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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
965 | task965_librispeech_asr_missing_word_prediction | You are given an English sentence with a blank, and you need to predict the missing word. After completing, the whole sentence should be gramatically correct and non-ambiguous. | [
"Fill in The Blank"
] | [
"Books"
] | [
"librispeech_asr,"
] | [
"Abductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Surya Singulur"
] | [{"input": "The kid on the street is ____ soccer", "output": "playing", "explanation": "This is the original sentence 'The kid on the street is playing soccer' So, we have correctly predicted the missing word to be 'soccer'"}, {"input": "Joey's favourite food is ____", "output": "sandwiches", "explanation": "This is th... | [{"input": "How have ____ been?", "output": "very", "explanation": "This is a bad example because we need to predict 'you' to fill in the blank, but we have predicted 'very'"}, {"input": "It's gonne be a ____ day!", "output": "Glass", "explanation": "This is a bad example because we need to predict 'long' to fill in th... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task965 | https://huggingface.co/datasets/Lots-of-LoRAs/task965_librispeech_asr_missing_word_prediction | librispeech asr missing word prediction |
1498 | task1498_24hour_to_12hour_clock | You are given a time in 24-Hours format, and you need to convert it to time in the 12-Hours format. For a 24-Hours format time larger than 12:00, subtract 12 hours from the given time, then add 'PM'. For example, if you have 14:30 hours, subtract 12 hours, and the result is 2:30 PM. If the 24-Hours format time is less... | [
"Misc."
] | [
"Commonsense -> Concepts and Relations"
] | [
"synthetic"
] | [
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Amit Sharma"
] | [{"input": "19:00 Hrs", "output": "07:00 PM", "explanation": "For a 24-Hours format time larger than 12:00, we should subtract 12 hours from the given time, then add 'PM'. So, the output is correct."}, {"input": "11:50 Hrs", "output": "11:50 AM", "explanation": "The given time is less than 12:00. So, we should just add... | [{"input": "17:00 Hrs", "output": "17:00 PM", "explanation": "The input 24-hour time has not been converted to the 12-hour format. The correct output should be 05:00 PM."}, {"input": "13:30 Hrs", "output": "13:30 AM", "explanation": "The input 24-hour time has not been converted to the 12-hour format. The correct outpu... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1498 | https://huggingface.co/datasets/Lots-of-LoRAs/task1498_24hour_to_12hour_clock | 24hour to 12hour clock |
584 | task584_udeps_eng_fine_pos_tagging | In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are fine labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is : '$': D... | [
"Pos Tagging"
] | [
"News"
] | [
"universal_dependencies___english_dependency_treebank"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Siddhartha Mishra"
] | [{"input": "Sentence: Those things ended up being a windsheild washer fluid tank {{ ( }} 1 screw ) and the air filter canister ( 4 spring clips ) . \nWord: (", "output": "-LRB-", "explanation": "\"(\" is the symbol for Left Parantheses (-LRB-)."}, {"input": "Sentence: I melt brass and cast it {{ http://www.mikegigi.com... | [{"input": "Sentence: It s between sea {{ and }} mountains so you can camp on beach or between mountains ! \nWord: and", "output": "VB", "explanation": "\"and\" is not a Verb (VB) since it does not signal an action/event."}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task584 | https://huggingface.co/datasets/Lots-of-LoRAs/task584_udeps_eng_fine_pos_tagging | udeps eng fine pos tagging |
462 | task462_qasper_classification | In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering ab... | [
"Question Understanding"
] | [
"Scientific Research Papers"
] | [
"qasper"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "We build a dataset of Twitter accounts based on two lists annotated in previous works. For the non-factual accounts, we rely on a list of 180 Twitter accounts from BIBREF1. On the other hand, for the factual accounts, we use a list with another 32 Twitter accounts from BIBREF19 that are considered trustwort... | [{"input": "For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two dif... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task462 | https://huggingface.co/datasets/Lots-of-LoRAs/task462_qasper_classification | qasper classification |
1442 | task1442_doqa_movies_isanswerable | Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question has a prefix... | [
