090f\u0901", "explanation": "This is not a accurate localization as the special character is not copied and the 'file & name' part is translated as '\u092b\u093c\u093e\u0907\u09... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task877 | https://huggingface.co/datasets/Lots-of-LoRAs/task877_kde4_translation | kde4 translation |
242 | task242_tweetqa_classification | In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify given passage into two categories: (1) "yes" if the given context is useful in answering the question, and (2) "no" if the given context is not useful. | [
"Answerability Classification"
] | [
"Social Media -> Twitter"
] | [
"tweetqa"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "Context: Our prayers are with the students, educators & families at Independence High School & all the first responders on the scene. #PatriotPride\u2014 Doug Ducey (@dougducey) February 12, 2016 Question: at which school were first responders on the scene for? Answer: independence high school", "output": "... | [{"input": "Context: So many bad jokes about #BrazilvsGermany right now. I can't take it an neymar.\u2014 Professor Snape (@_Snape_) July 8, 2014 Question: what can\u2019t professor snape take anymore? Answer: bad jokes", "output": "no", "explanation": "Here, the generated label should be 'yes' because the given contex... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task242 | https://huggingface.co/datasets/Lots-of-LoRAs/task242_tweetqa_classification | tweetqa classification |
1542 | task1542_every_ith_element_from_starting | In this task, you are given an input i,A where i is an integer and A is an array. You need to find every ith element of A starting with the 1st element. | [
"Program Execution"
] | [
"Code"
] | [
"synthetic"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Pulkit Verma"
] | [{"input": "3, ['a', '34', 'f', '931', '7', '3432', '13245', '762']", "output": "a, 931, 13245", "explanation": "Here, every 3rd element from array are 'a', '931', and '13245'."}, {"input": "4, ['D', '9127', '4217', '8469', '9585', '933', '5401', 't', '1977', '7989', 'l', '455', 'r', 'K', 'p', '1755', '7391', 'h']", "o... | [{"input": "4, ['5831', 'k', 'T', 'J', '3895', 'N', 'p', 'V', '9379']", "output": "5831, T, N, V", "explanation": "Here, the answer should have been ['5831', '3895', '9379'] as every 4th element of the array are '5831', '3895', and '9379'."}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1542 | https://huggingface.co/datasets/Lots-of-LoRAs/task1542_every_ith_element_from_starting | every ith element from starting |
199 | task199_mnli_classification | In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to determine if the two sentences clearly agree/disagree with each other, or if this can't be determined. Indicate your answer as yes or no respectively. | [
"Textual Entailment"
] | [
"History",
"Fiction",
"Dialogue",
"Law",
"Government and Politics"
] | [
"multinli"
] | [
"Textual Entailment"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Anjana Arunkumar"
] | [{"input": "Sentence 1: Next to the MGM Grand you will find M and M World. Sentence 2: The candy has many fans who love its attractions.", "output": "no", "explanation": "It is not clear that M and M world is popular."}, {"input": "Sentence 1: I've forgotten his name now, confessed Tuppence. Sentence 2: Tuppence rememb... | [{"input": "Sentence 1: There was an earthquake in San Fransisco. Sentence 2: The earthquake caused a lot of road damage.", "output": "yes", "explanation": "The magnitude of the earthquake may or may not have been large enough to cause damage."}, {"input": "Sentence 1: Representing yourself in court can be a tricky end... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task199 | https://huggingface.co/datasets/Lots-of-LoRAs/task199_mnli_classification | mnli classification |
171 | task171_spl_translation_en_es | The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | [
"Translation"
] | [
"Public Places"
] | [
"semantic_parser_localizer"
] | [] | [
"English"
] | [
"Spanish"
] | [
"English"
] | [
"Mehrad Moradshahi"
] | [{"input": "are there any \" italian \" restaurants nearby with 2 star reviews ?", "output": "\u00bfhay alg\u00fan restaurante \" italian \" cerca con opiniones de 2 estrellas?", "explanation": "The translation correctly preserves \" italian \" entity and is accurate"}, {"input": "what kind of food does this restaurant... | [{"input": "where is the closest \" wendy 's \" ?", "output": "\u00bfd\u00f3nde est\u00e1 el wendy 's m\u00e1s cercano?", "explanation": "Translation contain the entity \" wendy 's \" but quotation marks are dropped"}, {"input": "show me the closest \" mcdonald 's \"", "output": "mu\u00e9streme el \" McDonald's \" m\u0... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task171 | https://huggingface.co/datasets/Lots-of-LoRAs/task171_spl_translation_en_es | spl translation en es |
652 | task652_parsinlu_en_fa_translation | In this task, you are given a question in English, and your task is to translate it into Persian. | [
"Translation"
] | [
"Web"
] | [
"parsinlu"
] | [] | [
"English"
] | [
"Persian"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "How do I look up my pay stubs for McDonald's?", "output": "\u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u0645 \u062e\u0631\u062f\u0647 \u0641\u0631\u0648\u0634\u06cc \u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u06a9 \u062f\u0648\u0646\u0627\u064... | [{"input": "Why companies like Rolex and blackberry they never advertising their products?", "output": "\u0686\u0631\u0627 \u0634\u0631\u06a9\u062a \u0647\u0627\u0647\u0631\u06af\u0632 \u0645\u062d\u0635\u0648\u0644\u0627\u062a \u062e\u0648\u062f \u0631\u0627 \u062a\u0628\u0644\u06cc\u063a \u0646\u0645\u06cc \u06a9\u06... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task652 | https://huggingface.co/datasets/Lots-of-LoRAs/task652_parsinlu_en_fa_translation | parsinlu en fa translation |
762 | task762_emea_fr_sk_translation | In this task, you are given a sentence in the French language. Your task is to convert it to Slovak language. | [
"Translation"
] | [
"Miscellaneous"
] | [
"emea_fr_sk"
] | [] | [
"French"
] | [
"Slovak"
] | [
"English"
] | [
"Vijay Kumawat"
] | [{"input": "Abilify est un m\u00e9dicament qui contient le principe actif aripiprazole.", "output": "Abilify je liek, ktor\u00e9ho \u00fa\u010dinnou l\u00e1tkou je aripiprazol.", "explanation": "Translation of French sentence to Slovak sentence is correctly translated."}, {"input": "L'incidence des d\u00e9c\u00e8s dans... | [{"input": "9 Dans trois \u00e9tudes court terme (4 \u00e0 6 semaines) contr\u00f4l\u00e9es versus placebo portant sur 1.228 patients schizophr\u00e8nes pr\u00e9sentant des sympt\u00f4mes positifs ou n\u00e9gatifs, l'aripiprazole a montr\u00e9 une am\u00e9lioration significativement plus importante des sympt\u00f4mes p... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task762 | https://huggingface.co/datasets/Lots-of-LoRAs/task762_emea_fr_sk_translation | emea fr sk translation |
1726 | task1726_mathqa_correct_answer_generation | The task is to generate the correct answer for a given math problem. | [
"Question Answering"
] | [
"Mathematics"
] | [
"math_qa"
] | [
"Quantitative Reasoning",
"Scientific Reasoning",
"Mathematics -> Combinatorics",
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Adheesh Wadkar"
] | [{"input": "a multiple choice test consists of 4 questions, and each question has 5 answer choices. in how many r ways can the test be completed if every question is unanswered ?", "output": "625", "explanation": "Total r of 5 * 5 * 5 * 5 = 5 ^ 4 = 625 ways to answer all of them. Therefore, the answer is 625."}, {"inpu... | [{"input": "if x and y are positive integers and 7 + x + y + xy = 21, what is the value of x + y ?", "output": "9", "explanation": "For a: 7 + 3 + xy = 21 ; xy = 11 ( impossible , 11 prime number . 1 + 11 does n ' t equal 3 ) for b : 7 + 5 + xy = 21 ; xy = 9 ( no combination of xy = 9 and x + y = 5 ) for c : 7 + 6 + xy... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1726 | https://huggingface.co/datasets/Lots-of-LoRAs/task1726_mathqa_correct_answer_generation | mathqa correct answer generation |
960 | task960_ancora-ca-ner_named_entity_recognition | Given the following Catalan sentence, indicate the name entities (i.e., the real-world objects such as a person, location, organization, etc. that can be denoted with a proper name) such as 'New York Times'. For each words of a named-entity, indicate their type 'LOC' or 'ORG' or 'PER', where 'LOC' indicates a location... | [
"Named Entity Recognition"
] | [
"News"
] | [
"ancora_ca_ner"
] | [] | [
"Catalan"
] | [
"Catalan"
] | [
"English"
] | [
"Surya Singulur"
] | [{"input": "Una setantena de treballadors de Fomento de Construcciones y Contratas a Manresa , gaireb\u00e9 la totalitat de la plantilla , s' han manifestat aquest migdia pels carrers de la ciutat .", "output": "Una (O) setantena (O) de (O) treballadors (O) de (O) Fomento (B-ORG) de (I-ORG) Construcciones (I-ORG) y (I-... | [{"input": "D' una banda , s' ha fet una bustiada informativa sobre els dies que hi haur\u00e0 recollida de deixalles .", "output": "D' (I-LOC) una (O) banda (O) , (O) s' (O) ha (O) fet (O) una (O) bustiada (O) informativa (O) sobre (O) els (O) dies (O) que (O) hi (O) haur\u00e0 (O) recollida (O) de (O) deixalles (O) .... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task960 | https://huggingface.co/datasets/Lots-of-LoRAs/task960_ancora-ca-ner_named_entity_recognition | ancora-ca-ner named entity recognition |