"Answerability Classification"
] | [
"Movies",
"Dialogue"
] | [
"doqa"
] | [
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kuntal Kumar Pal"
] | [{"input": "CONTEXT: I think it's deliberately ambiguous. If it's real, the inconsistencies are easily explained by Vidal's fascist belief system. These elements simply are not part of his world. If it's fantasy, then of course only Ofelia can see these thing because she imagined them. I think part of Del Toro's purpos... | [{"input": "CONTEXT: Logan's plan earlier in the movie was to buy a sailboat and sail to the ocean with the Professor, where they would spend their last days. Out on the sea, the Professor wouldn't pose a threat to other humans when he lost his control over his ability. If I am not mistaken the Professor liked that ide... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1442 | https://huggingface.co/datasets/Lots-of-LoRAs/task1442_doqa_movies_isanswerable | doqa movies isanswerable |
1048 | task1048_pib_translation_telugu_english | A text is given in English. Translate it from the English language to the Telugu language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Telugu"
] | [
"English"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u0c2b\u0c3f\u0c02\u0c17\u0c30\u0c4d \u0c2a\u0c4d\u0c30\u0c3f\u0c02\u0c1f\u0c4d \u0c2c\u0c4d\u0c2f\u0c42\u0c30\u0c4b\u0c15\u0c4d\u0c38\u0c4d \u0c21\u0c48\u0c30\u0c15\u0c4d\u0c1f\u0c30\u0c4d\u0c32 19 \u0c35 \u0c05\u0c16\u0c3f\u0c32 \u0c2d\u0c3e\u0c30\u0c24 \u0c38\u0c26\u0c38\u0c4d\u0c38\u0c41 \u0c2a\u0c4d\u0... | [{"input": "\u0c15\u0c3e\u0c28\u0c40, \u0c07\u0c2a\u0c4d\u0c2a\u0c41\u0c21\u0c41 \u0c21\u0c47\u0c1f\u0c3e \u0c38\u0c4d\u0c2a\u0c40\u0c21\u0c4d \u0c17\u0c41\u0c30\u0c3f\u0c02\u0c1a\u0c3f \u0c1a\u0c30\u0c4d\u0c1a\u0c3f\u0c38\u0c4d\u0c24\u0c41\u0c28\u0c4d\u0c28\u0c3e\u0c30\u0c41", "output": "I urge the citizens of Surat t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1048 | https://huggingface.co/datasets/Lots-of-LoRAs/task1048_pib_translation_telugu_english | pib translation telugu english |
1491 | task1491_bengali_political_hate_speech_binary_classification | In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: political or non-political depending on the top... | [
"Text Categorization"
] | [
"Social Media",
"Dialogue"
] | [
"bengali_hate_speech_dataset"
] | [
"Reasoning on Social Interactions"
] | [
"Bengali"
] | [
"English"
] | [
"English"
] | [
"Ishani Mondal"
] | [{"input": "\u0996\u09be\u09a8\u0995\u09bf\u09b0 \u09aa\u09c1\u09b2\u09be \u09ae\u09be\u09b2\u09be\u09df\u09a8\u09a6\u09c7\u09b0 \u09ae\u09c7\u09b0\u09c7 \u09b8\u09be\u09ab\u09be \u0995\u09b0\u09c7 \u09ab\u09c7\u09b2", "output": "political", "explanation": "Here it expresses hate against the government, hence tagged as... | [{"input": "\u098f\u0987 \u09b8\u09b0\u0995\u09be\u09b0 \u0995\u09c7 \u09af\u09be\u09b0\u09be \u09a8\u09bf\u09b0\u09cd\u09b2\u099c\u09cd\u099c\u09c7\u09b0 \u09ae\u09a4 \u09b8\u09be\u09aa\u09cb\u09b0\u09cd\u099f \u09a6\u09bf\u09df\u09c7\u099b\u09c7 \u09ac\u099b\u09b0\u09c7\u09b0 \u09aa\u09b0 \u09ac\u099b\u09b0, \u09a4\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1491 | https://huggingface.co/datasets/Lots-of-LoRAs/task1491_bengali_political_hate_speech_binary_classification | bengali political hate speech binary classification |
995 | task995_pib_translation_bengali_english | A text is given in Bengali. Translate it from the Bengali language to the English language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Bengali"
] | [
"English"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u09a6\u09b0\u09bf\u09a6\u09cd\u09b0, \u09aa\u09cd\u09b0\u09be\u09a8\u09cd\u09a4\u09bf\u0995 \u098f\u09ac\u0982 \u09a6\u09c7\u09b6\u09c7\u09b0 \u09aa\u09b2\u09cd\u09b2\u09c0 \u0985\u099e\u09cd\u099a\u09b2\u09c7\u09b0 \u09b8\u09c7\u09ac\u09be\u09af\u09bc \u09a4\u09bf\u09a8\u09bf \u099b\u09bf\u09b2\u09c7\u09a... | [{"input": "\u09aa\u09bf \u09ad\u09bf \u09a8\u09b0\u09b8\u09bf\u0982\u09b9 \u09b0\u09be\u0993-\u0995\u09c7 \u09a4\u09be\u0981\u09b0 \u099c\u09a8\u09cd\u09ae\u09ac\u09be\u09b0\u09cd\u09b7\u09bf\u0995\u09c0\u09a4\u09c7 \u09b8\u09cd\u09ae\u09b0\u09a3 \u0995\u09b0\u09b2\u09c7\u09a8 \u09aa\u09cd\u09b0\u09a7\u09be\u09a8\u09a... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task995 | https://huggingface.co/datasets/Lots-of-LoRAs/task995_pib_translation_bengali_english | pib translation bengali english |
105 | task105_story_cloze-rocstories_sentence_generation | In this task, you're given a four sentences of story written in natural language. Your job is to complete end part of the story by predicting appropriate last sentence which is coherent with the given sentences. | [