347 | task347_hybridqa_incorrect_answer_generation | In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write an implausible POS tag to the question. Even though there exist multiple wrong answers, we only need a single wrong answer. Here is the Alphabetical list of part-of-speech tags used in this task: CC... | [
"Pos Tagging"
] | [
"Wikipedia"
] | [
"hybridqa"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "What is the part-of-speech tag of the word \"the\" in the following question: Who were the builders of the mosque in Herat with fire temples ?", "output": "IN", "explanation": "This is a good example. POS tag of the is DT and IN is incorrect."}, {"input": "What is the part-of-speech tag of the word \"number... | [{"input": "What is the part-of-speech tag of the word \"Year\" in the following question: What year was the 1971-72 ECAC Hockey Player of the Year born ?", "output": "NN", "explanation": "The part-of-speech tag of the word Year in the question is NN. Note that the task is to generate an incorrect answer."}, {"input": ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task347 | https://huggingface.co/datasets/Lots-of-LoRAs/task347_hybridqa_incorrect_answer_generation | hybridqa incorrect answer generation |
1245 | task1245_ted_translation_gl_fa | You are given a sentence in Galician. Your job is to translate the Galician sentence into Farsi. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"Persian"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Cando chegas a estas sociedades en desenrolo, as mulleres son os piares da s\u00faa comunidade, pero os homes seguen a ser os que controlan as r\u00faas.", "output": "\u0648\u0642\u062a\u06cc \u0628\u0647 \u0627\u06cc\u0646 \u062c\u0627\u0645\u0639\u0647 \u0647\u0627\u06cc \u062f\u0631 \u062d\u0627\u0644 \u... | [{"input": "Se alg\u00fan d\u00eda saio de aqu\u00ed, sempre terei unha marca no meu nome.", "output": "(\u062e\u0646\u062f\u0647 \u062d\u0636\u0627\u0631) \u0628\u0635\u0648\u0631\u062a \u0622\u0646\u0644\u0627\u06cc\u0646 \u0639\u06cc\u0646\u06a9 \u0645\u06cc \u0641\u0631\u0648\u0634\u0646\u062f.", "explanation": "Th... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1245 | https://huggingface.co/datasets/Lots-of-LoRAs/task1245_ted_translation_gl_fa | ted translation gl fa |
1220 | task1220_ted_translation_en_ar | You are given a sentence in English. Your job is to translate the English sentence into Arabic. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"English"
] | [
"Arabic"
] | [
"English"
] | [
"David Stap"
] | [{"input": "(Applause) However there is a political battle in our country.", "output": "(\u062a\u0635\u0641\u064a\u0642) \u0648\u0645\u0639 \u0630\u0644\u0643 \u0647\u0646\u0627\u0643 \u0645\u0639\u0627\u0631\u0643 \u0633\u064a\u0627\u0633\u064a\u0629 \u0641\u064a \u0628\u0644\u062f\u0646\u0627.", "explanation": "The E... | [{"input": "And I say to you, I might not stick to this, but I don't think I'll ever serve foie gras on my menu again because of that taste experience with Eduardo.", "output": "\u062d\u0633\u0646\u0627 \u0641\u0644\u0646\u0642\u0644 \u060c \u0645\u0627\u0647\u064a \u0625\u062d\u062a\u0645\u0627\u0644\u0627\u062a \u062... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1220 | https://huggingface.co/datasets/Lots-of-LoRAs/task1220_ted_translation_en_ar | ted translation en ar |
1333 | task1333_check_validity_date_ddmmyyyy | In this task, you are given a date in "dd/mm/yyyy" format. You need to check if the date is valid or not. Return 1 if it is valid, else return 0. A date is valid if the components day("dd"), month("mm") and year("yyyy") are all valid individually. A day(dd) is valid if it: a) lies between 1 and 31 for the months of Jan... | [
"Misc."
] | [
"Mathematics",
"Commonsense -> Concepts and Relations"
] | [
"synthetic"
] | [
"Numerical Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Ravsehaj Singh Puri"
] | [{"input": "15/2/2014", "output": "1", "explanation": "It is a valid date as the month is February and it is not a leap year, so the range of days is from 1 to 28, and 15 lies in this range."}, {"input": "10/18/1951", "output": "0", "explanation": "It is an invalid date because the month is greater than 12 and hence in... | [{"input": "37/13/1947", "output": "1", "explanation": "It is an invalid date because the month(mm) and the day(dd) are invalid. The month is greater than 12 and the day is greater than 31."}, {"input": "15/01/2061", "output": "0", "explanation": "It is a valid date because 15 is a valid day of January."}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1333 | https://huggingface.co/datasets/Lots-of-LoRAs/task1333_check_validity_date_ddmmyyyy | check validity date ddmmyyyy |
1546 | task1546_conll2002_location_name_extraction_answer_generation | In this task, you will be presented with a question in Dutch language, and you have to write the location names from the question if present. B denotes the first item of a phrase and an I any non-initial word. Identifier used for the location name - LOC. . There can be instances with no location name entity, then retur... | [
"Named Entity Recognition"
] | [
"Miscellaneous"
] | [
"conll2022"
] | [] | [
"Dutch"
] | [
"Dutch",
"English"
] | [
"English"
] | [
"Manikanta Ellenki"
] | [{"input": "Jean Alavoine ( Fra )", "output": "Fra: B-LOC", "explanation": "In the given sentence, Fra is identified as the location, which is correct."}, {"input": "Overal is Duckstad ' met de Donald Duck-verzameling van de Duitse cultuurfilosoof prof. Dr. Eckart die Donald Duck ziet als een intrigerend symbool van de... | [{"input": "Javier Ochoa ( Spa )", "output": "None", "explanation": "In the given sentence, Spa is not identified as the location, which is incorrect."}, {"input": "Elk van hen heeft het grootste deel van zijn leven gewoond in een Amerika en een New York waar ze hun geaardheid verborgen moesten houden -- alleen in semi... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1546 | https://huggingface.co/datasets/Lots-of-LoRAs/task1546_conll2002_location_name_extraction_answer_generation | conll2002 location name extraction answer generation |
1519 | task1519_qa_srl_question_generation | In this task, you are given a sentence and a verb from the sentence. Your task is to generate a set of wh-questions starting with who, what, when, where, why, how, how much. The generated questions must contain the verb and the answers to these questions are phrases in the input sentence. The answer to the questions is... | [
"Question Generation"
] | [
"News",
"Wikipedia"
] | [
"qa_srl"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Sai Venkat Subramani"
] | [{"input": "Sentence: The album is named after the discredited pseudoscience of phrenology , the study of head shapes to determine intelligence and character , which was used to rationalize racism during the 19th century in the United States .\n Verb: named", "output": "what is named after something?", "explanation":... | [{"input": "Sentence: On September 21 , 1955 , Moore went up in weight to face future Hall of Famer Rocky Marciano for Marciano 's Heavyweight Championship . \n Verb: went", "output": "Did something went up?", "explanation": "Although the question can be answered from the sentence, The output does not start with one of... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1519 | https://huggingface.co/datasets/Lots-of-LoRAs/task1519_qa_srl_question_generation | qa srl question generation |
970 | task970_sherliic_causal_relationship | In this task, you will be given two sentences sentence1 and sentence2. You should decide whether the second sentence is entailed(agreed) by the first sentence. If it does entail, answer "yes", else answer "no". | [
"Textual Entailment"
] | [
"Formal logic"
] | [
"sherliic"
] | [
"Textual Entailment -> Deductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "sentence1:region is nation in location\nsentence2:region is country in location", "output": "yes", "explanation": "A nation is a community of people of similar characteristics/descent with a common government. A country is a region sharing a common government. Hence, a nation can be defined as a country."},... | [{"input": "sentence1:award_winner is edging employer\nsentence2:award_winner is winning over employer", "output": "Incorrect", "explanation": "Answer expected is either \"yes\" or \"no\""}, {"input": "sentence1:award_nominee is finishing in sports.sports_league\nsentence2:award_nominee is teaming in sports.sports_lea... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task970 | https://huggingface.co/datasets/Lots-of-LoRAs/task970_sherliic_causal_relationship | sherliic causal relationship |
1275 | task1275_ted_translation_pt_ja | You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Japanese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Portuguese"
] | [
"Japanese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "A ideia \u00e9 muito, muito simples.", "output": "\u3053\u306e\u30a2\u30a4\u30c7\u30a2\u306f\u3068\u3066\u3082\u30b7\u30f3\u30d7\u30eb\u3067", "explanation": "The Portugese sentence is correctly translated into Japanese, because the meaning is preserved."}, {"input": "Eles s\u00e3o alvo de leis que punem as... | [{"input": "\"\" O que lhe estou a apresentar hoje n\u00e3o \u00e9 um produto aut\u00f3nomo.", "output": "\u3053\u306e\u5199\u771f\u306e\u3088\u3046\u306b\u653e\u7f6e\u3055\u308c\u8352\u5ec3\u3057\u305f 3 \u30ad\u30ed\u306e\u30a6\u30a9\u30fc\u30bf\u30fc\u30d5\u30ed\u30f3\u30c8\u306f\u30d6\u30eb\u30c3\u30af\u30ea\u30f3\... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1275 | https://huggingface.co/datasets/Lots-of-LoRAs/task1275_ted_translation_pt_ja | ted translation pt ja |
541 | task541_alt_translation_kh_en | In this task, given a sentence in the Central Khmer language, your task is to convert it into the English language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"Central Khmer"
] | [
"English"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "\u17a2\u17c6\u1796\u17b8\u1780\u17b6\u179a\u179b\u17bb\u1794\u1785\u17c4\u179b \u179b\u17c4\u1780\u17a0\u17d2\u1782\u17b6\u179a\u17b8 \u1794\u17c1\u178f\u1798\u17c1\u1793 \u1794\u17b6\u1793\u17b7\u1799\u17b6\u1799\u1790\u17b6 \"\u1797\u17b6\u1796\u17a2\u17b6\u1798\u17c9\u17b6\u179f\u200b\u1793\u17c3\u179a\u... | [{"input": "\u1785\u17d2\u1794\u17b6\u1794\u17cb\u179a\u1794\u179f\u17cb\u17a2\u1784\u17d2\u1782\u1780\u17b6\u179a\u179f\u17bb\u1781\u1797\u17b6\u1796\u1796\u17b7\u1797\u1796\u179b\u17c4\u1780\u178f\u1798\u17d2\u179a\u17bc\u179c\u17b1\u17d2\u1799\u1789\u17c9\u17bc\u179c\u17c2\u179b\u17a0\u17d2\u179f\u17c2\u17a1\u1784\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task541 | https://huggingface.co/datasets/Lots-of-LoRAs/task541_alt_translation_kh_en | alt translation kh en |
373 | task373_synthetic_round_tens_place | In this task you will be given a list of integers. You should round each integer to the nearest tens place. That means you should round the number to the nearest multiple of 10. | [
"Program Execution"
] | [
"Code",
"Mathematics"
] | [
"synthetic"
] | [
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[-83, 53, -48, 8]", "output": "[-80, 50, -50, 10]", "explanation": "The output correctly rounds each integer in the input list to the nearest ten. So this is a good example."}, {"input": "[93, -18, 83, -66, -74]", "output": "[90, -20, 80, -70, -70]", "explanation": "The integers '-66' and '-74' both round t... | [{"input": "[-97, 66, -4, 53, 65, 14]", "output": "[-90, 60, -10, 60, 60, 20]", "explanation": "The output rounded every integer to the incorrect multiple of 10. So this is a bad example."}, {"input": "[93, -18, 83, -66, -74]", "output": "[90, -10, 80, -60, -80]", "explanation": "The output rounded all of the negative ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task373 | https://huggingface.co/datasets/Lots-of-LoRAs/task373_synthetic_round_tens_place | synthetic round tens place |
1273 | task1273_ted_translation_fa_pt | You are given a sentence in Persian. Your job is to translate the Farsi sentence into Portugese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Persian"
] | [
"Portuguese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u0645\u0646 \u0647\u0645\u0686\u0646\u0627\u0646 \u0645\u0639\u062a\u0642\u062f\u0645 \u06a9\u0647 \u062d\u0645\u0644 \u0648 \u0646\u0642\u0644 \u06a9\u0627\u0646\u0648\u0646 \u0645\u0634\u06a9\u0644\u0627\u062a \u062c\u0647\u0627\u0646 \u0627\u0633\u062a.", "output": "E eu continuo a pensar que o transpor... | [{"input": "\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u062e\u0627\u0637\u0631 \u062a\u0648\u062c\u0647\u062a\u0648\u0646 \u062a\u0634\u06a9\u0631 \u0645\u06cc\u06a9\u0646\u0645.", "output": "\u266a Porque tudo o que sempre tive \u266a \u2014 can\u00e7\u00f5es de reden\u00e7\u00e3o.", "explanation": "The Farsi sente... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1273 | https://huggingface.co/datasets/Lots-of-LoRAs/task1273_ted_translation_fa_pt | ted translation fa pt |
1604 | task1604_ethos_text_classification | Given a comment, classify it into a 'hate' speech or 'not hate' speech. Answer using 'hate' or 'not hate'. | [
"Toxic Language Detection"
] | [
"Social Media"
] | [
"ethos"
] | [
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Srija Macherla"
] | [{"input": "I hate women. All of them are useless.", "output": "hate", "explanation": "Gender discrimination is shown in this comment. Hence, it is classified as hate speech."}, {"input": "You look like a cow, stop eating!", "output": "hate", "explanation": "A person's looks are judged and commented in a hurtful way. T... | [{"input": "I don't dislike women i just think that they have nothing interesting to say. None reason for existence.", "output": "not hate", "explanation": "The comment discriminates women and doubts the existence of them which is a hate speech, so the output is incorrect."}, {"input": "Women have such obvious respect ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1604 | https://huggingface.co/datasets/Lots-of-LoRAs/task1604_ethos_text_classification | ethos text classification |
1274 | task1274_ted_translation_pt_en | You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into English. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Portuguese"
] | [
"English"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Os astr\u00f3nomos acreditam que cada estrela da gal\u00e1xia tem um planeta, e especulam que at\u00e9 um quinto deles tem um planeta do tipo da Terra que poder\u00e1 ter vida, mas ainda n\u00e3o vimos nenhum deles.", "output": "Astronomers now believe that every star in the galaxy has a planet, and they sp... | [{"input": "Agora: um, dois, tr\u00eas, vai.", "output": "So: one, two, four, go.", "explanation": "The Portugese sentence is not correctly translated into English. `tr\u00eas` is incorrectly translated as `four`, but it should have been `three`."}, {"input": "Eventualmente, vamos ver se teremos todos os sentidos human... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1274 | https://huggingface.co/datasets/Lots-of-LoRAs/task1274_ted_translation_pt_en | ted translation pt en |
1233 | task1233_ted_translation_ar_he | You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Hebrew. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Arabic"
] | [
"Hebrew"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u0648\u064a\u0645\u0643\u0646 \u0627\u0639\u0627\u062f\u0629 \u062a\u0643\u0631\u0627\u0631 \u0647\u0630\u0647 \u0627\u0644\u0639\u0645\u0644\u064a\u0629 \u0639\u0644\u0649 \u0637\u0648\u0644 \u0627\u0644\u0634\u0631\u064a\u0637 \u0644\u0643\u064a \u0646\u0637\u0628\u0642 \u0634\u0631\u064a\u0637 \u0627\u0... | [{"input": "\u0645\u062b\u0644 \u060c \u0623\u062d\u0628 \u0643\u0644 \u0634\u0626 \u062d\u0648\u0644\u0647. \u0625\u0646\u0647 \u0645\u0630\u0647\u0644.", "output": "\u05d0\u05ea\u05dd \u05d9\u05db\u05d5\u05dc\u05d9\u05dd \u05dc\u05e6\u05d9\u05d9\u05e8, \u05db\u05de\u05d5 \u05e9\u05db\u05dc \u05d0\u05d7\u05d3 \u05e6\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1233 | https://huggingface.co/datasets/Lots-of-LoRAs/task1233_ted_translation_ar_he | ted translation ar he |
1099 | task1099_ted_translation_ja_pt | You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Portugese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Japanese"
] | [
"Portuguese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u3053\u306e\u30a2\u30a4\u30c7\u30a2\u306f\u3068\u3066\u3082\u30b7\u30f3\u30d7\u30eb\u3067", "output": "A ideia \u00e9 muito, muito simples.", "explanation": "The Japanese sentence is correctly translated into Portugese, because the meaning is preserved."}, {"input": "\u5f7c\u3089\u306f\u305d\u306e\u884c\u3... | [{"input": "\u4eca\u65e5\u79c1\u304c\u3054\u63d0\u6848\u3059\u308b\u88fd\u54c1\u306f\u5b9f\u306f\u305d\u308c\u5358\u4f53\u3067\u4f7f\u3046\u306e\u3067\u306f\u306a\u304f", "output": "V\u00eaem aqui o que eram tr\u00eas quil\u00f3metros de litoral abandonado, degradado nos bairros de Greenpoint e de Williamsburg, em Broo... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1099 | https://huggingface.co/datasets/Lots-of-LoRAs/task1099_ted_translation_ja_pt | ted translation ja pt |
1324 | task1324_open_subtitles_te_en_translation | The task is about translation from Telugu to English. While performing the translation you must preserve the original meaning. Do not include any words which are only limited to your native place. | [
"Translation"
] | [
"Commonsense -> Concepts and Relations",
"Dialogue",
"Narrative"
] | [
"opensubtitles"
] | [] | [
"Telugu"
] | [
"English"
] | [
"English"
] | [
"Yammanur Abhilash Reddy"
] | [{"input": "\u0c05\u0c28\u0c47\u0c15\u0c35\u0c3f\u0c02\u0c24\u0c2a\u0c41\u0c30\u0c3e\u0c23\u0c2e\u0c41\u0c32\u0c41 \u0c2d\u0c3e\u0c30\u0c24\u0c26\u0c47\u0c36\u0c02 \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c08 \u0c05\u0c30\u0c23\u0c4d\u0c2f \u0c2f\u0c4a\u0c15\u0c4d\u0c15 \u0c1a\u0c46\u0c2a\u0c4d\u0c2a\u0c2c\u0c21\u0c4d\u0c21\u... | [{"input": "\u0c37\u0c47\u0c30\u0c4d \u0c16\u0c3e\u0c28\u0c4d \u0c24\u0c2a\u0c4d\u0c2a\u0c28\u0c3f\u0c38\u0c30\u0c3f\u0c17\u0c3e \u0c2c\u0c3e\u0c32\u0c41\u0c21\u0c41 \u0c1a\u0c02\u0c2a\u0c21\u0c3e\u0c28\u0c3f\u0c15\u0c3f \u0c2e\u0c30\u0c3f\u0c2f\u0c41 \u0c05\u0c24\u0c21\u0c41 \u0c30\u0c15\u0c4d\u0c37\u0c3f\u0c02\u0c1a\... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1324 | https://huggingface.co/datasets/Lots-of-LoRAs/task1324_open_subtitles_te_en_translation | open subtitles te en translation |
338 | task338_hateeval_classification_individual_es | In this task, you are given a hateful post in Spanish from online platforms. You are expected to classify the target being harassed in the post as individual or generic, i.e., single person or a group of people. Note that the URLs in the text have been replaced with [Link]. | [
"Toxic Language Detection"
] | [
"Social Media -> Twitter"
] | [
"hateeval"
] | [] | [
"Spanish"
] | [
"English"
] | [
"English"
] | [
"Xudong Shen"