"Text Completion"
] | [
"Story",
"Commonsense"
] | [
"pib"
] | [
"Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mirali Purohit"
] | [{"input": "Sentence1: Rick grew up in a troubled household. Sentence2: He never found good support in family, and turned to gangs. Sentence3: It wasn't long before Rick got shot in a robbery. Sentence4: The incident caused him to turn a new leaf.", "output": "He is happy now.", "explanation": "As mentioned in last sen... | [{"input": "Sentence1: Rick grew up in a troubled household. Sentence2: He never found good support in family, and turned to gangs. Sentence3: It wasn't long before Rick got shot in a robbery. Sentence4: The incident caused him to turn a new leaf.", "output": "He joined a gang.", "explanation": "As mentioned in last se... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task105 | https://huggingface.co/datasets/Lots-of-LoRAs/task105_story_cloze-rocstories_sentence_generation | story cloze-rocstories sentence generation |
1364 | task1364_hans_answer_generation | In this task, you are given a premise sentence. Your task is to write a new sentence by substituting the subject and object (i.e., the input's subject should be output's object and vice versa.). The generated sentence must be fluent and shouldn't change the voice (i.e., passive or active) of the input. | [
"Sentence Composition"
] | [
"Reviews -> Movies",
"Movies"
] | [
"hans"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Devshree Patel"
] | [{"input": "The doctors supported the scientist .", "output": "The scientist supported the doctors .", "explanation": "The output uses the verbs and nouns from the premise and changes the object with the subject. This is a good example."}, {"input": "The athletes introduced the tourist .", "output": "The tourist introd... | [{"input": "The judge encouraged the athlete .", "output": "The athlete was encouraged by the judge .", "explanation": "The output changes the voice of the input, thus it is not a correct answer."}, {"input": "The lawyers called the judge.", "output": "The judge was called by the people .", "explanation": "The output d... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1364 | https://huggingface.co/datasets/Lots-of-LoRAs/task1364_hans_answer_generation | hans answer generation |
292 | task292_storycommonsense_character_text_generation | In this task, you're given a story (which contains five sentences only). Your task is to find all the characters which are available in the given story. | [
"Information Extraction"
] | [
"Story"
] | [
"storycommonsense"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mirali Purohit"
] | [{"input": "Sentence1: My dog was bored. Sentence2: I was working all day so I couldn't spend time with him. Sentence3: When I finished work I decided to play with my dog. Sentence4: He was so happy to finally have some fun! Sentence5: Alas, he fell sick and died.", "output": "I (myself), Dog", "explanation": "There is... | [{"input": "Sentence1: I arranged to meet Mormon missionaries today. Sentence2: They were delivering a free Book of Mormon. Sentence3: I met two young men from Utah. Sentence4: They gave me the book and posed for a photo. Sentence5: I posted the photo on Facebook.", "output": "Utah", "explanation": "Utah is not charact... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task292 | https://huggingface.co/datasets/Lots-of-LoRAs/task292_storycommonsense_character_text_generation | storycommonsense character text generation |
866 | task866_mawps_multidiv_question_answering | You are given a math word problem and you are supposed to apply multiplication or division mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer. | [
"Question Answering"
] | [
"Mathematics"
] | [
"nlu_asdiv_dataset"
] | [
"Numerical Reasoning",
"Quantitative Reasoning",
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Tanay Dixit"
] | [{"input": "Maria has 3 boxes of eggs . Each box holds 7 eggs and there are 8 boxes in a case . How many eggs does Maria have ?", "output": "21", "explanation": "Total number of eggs that Maria has is 3*7 = 21"}, {"input": "Tom had 56 dollars how many 4 dollar toys could he buy with the money he had left ?", "output":... | [{"input": "Each ticket costs $ 9 . How much do 4 tickets cost ?", "output": "9", "explanation": "4 tickets would cost = cost of each ticket*total tickets = 9*4 = 36"}, {"input": "If Victor split 25 Skittles between 5 people in her class and kept the left overs , how many Skittles did each classmate get ?", "output": "... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task866 | https://huggingface.co/datasets/Lots-of-LoRAs/task866_mawps_multidiv_question_answering | mawps multidiv question answering |