] | [{"input": "Post: @Darkeph Ella es m\u00e1s bonita, t\u00fa eres m\u00e1s perra.", "output": "Individual", "explanation": "This post should be classified as individual because it is hateful towards the person that this post replies to."}, {"input": "Post: Que ladilla esos malditos \u00e1rabes con su llamadera por fb.",... | [{"input": "Post: EN TU CARA ZORRA", "output": "Generic", "explanation": "This post should be classified as individual because it disrespects the person the post is replying to, rather than a group of people."}, {"input": "Post: No son subsaharianos, son Negros. Que yo sepa, Sud\u00e1n y N\u00edger est\u00e1n en el S\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task338 | https://huggingface.co/datasets/Lots-of-LoRAs/task338_hateeval_classification_individual_es | hateeval classification individual es |
684 | task684_online_privacy_policy_text_information_type_generation | Given a part of privacy policy text, identify the type of personal information which is collected, used, tracked or retained. The type of information should be present inside the given policy text, answer as 'Not Specified' otherwise | [
"Information Extraction"
] | [
"Law"
] | [
"opp_115"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Sai Surya Kaushik, Punyamurthula"
] | [{"input": "The site collects your cookies or tracking elements for a basic service or feature. Collection happens in an unspecified way, and your data is aggregated or anonymized.", "output": "Cookies and tracking elements", "explanation": "The type of user information collected is clearly stated in the given policy t... | [{"input": "You can choose not to use a service or feature to avoid the use of unspecified information by an unspecified party for an unspecified purpose.", "output": "Location", "explanation": "The returned type of user information is not stated in the given policy text. It is stated that 'unspecified information' is ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task684 | https://huggingface.co/datasets/Lots-of-LoRAs/task684_online_privacy_policy_text_information_type_generation | online privacy policy text information type generation |
371 | task371_synthetic_product_of_list | In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list. | [
"Program Execution"
] | [
"Code",
"Mathematics"
] | [
"synthetic"
] | [
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[[5, 1, 2, 7], [0, 4, 6, 6], [7, 8, 10, 3, 1], [1, 4]]", "output": "[70, 0, 1680, 4]", "explanation": "The second list had zero so the second product is zero. Every product is calculated correctly: 5x1x2x7= 70, 7x8x10x3x1=1680, 1x4=4."}, {"input": "[[9, 9, 9], [-4, 5, 7, 3], [-8, -2, 10]]", "output": "[729,... | [{"input": "[[10, 6], [10, 5, 1, 9], [6, 5, 7, 3]]", "output": "[[60], [450], [630]]", "explanation": "The products are correctly calculated but the output is a list of lists. The output should be a list of integers."}, {"input": "[[0, 9, 7, 6], [-8, 0, 10], [1, -9, 9, 0, 7]]", "output": "[378, -80, -567]", "explanatio... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task371 | https://huggingface.co/datasets/Lots-of-LoRAs/task371_synthetic_product_of_list | synthetic product of list |
1481 | task1481_gene_extraction_bc2gm_dataset | In this task, you are given a sentence. You are expected to recognize the name of gene or protein. Although there might be several correct answers, you need to write one of them. | [
"Named Entity Recognition"
] | [
"Biology -> Bioinformatics"
] | [
"bc2gm_corpus"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Ishani Mondal"
] | [{"input": "Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development ", "output": "TCF - 1", "explanation": "The gene, TCF - 1 has been tagged as protein since it plays a crucial role in early thymocyte development."}, {"input": "The NF - ... | [{"input": "Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development", "output": "thymocyte", "explanation": "Thymocytes are the immune cells present in the thymus, before it undergoes transformation into a T cell. Therefore, it should not... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1481 | https://huggingface.co/datasets/Lots-of-LoRAs/task1481_gene_extraction_bc2gm_dataset | gene extraction bc2gm dataset |
990 | task990_pib_translation_urdu_marathi | A text is given in Urdu. Translate it from the Urdu language to the Marathi language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Urdu"
] | [
"Marathi"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u0627\u06cc\u0633\u06cc \u0648\u0642\u0641 \u0627\u0645\u0644\u0627\u06a9 \u062c\u0646 \u067e\u0631 \u0646\u0627\u062c\u0627\u0626\u0632 \u0637\u0648\u0631 \u067e\u0631 \u0642\u0628\u0636\u06c1 \u06a9\u06cc\u0627 \u062c\u0627\u0686\u06a9\u0627 \u06c1\u06d2 \u0627\u0646 \u06a9\u06cc \u0631\u06cc\u0627\u0633... | [{"input": "\u0627\u0633\u0631\u0627\u0626\u06cc\u0644 \u0645\u06cc\u06ba \u06a9\u0645\u06cc\u0648\u0646\u0679\u06cc \u0636\u06cc\u0627\u0641\u062a \u06a9\u06d2 \u062f\u0648\u0631\u0627\u0646 \u0648\u0632\u06cc\u0631\u0627\u0639\u0638\u0645 \u06a9\u06cc \u062a\u0642\u0631\u06cc\u0631 \u06a9\u0627 \u0645\u062a\u0646", "... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task990 | https://huggingface.co/datasets/Lots-of-LoRAs/task990_pib_translation_urdu_marathi | pib translation urdu marathi |
1092 | task1092_ted_translation_en_pl | You are given a sentence in English. Your job is to translate the English sentence into Polish. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"English"
] | [
"Polish"
] | [
"English"
] | [
"David Stap"
] | [{"input": "It's sort of the biggest TiVo box you've ever seen.", "output": "To najwi\u0119ksza nagrywarka, jak\u0105 w \u017cyciu widzieli\u015bcie.", "explanation": "The English sentence is correctly translated into Polish, because the meaning is preserved."}, {"input": "So those conversations, getting men engaged in... | [{"input": "And I was astonished, I was very angry, and I was deeply confused.", "output": "Mam szcz\u0119\u015bcie, bo jest lepszy od innych dzieci. Mam szcz\u0119\u015bcie, bo jest lepszy od innych dzieci.", "explanation": "The English sentence is not correctly translated into Polish, because the meaning is different... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1092 | https://huggingface.co/datasets/Lots-of-LoRAs/task1092_ted_translation_en_pl | ted translation en pl |
1228 | task1228_ted_translation_es_ar | You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Arabic. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Spanish"
] | [
"Arabic"
] | [
"English"
] | [
"David Stap"
] | [{"input": "A fines del verano estamos instalando el primer lote de computadoras y ayudando al Dr. Zullinger a desarrollar estrategias para poder conectar el aula y el hogar y extender el aprendizaje m\u00e1s all\u00e1 del d\u00eda escolar.", "output": "\u0641\u0627\u0644\u0641\u0631\u0642\u0629 \u0627\u0644\u0623\u064... | [{"input": "Ahora las horas se contraen; en primer lugar debido al retiro de los \"\" baby boomers \"\", y en segundo lugar porque ha habido un abandono significativo de los hombres adultos de la fuerza laboral, que est\u00e1n en la mitad inferior de la distribuci\u00f3n educativa.", "output": "\u0627\u0644\u0622\u0646... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1228 | https://huggingface.co/datasets/Lots-of-LoRAs/task1228_ted_translation_es_ar | ted translation es ar |
643 | task643_refresd_classification | Given an English and a French sentence, determine whether both sentences correspond, with 0 meaning divergent and 1 meaning equivalent. | [
"Text Matching"
] | [
"Miscellaneous"
] | [
"refresd"
] | [] | [
"English",
"French"
] | [
"English"
] | [
"English"
] | [
"Ian Lobo"
] | [{"input": "The invention of farming some 10,000 years ago led to the development of agrarian societies , whether nomadic or peasant , the latter in particular almost always dominated by a strong sense of traditionalism . <sep> En quelques d\u00e9cennies , l' activit\u00e9 \u00e9conomique de la vall\u00e9e est pass\u00... | [{"input": "The agency was near insolvency as a result of a 40 % fall in contributions since the inaugural of the private AFJP system , a new recession , and mounting lawsuits . <sep> La recession provoque un accroissement important des d\u00e9penses publiques ( 44 % du PIB ) avec la chute des investissements priv\u00e... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task643 | https://huggingface.co/datasets/Lots-of-LoRAs/task643_refresd_classification | refresd classification |
459 | task459_matres_static_classification | You will be given a context and a verb separated with a newline character, and you have to answer if the given verb is static or not. We say a verb is static if it is about an event that doesn't change or it happens regularly. The output should be "Yes" if the verb is static and "No" otherwise. | [
"Word Semantics"
] | [
"News"
] | [
"matres"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "New York (is) on the east coast. \n Verb: is", "output": "Yes", "explanation": "This is a good example. New York always is on the east coast."}, {"input": "Suspected bombs exploded outside the U.S. embassies in the Kenyan and Tanzanian capitals Friday, (killing) dozens of people, witnesses said. \n Verb: ki... | [{"input": "He (is) a brave man. \n Verb: is", "output": "No", "explanation": "Being brave is static, so the answer is incorrect."}, {"input": "In Washington today, the Federal Aviation Administration (released) air traffic control tapes from the night the TWA Flight eight hundred went down. \n Verb: released", "output... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task459 | https://huggingface.co/datasets/Lots-of-LoRAs/task459_matres_static_classification | matres static classification |
558 | task558_alt_translation_en_hi | In this task, given a sentence in the English language, your task is to convert it into the Hindi language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Hindi"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "The Prince, who is also an officer in the navy, is being treated only as a witness in this case, there have been no charges against him.", "output": "\u0930\u093e\u091c\u0915\u0941\u092e\u093e\u0930, \u091c\u094b \u0928\u094c\u0938\u0947\u0928\u093e \u092e\u0947\u0902 \u090f\u0915 \u0905\u0927\u093f\u0915\u... | [{"input": "The mining company says that a lift electrical cable broke on a basket that was carrying miners, trapping thousands at least 2,200 meters (1.3 miles) below the earth's surface.", "output": "\u0909\u0928\u094d\u0939\u094b\u0902\u0928\u0947 \u0915\u0939\u093e \u0915\u093f \u0935\u0939 \u091a\u093f\u0902\u0924... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task558 | https://huggingface.co/datasets/Lots-of-LoRAs/task558_alt_translation_en_hi | alt translation en hi |
1359 | task1359_numer_sense_answer_generation | Given a sentence, fill out the missing word with a 'no' or a number (between zero and ten). You should write the numbers with english alphabet, like: four instead of 4. | [
"Fill in The Blank"
] | [
"Commonsense -> Concepts and Relations",
"Animals"
] | [
"numersense"
] | [
"Commonsense Reasoning -> Numerical Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Krishna Sree G"
] | [{"input": "Female snakes incubate eggs inside of their bodies, giving birth to live young of ____ or more.", "output": "ten", "explanation": "Snakes give birth to minimum ten young ones so ten is a correct answer."}, {"input": "Latin verbs have ____ principal parts.", "output": "four", "explanation": "This is a fact a... | [{"input": "Nothing can move faster than light in either the ____ spatial dimensions or time.", "output": "five", "explanation": "In this world we have only three dimensions so five is a wrong answer."}, {"input": "Oxygen atoms can have ____ different masses.", "output": "two", "explanation": "As oxygen has three diffe... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1359 | https://huggingface.co/datasets/Lots-of-LoRAs/task1359_numer_sense_answer_generation | numer sense answer generation |
814 | task814_pawsx_japanese_korean_translation | Given a sentence in Japanese, provide an equivalent paraphrased translation in Korean that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Japanese"
] | [
"Korean"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "1975 - 76\u5e74\u306eNBA\u30b7\u30fc\u30ba\u30f3\u306f\u3001\u5168\u7c73\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb\u5354\u4f1a\u306e30\u756a\u76ee\u306e\u30b7\u30fc\u30ba\u30f3\u3067\u3057\u305f\u3002", "output": "National Basketball Association\uc758 1975 - 76 \uc2dc\uc98c\uc740 NBA\uc758 30 \ubc88... | [{"input": "1560\u5e7410\u6708\u306b\u30d1\u30ea\u3067\u3001\u5f7c\u306f\u5bc6\u304b\u306b\u30b9\u30b3\u30c3\u30c8\u30e9\u30f3\u30c9\u3092\u901a\u3063\u3066\u30a4\u30f3\u30b0\u30e9\u30f3\u30c9\u306b\u623b\u308b\u305f\u3081\u306b\u30d1\u30b9\u30dd\u30fc\u30c8\u3092\u5f7c\u306b\u6c42\u3081\u3066\u3001\u82f1\u56fd\u5927\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task814 | https://huggingface.co/datasets/Lots-of-LoRAs/task814_pawsx_japanese_korean_translation | pawsx japanese korean translation |
551 | task551_alt_translation_en_th | In this task, given a sentence in the English language, your task is to convert it into the Thai language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Thai"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "Some protesters taunted riot police, who responded with stun grenades.", "output": "\u0e1c\u0e39\u0e49\u0e1b\u0e23\u0e30\u0e17\u0e49\u0e27\u0e07\u0e1a\u0e32\u0e07\u0e04\u0e19\u0e25\u0e49\u0e2d\u0e40\u0e25\u0e35\u0e22\u0e19\u0e15\u0e33\u0e23\u0e27\u0e08\u0e1b\u0e23\u0e32\u0e1a\u0e08\u0e25\u0e32\u0e08\u0e25 \... | [{"input": "Israeli Prime Minister Benjamin Netanyahu actively pushed for a military strike on Iran, according to a report published in the Israeli newspaper Haaretz on Thursday.", "output": "\"\u0e1e\u0e27\u0e01\u0e40\u0e23\u0e32\u0e2a\u0e19\u0e31\u0e1a\u0e2a\u0e19\u0e38\u0e19\u0e43\u0e2b\u0e49\u0e21\u0e35\u0e01\u0e32... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task551 | https://huggingface.co/datasets/Lots-of-LoRAs/task551_alt_translation_en_th | alt translation en th |
1686 | task1686_menyo20k_translation | This task is about translating a given Yoruba language sentence to English. | [
"Translation"
] | [
"News",
"TED Talks",
"Captions -> Video Captions",
"Natural Science"
] | [
"menyo20k_mt"
] | [] | [
"Yoruba"
] | [
"English"
] | [
"English"
] | [
"Siddhesh Jagtap"
] | [{"input": "L\u00f3de \u00f2n\u00ed gbaj\u00fabaj\u00e0 ni \u00e0w\u1ecdn \u00e0\u1e63\u1eb9 CC l\u00f3r\u00ed ay\u00e9luj\u00e1ra t\u00ed \u00e0w\u1ecdn on\u00ed\u1e63\u1eb9\u0301-\u1ecdp\u1ecdl\u1ecd j\u00e1k\u00e8j\u00e1d\u00f2 il\u00e9-ay\u00e9 s\u00ec \u0144 l\u00f2 w\u1ecd\u0301n f\u00fan \u00e8y\u00ed-\u00f2-j\u... | [{"input": "\u00ccm\u1ecd\u0300-\u1eb9\u0300r\u1ecd m\u00fa u r\u1ecdr\u00f9n f\u00fan \u00e0w\u1ecdn \u1eb9gb\u1eb9l\u1eb9m\u00f9k\u00f9 \u00e8n\u00ecy\u00e0n l\u00e1ti lo \u00e0w\u1ecdn \u00e0k\u00f3\u00f3n\u00fa or\u00ed \u1eb9\u0300r\u1ecd-ay\u00e9luj\u00e1ra l\u1eb9\u0301r\u00ecnkann\u00e1\u00e0, t\u00ed w\u1ecd\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1686 | https://huggingface.co/datasets/Lots-of-LoRAs/task1686_menyo20k_translation | menyo20k translation |
1202 | task1202_atomic_classification_xneed | In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | [
"Commonsense Classification"
] | [
"Sociology",
"Commonsense -> Concepts and Relations -> Social Commonsense"
] | [
"atomic"
] | [
"Relational Reasoning",
"Reasoning on Social Interactions",
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "Head: PersonX is at PersonY's friend's house<sep>Tail: to walk up to PersonY's friend's house", "output": "Yes", "explanation": "This is a good example. PersonX is at PersonY's friend's house. But before, PersonX needed to walk up to PersonY's friend's house."}, {"input": "Head: PersonX bats PersonX's eyela... | [{"input": "Head: PersonX asks PersonY's boyfriend<sep>Tail: scared", "output": "Yes", "explanation": "PersonX doesn't need to be scared before asking PersonY's boyfriend. So the output should be \"No\"."}, {"input": "Head: PersonX holds hands<sep>Tail: to go near him", "output": "No", "explanation": "PersonX needs to ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1202 | https://huggingface.co/datasets/Lots-of-LoRAs/task1202_atomic_classification_xneed | atomic classification xneed |
441 | task441_eng_guj_parallel_corpus_gu-en_language_identification | In this task, you are given a sentence which is either in the Gujarati language or English language. You task is to identify the language of input sentence. Input sentence can be in Gujarari or English language only and also it cannot have two languages at a time. | [
"Language Identification"
] | [
"Captions -> Image Captions"
] | [
"eng_guj_parallel_corpus"
] | [] | [
"Gujarati",
"English"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "A herd of sheep standing together grazing in a pasture.", "output": "English", "explanation": "Input sentence is in English language."}, {"input": "\u0aa4\u0acd\u0aaf\u0abe\u0a82 \u0a8f\u0a95 \u0aae\u0aae\u0acd\u0aae\u0ac0 \u0a9c\u0abf\u0ab0\u0abe\u0aab \u0aa4\u0ac7\u0aa8\u0abe \u0aac\u0abe\u0ab3\u0a95 \u0a... | [{"input": "A herd of sheep standing together grazing in a pasture.", "output": "Cannot identify the language.", "explanation": "Answer should be Gujarati or English."}, {"input": "\u0aa4\u0acd\u0aaf\u0abe\u0a82 \u0a8f\u0a95 \u0aae\u0aae\u0acd\u0aae\u0ac0 \u0a9c\u0abf\u0ab0\u0abe\u0aab \u0aa4\u0ac7\u0aa8\u0abe \u0aac\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task441 | https://huggingface.co/datasets/Lots-of-LoRAs/task441_eng_guj_parallel_corpus_gu-en_language_identification | eng guj parallel corpus gu-en language identification |
415 | task415_mickey_bg_sentence_perturbation_generation | Given a sentence in Bulgarian, generate a new Bulgarian sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of ... | [
"Sentence Perturbation"
] | [
"Commonsense",
"Knowledge Base -> Wikidata"
] | [
"xcsr"
] | [] | [
"Bulgarian"
] | [
"Bulgarian"
] | [
"English"
] | [
"Maitreya Patel"
] | [{"input": "\u0412\u0438\u0435 \u043c\u043e\u0436\u0435\u0442\u0435 \u0434\u0430 \u043f\u043b\u0430\u043d\u0438\u0440\u0430\u0442\u0435 \u0435\u0434\u043d\u0430 \u0448\u0430\u043f\u043a\u0430 \u043f\u043e\u0440\u0442\u0444\u0435\u0439\u043b, \u0437\u0430 \u0434\u0430 \u043d\u043e\u0441\u044f\u0442 \u0432\u0441\u0438\u0... | [{"input": "\u041c\u043e\u0436\u0435\u0442\u0435 \u0434\u0430 \u0438\u0437\u043f\u043e\u043b\u0437\u0432\u0430\u0442\u0435 \u0445\u0430\u0440\u0434\u0443\u0435\u0440\u0435\u043d \u0435\u043b\u0435\u043c\u0435\u043d\u0442, \u0437\u0430 \u0434\u0430 \u0438\u043c\u0430\u0442 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u043... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task415 | https://huggingface.co/datasets/Lots-of-LoRAs/task415_mickey_bg_sentence_perturbation_generation | mickey bg sentence perturbation generation |
374 | task374_synthetic_pos_or_neg_calculation | In this task you will be given a list of integers. For every element in the list, if the element is positive you should multiply it by 2. If the element is negative you should multiply it by -3. The output should be a list of integers that is the result of applying that logic to the input list.