1346 | task1346_glue_cola_grammatical_correctness_classification | You will be given a sentence. Check whether the sentence is grammatically correct and is meaningful. If the sentence is grammatically correct, then answer with '1', otherwise answer with '0'. | [
"Grammar Error Detection"
] | [
"Books",
"Dialogue"
] | [
"cola"
] | [
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Arit Chanda"
] | [{"input": "Our friends won't buy this analysis, let alone the next one we propose.", "output": "1", "explanation": "Since all the entities are in thier correct positions the statement is grammatically correct.Hence, the output is 1."}, {"input": "One more pseudo generalization and I'm giving up.", "output": "1", "expl... | [{"input": "The most you want, the least you eat.", "output": "1", "explanation": "The word \"most\" makes the statement incorrect. So the output should've been 0 for incorrect."}, {"input": "The dog barked out of the room.", "output": "1", "explanation": " This statement doesn't make any sense. The statement should've... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1346 | https://huggingface.co/datasets/Lots-of-LoRAs/task1346_glue_cola_grammatical_correctness_classification | glue cola grammatical correctness classification |
1640 | task1640_aqa1.0_answerable_unanswerable_question_classification | Given a paragraph from a Wikipedia article about some topic, and a question related to the topic, determine whether the question is answerable from the paragraph. If the question is answerable, answer "True", otherwise, answer "False". | [
"Answerability Classification"
] | [
"Wikipedia"
] | [
"adversarial_qa"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Suchit Jain"
] | [{"input": "Another approach to brain function is to examine the consequences of damage to specific brain areas. Even though it is protected by the skull and meninges, surrounded by cerebrospinal fluid, and isolated from the bloodstream by the blood\u2013brain barrier, the delicate nature of the brain makes it vulnerab... | [{"input": "NASCAR (headquartered in Daytona Beach) begins all three of its major auto racing series in Florida at Daytona International Speedway in February, featuring the Daytona 500, and ends all three Series in November at Homestead-Miami Speedway. Daytona also has the Coke Zero 400 NASCAR race weekend around Indep... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1640 | https://huggingface.co/datasets/Lots-of-LoRAs/task1640_aqa1.0_answerable_unanswerable_question_classification | aqa1.0 answerable unanswerable question classification |
313 | task313_europarl_en_sv_translation | In this task, you are given a sentence in the English language and your task is to convert it into the Swedish language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun). | [
"Translation"
] | [
"Government and Politics"
] | [
"europarl"
] | [] | [
"English"
] | [
"Swedish"
] | [
"English"
] | [
"Mirali Purohit"
] | [{"input": "The debate is closed.", "output": "Jag f\u00f6rklarar debatten avslutad.", "explanation": "English sentence is properly converted into Swedish sentence."}, {"input": "Thank you very much, Commissioner.", "output": "Tack s\u00e5 mycket, fru kommission\u00e4r.", "explanation": "English sentence is properly co... | [{"input": "The debate is closed.", "output": "Jag f\u00f6rklarar avslutad.", "explanation": "The conversion of English to Swedish is wrong because output missed one part from the input, i.e., debate."}, {"input": "Thank you very much, Commissioner.", "output": "Inga problem, fru kommission\u00e4r.", "explanation": "Th... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task313 | https://huggingface.co/datasets/Lots-of-LoRAs/task313_europarl_en_sv_translation | europarl en sv translation |
775 | task775_pawsx_chinese_text_modification | Given a sentence in Chinese, provide an equivalent paraphrased version from the original that retains the same meaning. | [
"Paraphrasing"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Chinese"
] | [
"Chinese"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "1975\u5e74\u7684NBA\u8d5b\u5b63 - 76\u8d5b\u5b63\u662f\u5168\u7f8e\u7bee\u7403\u534f\u4f1a\u7684\u7b2c30\u4e2a\u8d5b\u5b63\u3002", "output": "1975-76\u8d5b\u5b63\u7684\u5168\u56fd\u7bee\u7403\u534f\u4f1a\u662fNBA\u7684\u7b2c30\u4e2a\u8d5b\u5b63\u3002", "explanation": "The paraphrase of the original sentenc... | [{"input": "1560\u5e7410\u6708\uff0c\u4ed6\u5728\u5df4\u9ece\u79d8\u5bc6\u4f1a\u89c1\u4e86\u82f1\u56fd\u5927\u4f7fNicolas Throckmorton\uff0c\u8981\u6c42\u4ed6\u901a\u8fc7\u82cf\u683c\u5170\u8fd4\u56de\u82f1\u56fd\u3002", "output": "1560\u5e7410\u6708\uff0c\u4ed6\u5728\u5df4\u9ece\u79d8\u5bc6\u4f1a\u89c1\u4e86\u82f1\u56... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task775 | https://huggingface.co/datasets/Lots-of-LoRAs/task775_pawsx_chinese_text_modification | pawsx chinese text modification |
246 | task246_dream_question_generation | In this task, you will be shown a conversation. You need to write a question with three choices for the conversation. Your question should be answerable based on the conversation and only have one correct answer. Note that you don't need to answer your question. "W" and "M" in the conversations stand for "woman" and "m... | [
"Question Generation"
] | [
"Dialogue",
"Natural Science -> School Science Textbooks"
] | [
"dream"
] | [
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "W: The movie next Tuesday has been cancelled due to lack of interest. M: What do you mean? W: Well, by last night only a few tickets has been sold.", "output": "What can we conclude about the movie? (A) They want to buy the tickets for the movie. (B) The tickets for the movie were sold. (C) The movie will n... | [{"input": "W: Can I help you? M: I'm looking for some suit that I can wear at the office as well as on weekends. W: Let me show you a new summer collection. There're several styles that you're just looking for.", "output": "What is the color of suit? (A) Black (B) Brown (C) Red", "explanation": "This question is not a... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task246 | https://huggingface.co/datasets/Lots-of-LoRAs/task246_dream_question_generation | dream question generation |
838 | task838_cdt_classification | Given a text from Polish tweets, classify given tweet text into two categories: '1' (bullying), and '0' (not bullying) on its content. | [
"Toxic Language Detection"
] | [
"Social Media -> Twitter"
] | [
"cdt"
] | [
"Commonsense Reasoning -> Social Situations",
"Reasoning on Social Interactions"
] | [
"Polish"
] | [
"English"
] | [
"English"
] | [
"Sai Surya Akhilesh, Amara Venkata"
] | [{"explanation": "The tweet contains Bullying content", "input": "@anonymized_account @anonymized_account @anonymized_account Gdzie jest @anonymized_account . Brudzi\u0144ski jeste\u015b k\u0142amc\u0105 i marnym kutasem @anonymized_account", "output": "1"}, {"explanation": "The tweet does not contain Bullying content"... | [{"explanation": "The tweet contains Bullying content", "input": "@anonymized_account @anonymized_account No to Sko\u0144czmy kurwa z tym wersalem w j...ej szczujni", "output": "0"}, {"explanation": "The tweet does not contain Bullying content", "input": "@anonymized_account @anonymized_account Brawo ty Daria kibic ma ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task838 | https://huggingface.co/datasets/Lots-of-LoRAs/task838_cdt_classification | cdt classification |
1516 | task1516_imppres_naturallanguageinference | In this task, you are given a premise and hypothesis. The task is to classify them into three categories: 'positive' if the hypothesis supports the premise, 'negated' if it opposes the premise, and 'neutral' if it neither supports nor opposes it. | [
"Textual Entailment"
] | [
"Commonsense"
] | [
"imppres"
] | [
"Textual Entailment"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Vivek Bellalacharvu Srinivasa Rao"
] | [{"input": "'Premise : All ten guys that proved to boast were divorcing.','Hypothesis : There are exactly ten guys that proved to boast.'", "output": "positive", "explanation": "The output of the given hypothesis and hremise is 'Positive' as the hypothesis supports the premise in a 'Positive' way. In the premise it is ... | [{"input": "'Premise : If all ten guys that proved to boast were divorcing, it's okay.','Hypothesis : There are exactly ten guys that proved to boast.'", "output": "negated", "explanation": "The output is 'positive' not 'negated' as the hypothesis supports the premise in a 'positive' way. In the premise it is mentioned... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1516 | https://huggingface.co/datasets/Lots-of-LoRAs/task1516_imppres_naturallanguageinference | imppres naturallanguageinference |
1689 | task1689_qed_amara_translation | This task is about translating a given English language sentence to French. | [
"Translation"
] | [
"Captions -> Video Captions"
] | [
"qed_amara"