Note: A list is presen... | [
"Program Execution"
] | [
"Code",
"Mathematics"
] | [
"synthetic"
] | [
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[-7, -1, 8, 7, -8]", "output": "[21, 3, 16, 14, 24]", "explanation": "Every negative number is multiplied by -3 and every positive number is multiplied by 2. So this is a good example."}, {"input": "[6, 0, 9, -4]", "output": "[12, 0, 18, 12]", "explanation": "The rules are applied correctly for positive/neg... | [{"input": "[-5, 8, 0]", "output": "[-5, 8, 0, 15, 16, 0]", "explanation": "The output appended the new values to the input list. So this is a bad example."}, {"input": "[-9, -1, 6, 7, 9]", "output": "[-18, -2, -18, -21, -27]", "explanation": "The output multiplied negative numbers by 2 and positive numbers by -3. So t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task374 | https://huggingface.co/datasets/Lots-of-LoRAs/task374_synthetic_pos_or_neg_calculation | synthetic pos or neg calculation |
1117 | task1117_alt_ja_id_answer_generation | Given a sentence in the Japanese and Indonesian(Bahasa variant) language. Your task is check if the Bahasa Indonesia sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No". | [
"Text Matching"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"Japanese",
"Indonesian"
] | [
"English"
] | [
"English"
] | [
"Savan Doshi"
] | [{"input": "Japanese: \u8a73\u7d30\u306f\u6628\u65e5UTC17\u664230\u5206\u3001\u82f1\u56fd\u8b70\u4f1a\u3067\u30a4\u30ae\u30ea\u30b9\u306e\u30eb\u30b9\u30fb\u30b1\u30ea\u30fc\u904b\u8f38\u5927\u81e3\u306b\u3088\u3063\u3066\u4f1d\u3048\u3089\u308c\u305f\u3002 \n Bahasa Indonesia: Detil diberikan oleh Sekretaris Kementeri... | [{"input": "Japanese: \u30a4\u30ae\u30ea\u30b9\u306e\u653f\u6cbb\u95a2\u4fc2\u8005\u306f\u3001\u3053\u306e\u60c5\u5831\u306e\u7d1b\u5931\u305d\u306e\u3082\u306e\u306b\u3064\u3044\u3066\u3082\u3001\u653f\u5e9c\u304c\u60c5\u5831\u3092\u5b89\u5168\u306b\u53ce\u96c6\u3057\u3001\u4fdd\u6301\u3059\u308b\u80fd\u529b\u306b\u30... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1117 | https://huggingface.co/datasets/Lots-of-LoRAs/task1117_alt_ja_id_answer_generation | alt ja id answer generation |
783 | task783_pawsx_korean_english_translation | Given a sentence in Korean, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Korean"
] | [
"English"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "1975 \ub144\ubd80\ud130 76 \ub144\uae4c\uc9c0 NBA \uc2dc\uc98c\uc740 \uc804\uad6d \ub18d\uad6c \ud611\ud68c (National Basketball Association)\uc758 30 \ubc88\uc9f8 \uc2dc\uc98c\uc774\uc5c8\ub2e4.", "output": "The 1975 -- 76 season of the National Basketball Association was the 30th season of the NBA .", "ex... | [{"input": "1560 \ub144 10 \uc6d4 \ud30c\ub9ac\uc5d0\uc11c \uadf8\ub294 \ube44\ubc00\ub9ac\uc5d0 \uc601\uad6d \ub300\uc0ac \uc778 \ub2c8\ucf5c\ub77c\uc2a4 \ud2b8\ub85d \ubaa8\ud2bc\uc744 \ub9cc\ub0ac\uace0 \uc2a4\ucf54\ud2c0\ub79c\ub4dc\ub97c \ud1b5\ud574 \uc601\uad6d\uc73c\ub85c \ub3cc\uc544\uac08 \uc5ec\uad8c\uc744 \... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task783 | https://huggingface.co/datasets/Lots-of-LoRAs/task783_pawsx_korean_english_translation | pawsx korean english translation |
622 | task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | In this task, you are given an input list A. You need to convert all the alphabets in the list with a number representing their position in the English alphabet. E.g., replace A by 1, B by 2, a by 1, b by 2, and so on. | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Pulkit Verma"
] | [{"input": "['8129', 'a', '4245', '2391', 'Y', '7569']", "output": "8129, 1, 4245, 2391, 25, 7569", "explanation": "Here, the alphabets in the list are 'a' and 'Y', hence we replace them by their positions in the English alphabet '1' and '25', respectively in the input list to get '8129, 1, 4245, 2391, 25, 7569'."}, {"... | [{"input": "['5367', 'w', 'X', '3467', 'g']", "output": "23, 24, 7", "explanation": "Here, the answer should have been '5367, 23, 24, 3467, 7' as the alphabets in the list are 'w', 'X', and 'g', hence we replace them by their positions in the English alphabet '23', '24', and '7', respectively in the input list to get '... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task622 | https://huggingface.co/datasets/Lots-of-LoRAs/task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | replace alphabets in a list by their position in english alphabet |
1554 | task1554_scitail_classification | In this task, you are given two statements. The task is to output whether a given textual premise, i.e. Statement 2, entails or implies a given scientific fact, i.e. Statement 1. The output should be 'entails' if Statement 2 supports Statement 1 and should be 'neutral' otherwise. | [
"Textual Entailment"
] | [
"Web",
"Natural Science -> School Science Textbooks"
] | [
"scitail"
] | [
"Textual Entailment -> Deductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Nishtha Bhimte"
] | [{"input": "Sentence 1: The sum of all chemical reactions that take place within an organism is known as metabolism. Sentence 2: Metabolism is the sum total of all chemical reactions performed by an organism.", "output": "entails", "explanation": "Sentence 2 gives out supporting information about the Metabolism hence i... | [{"input": "Sentence 1: A fewer predators is most likely to cause the number of rabbits living in an area to increase. Sentence 2: A predator of rodents, rabbits, birds and the like, this is a sizeable snake.", "output": "entails", "explanation": "Sentence 2 doesn't give out more information about the Sentence 1 or sup... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1554 | https://huggingface.co/datasets/Lots-of-LoRAs/task1554_scitail_classification | scitail classification |
174 | task174_spl_translation_en_ja | The provided file includes inquiries about restaurants, and we ask you to translate those to the Japanese language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloq... | [
"Translation"
] | [
"Public Places"
] | [
"semantic_parser_localizer"
] | [] | [
"English"
] | [
"Japanese"
] | [
"English"
] | [
"Mehrad Moradshahi"
] | [{"input": "are there any \" italian \" restaurants nearby with 4 star reviews ?", "output": "\u8fd1\u304f\u306b4\u3064\u661f\u8a55\u4fa1\u306e\" italian \"\u30ec\u30b9\u30c8\u30e9\u30f3\u306f\u3042\u308b\uff1f", "explanation": "The translation correctly preserves \" italian \" entity and is accurate"}, {"input": "what... | [{"input": "where is the closest \" wendy 's \" ?", "output": "\u6700\u5bc4\u308a\u306ewendy 's\u306f\uff1f", "explanation": "Translation contain the entity \" wendy 's \" but quotation marks are dropped"}, {"input": "show me the closest \" mcdonald 's \"", "output": "\u6700\u5bc4\u308a\u306e\" McDonald's \"\u3092\u898... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task174 | https://huggingface.co/datasets/Lots-of-LoRAs/task174_spl_translation_en_ja | spl translation en ja |
1223 | task1223_ted_translation_ja_es | You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Spanish. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Japanese"
] | [
"Spanish"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u305d\u308c\u306f\u500b\u4eba\u306e\u5185\u9762\u3067\u8d77\u3053\u308b\u95d8\u3044\u60aa \uff64 \u7f6a \uff64 \u8a98\u60d1 \uff64 \u6b32\u671b \uff64 \u8caa\u6b32\u306b\u5bfe\u3059\u308b\u82e6\u95d8\u3067\u3059\u305d\u308c\u306f\u500b\u4eba\u306e\u5185\u9762\u3067\u8d77\u3053\u308b\u95d8\u3044\u60aa \uff6... | [{"input": "\u305d\u306e\u3046\u3061 \uff13 \uff5e 10\u6b73\u306e\u5b50\u3069\u3082\u304c\u3044\u308b \u2015 \u30c6\u30fc\u30d6\u30eb\u3078\u306f\u6226\u95d8\u614b\u52e2\u3067\u81e8\u3080\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f", "output": "Algunos de ellos tienen entre 5 y 10 a\u00f1os; ahora est\u00e1n listos... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1223 | https://huggingface.co/datasets/Lots-of-LoRAs/task1223_ted_translation_ja_es | ted translation ja es |
774 | task774_pawsx_german_text_modification | Given a sentence in German, provide an equivalent paraphrased version from the original that retains the same meaning. | [
"Paraphrasing"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"German"
] | [
"German"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "Die NBA-Saison 1975 - 76 war die 30. Saison der National Basketball Association.", "output": "Die Saison 1975 - 76 der National Basketball Association war die 30. Saison der NBA.", "explanation": "The paraphrase of the original sentence in German is correct and accurate because even though sentence order ha... | [{"input": "Im Oktober 1560 traf er sich in Paris heimlich mit dem englischen Botschafter Nicolas Throckmorton und bat ihn um einen Pass, um durch Schottland nach England zur\u00fcckzukehren.", "output": "Im Oktober 1560 traf er sich heimlich mit dem englischen Botschafter Nicolas Throckmorton in Paris und bat ihn um e... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task774 | https://huggingface.co/datasets/Lots-of-LoRAs/task774_pawsx_german_text_modification | pawsx german text modification |
432 | task432_alt_en_hi_translation | In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun). | [
"Translation"
] | [
"Public Places"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Hindi"
] | [
"English"
] | [
"Savan Doshi"