] | [] | [
"English"
] | [
"French"
] | [
"English"
] | [
"Siddhesh Jagtap"
] | [{"input": "How shall we inscribe intent on all the objects we create, on all the circumstances we create, on all the places we change?", "output": "Comment devrions nous inscrire l'intention sur tous les objets que nous cr\u00e9ons, sur toutes les circonstances que nous cr\u00e9ons, sur tous les lieux que nous changeo... | [{"input": "That development should not come at the expense of the majority of the population is still considered a radical idea here in the U.S.", "output": "Mosse c'est le syst\u00e8me \u00e9ducatif \u00e0 l'heure actuelle.", "explanation": "This is a bad example because the English sentence has not been translated c... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1689 | https://huggingface.co/datasets/Lots-of-LoRAs/task1689_qed_amara_translation | qed amara translation |
912 | task912_bianet_classification | In this task, we are given a sentence in either 'English' or 'Kurdish' languages and we have to determine what the language of the sentence is as output | [
"Language Identification"
] | [
"News"
] | [
"bianet"
] | [] | [
"English",
"Kurdish"
] | [
"English"
] | [
"English"
] | [
"Vivek Bellalacharvu Srinivasa Rao"
] | [{"input": "If we defend that it is not only Turks but many different peoples are living in a country in which suffering, oppression, and other things that shouldn\u2019t be seen in 21st century, and mention an understanding that defend that these peoples should develop without hurting each other, excluding each other\... | [{"input": "Par\u00eazer, Ozlem Gumu\u015fta\u015f\u00ea j\u00ee gotiye w\u00ea cara p\u00ea\u015fiy\u00ea dozeka bi v\u00ee reng\u00ee d\u00eetiye. Her kes di doze de ne heta ku niv\u00ees\u00ean b\u00eaniv\u00eeskar j\u00ee di dosyay\u00ea de hene.", "output": "English", "explanation": "This is a Negative example as ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task912 | https://huggingface.co/datasets/Lots-of-LoRAs/task912_bianet_classification | bianet classification |
1396 | task1396_europa_ecdc_tm_en_de_translation | In this task, you are given one english sentence. The major part of the sentences talk about health-related topics, but some of the them describe an organization and its activities. Your job is to translate the given sentences into German. | [
"Translation"
] | [
"Healthcare",
"Professions"
] | [
"europa_ecdc_tm"
] | [] | [
"English"
] | [
"German"
] | [
"English"
] | [
"Wen-Jui Mao"
] | [{"input": "Flu in birds is quite common.", "output": "Grippe bei V\u00f6geln kommt relativ h\u00e4ufig vor.", "explanation": "The translation is correct."}, {"input": "Tick-borne encephalitis", "output": "Zeckenenzephalitis", "explanation": "The translation is fluent, formal, and accurate."}, {"input": "Effective trea... | [{"input": "The bacteria are able to survive in the nature at a wide range of temperatures.", "output": "Der Direktor ist f\u00fcr die allgemeine Koordination und Leitung des ECDC zust\u00e4ndig.", "explanation": "The translation is incorrect."}, {"input": "Advisory forum Advisory Forum", "output": "Forum consultatif... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1396 | https://huggingface.co/datasets/Lots-of-LoRAs/task1396_europa_ecdc_tm_en_de_translation | europa ecdc tm en de translation |
139 | task139_detoxifying-lms_classification_topicality | Given a prompt and two completions from a language model, select the completion that is more topical with respect to continuing the prompt. A prompt-completion pair is defined to be topical if the completion maintains relevance and logical succession (i.e. stays on topic) with the prompt. The flow from the prompt to th... | [
"Text Completion"
] | [
"Social Media -> Twitter"
] | [
"detoxifying_lms"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Albert Xu",
"Eshaan Pathak",
"Eric Wallace",
"Suchin Gururangan",
"Maarten Sap",
"Dan Klein"
] | [{"input": "Prompt: Im 99 percent sure it was someone being an \nCompletion A: accomplice , or maybe just plain old con man . whatever it was , it 's over . \" \nCompletion B: asshole, your right?) but it's an awkward subject in which if you were in the trouble of \"me\", i mean \"fucking idiot\" jrgh... i dunno...I gu... | [{"input": "Prompt: Im 99 percent sure it was someone being an \nCompletion A: accomplice , or maybe just plain old con man . whatever it was , it 's over . \" \nCompletion B: asshole, your right?) but it's an awkward subject in which if you were in the trouble of \"me\", i mean \"fucking idiot\" jrgh... i dunno...I gu... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task139 | https://huggingface.co/datasets/Lots-of-LoRAs/task139_detoxifying-lms_classification_topicality | detoxifying-lms classification topicality |
1238 | task1238_ted_translation_gl_en | You are given a sentence in Galician. Your job is to translate the Galician sentence into English. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"English"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Agora, est\u00e1 ao lado, ou na mi\u00f1a casa.", "output": "Now, it's next door, or in my house.", "explanation": "The Galician sentence is correctly translated into English. `casa` is correctly translated as `house`."}, {"input": "Decat\u00e1monos de que con esa cor ti\u00f1amos unha marxe de maniobra.", ... | [{"input": "(Risas) (Aplausos) E probablemente unha chea de \u00e1rbores tam\u00e9n.", "output": "(Laughter) (Applause) And probably a whole bunch of trees as well.", "explanation": "The Galician sentence is not correctly translated into English. Information is missing, because `Risas`, which means `Laughter`, is not t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1238 | https://huggingface.co/datasets/Lots-of-LoRAs/task1238_ted_translation_gl_en | ted translation gl en |
1407 | task1407_dart_question_generation | In this task you are given a list of triplets of the form [subject, predicate, object] and the output should be a question based on the triplets but with the subject and/or object replaced with blanks (represented using two or more consecutive underscores). Triplet values encompassed in [*] are special tokens that can ... | [
"Data to Text"
] | [
"Wikipedia"
] | [
"dart"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Rushang Karia"
] | [{"input": "[['Northwestern College', 'NICKNAME', 'Red Raiders'], ['Northwestern College', 'LOCATION', 'Orange City, Iowa']]", "output": "The team whose nickname is red raiders is located in the _______", "explanation": "This sentence uses the triplets by correctly using the (subject, predicate, object) semantics for b... | [{"input": "[['Graham Edwards', 'PROVINCE', 'North Metropolitan']]", "output": "Edwards _____ the North Metropolitan Province.", "explanation": "This sentence is a bad example since it does not utilize the RDF triplet in the question making it open to interpretation. For example, this blank can be filled in several way... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1407 | https://huggingface.co/datasets/Lots-of-LoRAs/task1407_dart_question_generation | dart question generation |
844 | task844_financial_phrasebank_classification | Given a piece of financial news and its polarity, classify it into 'true' if the polarity is correct and classify into 'false' if the polarity is incorrect. Output must be 'true' or 'false'. | [
"Sentiment Analysis"
] | [
"News"
] | [
"financial_phrasebank"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Jalansh Munshi"
] | [{"input": "news:According to Gran , the company has no plans to move all production to Russia , although that is where the company is growing .\npolarity:neutral", "output": "true", "explanation": "Although the author uses negative words like 'no' in the news, there is no evidence of the news begin positive or negativ... | [{"input": "news:According to the company 's updated strategy for the years 2009-2012 , Basware targets a long-term net sales growth in the range of 20 % -40 % with an operating profit margin of 10 % -20 % of net sales .\npolarity:neutral", "output": "false", "explanation": "Here, the news uses terms like 'sales growth... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task844 | https://huggingface.co/datasets/Lots-of-LoRAs/task844_financial_phrasebank_classification | financial phrasebank classification |
1139 | task1139_xcsr_ru_commonsense_mc_classification | In this task, you will be presented with a question having multiple possible answers in Russian language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge. | [
"Question Answering"
] | [
"Commonsense"
] | [
"x_csr"
] | [
"Commonsense Reasoning"
] | [
"Russian"
] | [
"English"
] | [
"English"
] | [
"Maitreya Patel"
] | [{"input": "Question: \u0412 \u0441\u0442\u043e\u043c\u0430\u0442\u043e\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u043c \u043a\u0430\u0431\u0438\u043d\u0435\u0442\u0435 \u0440\u0430\u0431\u043e\u0442\u0430\u043b\u043e \u043c\u043d\u043e\u0433\u043e \u043f\u0430\u0446\u0438\u0435\u043d\u0442\u043e\u0432, \u0... | [{"input": "Question: \u0414\u0436\u043e\u043d \u043d\u0435 \u0437\u043d\u0430\u043b, \u0447\u0442\u043e \u043f\u043e\u0434\u0430\u0440\u0438\u0442\u044c \u043a\u043e\u043c\u0443-\u043d\u0438\u0431\u0443\u0434\u044c. \u041f\u043e\u043a\u0443\u043f\u043a\u0430 \u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u0435\u043d... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1139 | https://huggingface.co/datasets/Lots-of-LoRAs/task1139_xcsr_ru_commonsense_mc_classification | xcsr ru commonsense mc classification |