] | [{"input": "Italy have defeated Portugal 31-5 in Pool C of the 2007 Rugby World Cup at Parc des Princes, Paris, France.", "output": "2007 \u092e\u0947\u0902 \u092b\u093c\u094d\u0930\u093e\u0902\u0938, \u092a\u0947\u0930\u093f\u0938 \u0915\u0947 \u092a\u093e\u0930\u094d\u0915 \u0921\u0947\u0938 \u092a\u094d\u0930\u093f\... | [{"input": "Portugal never gave up and David Penalva scored a try in the 33rd minute, providing their only points of the match.", "output": "\u091c\u0940\u0924 \u0928 \u092e\u093e\u0928\u0924\u0947 \u0939\u0941\u090f, \u092a\u0941\u0930\u094d\u0924\u0917\u093e\u0932 \u0915\u0947 \u0921\u0947\u0935\u093f\u0921 \u092a\u0... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task432 | https://huggingface.co/datasets/Lots-of-LoRAs/task432_alt_en_hi_translation | alt en hi translation |
1725 | task1725_civil_comments_severtoxicity_classification | Categorize the comment on the basis of severe toxicity. If the comment is severely toxic output Yes, otherwise output No. | [
"Toxic Language Detection"
] | [
"Dialogue",
"Social Media"
] | [
"civil_comments"
] | [
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Himanshu Asati"
] | [{"input": "First off IDIOTS HIS HONDA IS NOT STOLEN I HAVE THE TITLE SIGNED OFF BY LAST OWNER IN MY POSSESSION.2ND THE ONLY THING HE WAS IN TROUBLE FOR BEFORE THE CHASE WAS FOR NOT CHECKING IN WITH HIS PROBATION OFFICER WHICH BRINGS THIS FACT TO LIGHT.YOU CAN DOWNLOAD DOUGLAS COUNTY PROBATION DEPARTMENT LIST OF CURREN... | [{"input": "FFFFUUUUUUUUUUUUUUU", "output": "No", "explanation": "The comment is abbreviation of 'Fuck You' which is toxic, but classified as not severly toxic. Therefore, this is a negative example."}, {"input": "Yeah, that man would look pretty ridiculous, given that 80% of congress, 95% of Fortune 500 CEOs, and 100%... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1725 | https://huggingface.co/datasets/Lots-of-LoRAs/task1725_civil_comments_severtoxicity_classification | civil comments severtoxicity classification |
208 | task208_combinations_of_list | In this task, you will be given a list. The list is several integers and letters separated with a comma, written within a []. You can create new lists by dropping one of the items in the input list. Your task is to write a list containing all the possible lists you can make by dropping one item from the input list. Fo... | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [
"Numerical Reasoning",
"Mathematics -> Combinatorics"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "['3', 'u', 'W', '8', 'j']", "output": "[['3', 'u', 'W', '8'], ['3', 'u', 'W', 'j'], ['3', 'u', '8', 'j'], ['3', 'W', '8', 'j'], ['u', 'W', '8', 'j']]", "explanation": "The output is a list of length 5, containing lists of length 4. Each inner list is created by dropping one item if the input list. So this i... | [{"input": "['j', 'I', 'U']", "output": "[['j'], ['I'], ['U']]", "explanation": "In this example, the inner lists of the output have been created by dropping two elements from the input list. If we drop an item from the input list, we will have a list with two items each time. So this is a bad example."}, {"input": "['... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task208 | https://huggingface.co/datasets/Lots-of-LoRAs/task208_combinations_of_list | combinations of list |
265 | task265_paper_reviews_language_identification | In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link]. | [
"Language Identification"
] | [
"Conference"
] | [
"paper_reviews_data_set"
] | [] | [
"Spanish",
"English"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar",
"Pegah Alipoormolabashi"
] | [{"input": "Este art\u00edculo no es un art\u00edculo de investigaci\u00f3n, ya que s\u00f3lo muestra c\u00f3mo programar un robot mediante la herramienta de l\u00f3gica difusa. Este tema ya ha sido propuesto como soluci\u00f3n en navegaci\u00f3n de robots.", "output": "es", "explanation": "This review is written in sp... | [{"input": "Este art\u00edculo no es un art\u00edculo de investigaci\u00f3n, ya que s\u00f3lo muestra c\u00f3mo programar un robot mediante la herramienta de l\u00f3gica difusa. Este tema ya ha sido propuesto como soluci\u00f3n en navegaci\u00f3n de robots.", "output": "en", "explanation": "This review is written in sp... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task265 | https://huggingface.co/datasets/Lots-of-LoRAs/task265_paper_reviews_language_identification | paper reviews language identification |
1110 | task1110_ted_translation_he_gl | You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Galician. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Hebrew"
] | [
"Galician"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\"\u05d0\u05d6,\" \u05d0\u05de\u05e8\u05ea\u05d9, \"\u05d6\u05d4 \u05db\u05de\u05d5 \u05d7\u05dc\u05d5\u05dd?\" \u05d5\u05d4\u05d9\u05d0 \u05d0\u05de\u05e8\u05d4, \"\" \u05dc\u05d0, \u05d6\u05d4 \u05dc\u05d0 \u05db\u05de\u05d5 \u05d7\u05dc\u05d5\u05dd. \u05d6\u05d4 \u05db\u05de\u05d5 \u05e1\u05e8\u05d8. \"\... | [{"input": "\u05db\u05d5\u05dc\u05dd, \u05d1\u05e2\u05d9\u05e7\u05e8 \u05db\u05e9\u05d4\u05d4\u05ea\u05e4\u05e8\u05e6\u05d5\u05ea \u05d4\u05ea\u05d7\u05d9\u05dc\u05d4 \u05dc\u05d4\u05ea\u05e4\u05e9\u05d8 \u05d2\u05dc\u05d5\u05d1\u05dc\u05d9\u05ea, \u05e4\u05e0\u05d5 \u05d0\u05dc\u05d9\u05e0\u05d5 \u05d1\u05db\u05d3\u05... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1110 | https://huggingface.co/datasets/Lots-of-LoRAs/task1110_ted_translation_he_gl | ted translation he gl |
801 | task801_pawsx_german_english_translation | Given a sentence in German, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"German"
] | [
"English"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "Die NBA-Saison 1975 - 76 war die 30. Saison der National Basketball Association.", "output": "The 1975 -- 76 season of the National Basketball Association was the 30th season of the NBA .", "explanation": "This is a correct and accurate translation from German to English because the translated paraphrase re... | [{"input": "Im Oktober 1560 traf er sich in Paris heimlich mit dem englischen Botschafter Nicolas Throckmorton und bat ihn um einen Pass, um durch Schottland nach England zur\u00fcckzukehren.", "output": "In October 1560 , he secretly met with the English ambassador , Nicolas Throckmorton , in Paris , and asked him for... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task801 | https://huggingface.co/datasets/Lots-of-LoRAs/task801_pawsx_german_english_translation | pawsx german english translation |
354 | task354_casino_classification_negotiation_no_need | The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | [
"Negotiation Strategy Detection"
] | [
"Dialogue"
] | [
"casino"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kushal Chawla"
] | [{"input": "Context: \nUtterance: 'how about I give you 2 waters and 1 food package in exchange for all your firewood?'", "output": "No", "explanation": "The utterance does not use the no-need strategy since it never refers to an item that the participant does not need."}, {"input": "Context: 'Hi, how are you?' 'Great,... | [{"input": "Context: 'Hello'\nUtterance: 'Hello! How are you doing today?'", "output": "Yes", "explanation": "The utterance does not contain the no-need strategy. The correct answer is 'No'."}, {"input": "Context: 'Hello, what are your preferences for extra supplies? I am greatly in need of food and water. We will be... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task354 | https://huggingface.co/datasets/Lots-of-LoRAs/task354_casino_classification_negotiation_no_need | casino classification negotiation no need |
604 | task604_flores_translation_entosn | In this task, you will be given text in English. You need to translate the text into the Sinhali language. | [
"Translation"
] | [
"Miscellaneous"
] | [
"flores"
] | [] | [
"English"
] | [
"Sinhala"
] | [
"English"
] | [
"Nikhitha Munugala"
] | [{"input": "When ventricles systole, blood flows to the pulmonary artery or the greater aorta. ", "output": "\u0d9a\u0ddd\u0dc2\u0dd2\u0d9a\u0dcf \u0d89\u0dc4\u0dd2\u0dbd\u0dca\u0dc0\u0db1 \u0dc0\u0dd2\u0da7, \u0db0\u0db8\u0db1\u0dd2\u0dba\u0dda \u0dc3\u0dd2\u0da7 \u0d9a\u0ddd\u0dc2\u0dd2\u0d9a\u0dcf\u0dc0 \u0dc0\u0dd9... | [{"input": "A special membrane called perkin fibers help to transmit this signal to the ventricle.", "output": "\u0db1\u0db8\u0dd4\u0dad\u0dca \u0dc4\u0dd8\u0daf \u0db4\u0dca \u0dbb\u0dad\u0dd2\u0d9a\u0dcf\u0dbb \u0dc3\u0db3\u0dc4\u0dcf \u0db1\u0ddc\u0dba\u0dd9\u0d9a\u0dd4\u0dad\u0dca \u0dc0\u0dd9\u0db1\u0dad\u0dca \u0... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task604 | https://huggingface.co/datasets/Lots-of-LoRAs/task604_flores_translation_entosn | flores translation entosn |
1241 | task1241_ted_translation_gl_ar | You are given a sentence in Galician. Your job is to translate the Galician sentence into Arabic. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"Arabic"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u00c9 basicamente un caldeiro que rota.", "output": "\u0648\u064a\u0648\u062c\u062f \u0623\u0633\u0627\u0633\u0627 \u0645\u0631\u062c\u0644 \u062f\u0648\u0627\u0631.", "explanation": "The Galician sentence is correctly translated into Arabic, because the meaning is preserved."}, {"input": "Ou queiman os pl... | [{"input": "Os im\u00e1ns est\u00e1n a\u00ed dentro.", "output": "\u0641\u064a\u0646\u0641\u0639\u0644 \u0623\u0648\u062f\u064a\u0633\u064a\u0648\u0633 \u0648\u064a\u0642\u0648\u0644 \u0644\u0647 \u0623\u064a\u0647\u0627 \u0627\u0644\u0627\u062d\u0645\u0642 \u0623\u064a\u0647\u0627 \u0627\u0644\u063a\u0628\u064a", "exp... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1241 | https://huggingface.co/datasets/Lots-of-LoRAs/task1241_ted_translation_gl_ar | ted translation gl ar |
1664 | task1664_winobias_text_generation | In this task, you will be given a sentence, and you need to identify the set of coreference words. Coreferences are generally a set of words in the text that refer to the same person or thing. Your output set of coreference words must be strictly present in the given input sentence. Do not use any outside knowledge to ... | [
"Coreference Resolution"
] | [
"Professions",
"Commonsense"
] | [
"wino_bias"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Saradhi Kiran Amarthi"
] | [{"input": "The developer argued with the designer because he did not like the design.", "output": "The, developer, he", "explanation": "Here the output set of coreference words 'The', 'developer, and 'he' refer to the same person, and these are coreferences. So, the output is correct."}, {"input": "The mechanic greets... | [{"input": "The cook is always teaching the assistant new techniques because he likes to teach others.", "output": "The, assistant, others", "explanation": "Here the output set of coreference words 'The', 'assistant, and 'others' do not refer to the same person, and these are coreferences. So, the output is incorrect."... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1664 | https://huggingface.co/datasets/Lots-of-LoRAs/task1664_winobias_text_generation | winobias text generation |
036 | task036_qasc_topic_word_to_generate_related_fact | In this task, you need to write a topic word from the given fact. The topic word must have at least one word overlap with the given fact. The topic word often involves adding a new word from a related concept. In your topic word, use at least one word from the given fact. Topic words with two or more words work best. | [
"Keyword Tagging"
] | [
"Natural Science"
] | [
"qasc"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Swaroop Mishra",
"Daniel Khashabi"
] | [{"input": "Fact: pesticides cause pollution.", "output": "pollution harms.", "explanation": "This is a good topic word, because it contains one overlapping word \"pollution\"."}, {"input": "Fact: pesticides cause pollution.", "output": "modern farming pesticide.", "explanation": "The word \"pesticide\" is the overlapp... | [{"input": "Fact: pesticides cause pollution.", "output": "computer harms.", "explanation": "This is a bad topic word, because it has no overlapping word with the given fact."}, {"input": "Fact: pesticides cause pollution.", "output": "toopaste helps.", "explanation": "This is a bad topic word, because it has no overla... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task036 | https://huggingface.co/datasets/Lots-of-LoRAs/task036_qasc_topic_word_to_generate_related_fact | qasc topic word to generate related fact |
654 | task654_bible_fa_en_translation | In this task, you are given a sentence from the Bible in Persian, and your task is to translate it into English. | [
"Translation"
] | [
"World Religions",
"Books"
] | [
"parsinlu"
] | [] | [
"Persian"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "\u062f\u0631 \u0627\u0628\u062a\u062f\u0627\u060c \u062e\u062f\u0627 \u0622\u0633\u0645\u0627\u0646\u0647\u0627 \u0648 \u0632\u0645\u06cc\u0646 \u0631\u0627 \u0622\u0641\u0631\u06cc\u062f.", "output": "In the beginning God created the heaven and the earth.", "explanation": "This is a good example. The above... | [{"input": "\u0648 \u062e\u062f\u0627 \u0631\u0648\u0634\u0646\u0627\u06cc\u06cc \u0631\u0627 \u062f\u06cc\u062f \u06a9\u0647 \u0646\u06cc\u06a9\u0648\u0633\u062a \u0648 \u062e\u062f\u0627\u0631\u0648\u0634\u0646\u0627\u06cc\u06cc \u0631\u0627 \u0627\u0632 \u062a\u0627\u0631\u06cc\u06a9\u06cc \u062c\u062f\u0627 \u0633\... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task654 | https://huggingface.co/datasets/Lots-of-LoRAs/task654_bible_fa_en_translation | bible fa en translation |
1191 | task1191_food_veg_nonveg | In this task, you are given the name of an Indian food dish. You need to return whether the dish is "non vegetarian" or "vegetarian". Do not answer with any words other than those two. | [
"Misc."
] | [
"Food"
] | [
"indian_food_101"
] | [
"Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Ravsehaj Singh Puri"
] | [{"input": "Balu shahi", "output": "vegetarian", "explanation": "Balu shahi is a vegetarian dish."}, {"input": "Pork Bharta", "output": "non vegetarian", "explanation": "Pork Bharta contains pork and is a non vegetarian dish."}] | [{"input": "Malapua", "explanation": "Malapua is not a non vegetarian dish", "output": "non vegetarian"}, {"input": "Kadhai Chicken", "explanation": "Kadhai Chicken is not a vegetarian dish", "output": "vegetarian"}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1191 | https://huggingface.co/datasets/Lots-of-LoRAs/task1191_food_veg_nonveg | food veg nonveg |
735 | task735_mmmlu_answer_generation_us_foreign_policy | You are given a question on US foreign policy. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer. | [
"Question Answering"
] | [
"US Foreign Policy"
] | [
"measuring_massive_multitask_language_understanding"
] | [
"Scientific Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Sujan Reddy A"
] | [{"input": "What is the structure of the United Nations Security Council?\n(A)5 permanent members with veto power, 10 rotating members with no veto power (B)5 permanent members and 10 rotating members, all with veto power (C)10 permanent members with veto power, and 5 rotating members without veto power (D)15 permanent... | [{"input": "What is the structure of the United Nations Security Council?\n(A)5 permanent members with veto power, 10 rotating members with no veto power (B)5 permanent members and 10 rotating members, all with veto power (C)10 permanent members with veto power, and 5 rotating members without veto power (D)15 permanent... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task735 | https://huggingface.co/datasets/Lots-of-LoRAs/task735_mmmlu_answer_generation_us_foreign_policy | mmmlu answer generation us foreign policy |
831 | task831_giga_fren_classification | In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no". | [
"Text Matching"
] | [
"Miscellaneous"
] | [
"giga_fren"
] | [] | [
"English",
"French"
] | [
"English"
] | [
"English"
] | [
"Abhijeet Nawale"
] | [{"input": "English: What can I do? \n French: Que puis je faire?", "output": "yes", "explanation": "English sentence is properly converted into French sentence."}, {"input": "English: What are some themes for your display? \n French: Qu\u2019\u00eates-vous pr\u00eats \u00e0 faire pour favoriser l\u2019av\u00e8nement d... | [{"input": "English: What is the link between isotopes and hair? \n French: Quel lien existe-t-il entre les isotopes et les cheveux?", "output": "Correct", "explanation": "The answer can only be yes or no."}, {"input": "English: What are some of your next steps for securing additional resources? \n French: Quelles sont... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task831 | https://huggingface.co/datasets/Lots-of-LoRAs/task831_giga_fren_classification | giga fren classification |
562 | task562_alt_language_identification | In this task, an input sentence is given which can be in the English, Bengali, Filipino, Hindi, Indonesian(Bahasa variant), Japanese, Central Khmer, Lao, Malay, Burmese, Thai, Vietnamese or Chinese languages. There are a total of 13 languages. Your task is to identify the language of the input sentence. The input sente... | [
"Language Identification"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English",
"Bengali",
"Filipino",
"Hindi",
"Indonesian",
"Japanese",
"Central Khmer",
"Lao",
"Malay",
"Burmese",
"Thai",
"Vietnamese",
"Chinese"
] | [
"English"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "Kenneth Goldman is suing the United States Democratic political action committee Twenty-First Century Democrats (also 21st Century Democrats) and its former executive director Kelly Young.", "output": "English", "explanation": "Input sentence is in the English language."}, {"input": "\u09e8\u09e6\u09e7\u09e... | [{"input": "Ang radyo sa Israel ay nakapuna na ito ay ang ikatlong Palestinong bata sa loob ng dalawang buwan na nahuli na nagtatangkang magpuslit ng mga pampasabog lampas ng tsekpoint na Israeli.", "output": "Cannot identify the language", "explanation": "Input sentence should be in one of the 13 languages which are E... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task562 | https://huggingface.co/datasets/Lots-of-LoRAs/task562_alt_language_identification | alt language identification |
458 | task458_matres_negation_classification | You will be given a context and a verb separated with a newline character, and you have to answer if the given verb is a negation or not. A verb is a negation if it is not going to exist, not happen, or has no effect. The output should be "Yes" if the verb is a negation and "No" otherwise. | [
"Word Semantics"
] | [
"News"
] | [
"matres"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "Only the government of the United States can decide if it prefers this variant, continued the letter, which Castro read on a state television station broadcast. Gonzalez for months refused requests by Elian's Miami relatives to go to the United States to (claim) the boy. \n Verb: claim", "output": "Yes", "... | [{"input": "WASHINGTON ( AP ) -- Preliminary DNA tests link a missing anti-abortion activist to a strand of hair found near where a sniper shot and killed a Buffalo, N.Y., doctor who (performed) abortions, a law enforcement official said Friday. \n Verb: performed", "output": "Yes", "explanation": "In this sentence, t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task458 | https://huggingface.co/datasets/Lots-of-LoRAs/task458_matres_negation_classification | matres negation classification |
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