205 | task205_remove_even_elements | In this task you will be given a list of numbers. A list is shown by two brackets and comma-separated numbers inside, like: [1,2,3]. You should remove all of the even numbers from the list. If every number in the input list is even an empty list should be returned. Zero should be counted as an even number. | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [
"Quantitative Reasoning",
"Numerical Reasoning",
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[3, 0, 3, 8]", "output": "[3, 3]", "explanation": "Zero and eight are removed from the input list because they are even numbers, and because three appeared twice in the input list, it appears twice in the output list. So this is a good example."}, {"input": "[4, 10, 10]", "output": "[]", "explanation": "Eve... | [{"input": "[6, 4, 1, 5]", "output": "[6, 4]", "explanation": "The output contains only the even numbers from the input. So this is a bad example. Remember that you should remove the even elements and write the rest of the list."}, {"input": "[5, 0, 5, 6, 5]", "output": "[5]", "explanation": "The output only included o... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task205 | https://huggingface.co/datasets/Lots-of-LoRAs/task205_remove_even_elements | remove even elements |
1277 | task1277_ted_translation_pt_ar | You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Arabic. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Portuguese"
] | [
"Arabic"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Mas o que s\u00e3o direitos humanos?", "output": "\u0648\u0644\u0643\u0646 \u0645\u0627\u0647\u064a \u062d\u0642\u0648\u0642 \u0627\u0644\u0625\u0646\u0633\u0627\u0646 \u061f", "explanation": "The Portugese sentence is correctly translated into Arabic, because the meaning is preserved."}, {"input": "E v\u00... | [{"input": "Acho que todos veremos a aplica\u00e7\u00e3o cl\u00ednica desta tecnologia pelo menos, em adultos, dentro dos pr\u00f3ximos 10 anos.", "output": "\u0639\u0637\u0634\u0649 \u0644\u0623\u062c\u0644 \u0627\u0644\u0645\u0639\u0631\u0641\u0629 \u060c \u0648\u0627\u0644\u0641\u0631\u0635 \u060c \u0648\u0627\u0644... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1277 | https://huggingface.co/datasets/Lots-of-LoRAs/task1277_ted_translation_pt_ar | ted translation pt ar |
650 | task650_opus100_ar_en_translation | In this task, you are given a sentence in Arabic, and your task is to translate it into English. | [
"Translation"
] | [
"Dialogue"
] | [
"parsinlu"
] | [] | [
"Arabic"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "\u0623\u0645\u064a - \u0633\u0623\u0639\u0648\u062f \u0628\u0627\u0644\u062d\u0627\u0644 -", "output": "Mommy will be right back.", "explanation": "This is a good example. The above sentence is correctly translated from Arabic to English."}, {"input": "\u0647\u0644 \u0647\u064a \u0628\u062e\u064a\u0631\u061... | [{"input": "\u0625\u0645\u064a\u0631\u064a\u0644)\u060c \u0628\u0645 \u0623\u0646\u0643\u0650 \u0645\u0639\u064a)", "output": "Emeril.", "explanation": "This translation is incomplete. Hence it's not acceptable."}, {"input": "\u0647\u0648 \u0623\u0641\u0636\u0644\u064f.", "output": "They are better.", "explanation": "T... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task650 | https://huggingface.co/datasets/Lots-of-LoRAs/task650_opus100_ar_en_translation | opus100 ar en translation |
046 | task046_miscellaneous_question_typing | You are given a question-answer pair. Answer with their type. Pay attention that there may be more than one correct type, but you only have to choose one. In your responses, use of the following types:
(1) Humans: Any individual or group of humans, including fictional ones (e.g., a group or organization of persons , a... | [
"Question Understanding"
] | [
"Pop Culture",
"Natural Science",
"History",
"Law"
] | [
"miscellaneous"
] | [
"Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Swaroop Mishra",
"Daniel Khashabi"
] | [{"input": "Question: Melbourne has sustained the highest population increase and economic growth rate in any Australian city according to what organization? (Answer: Australian Bureau of Statistics).", "output": "Organization.", "explanation": "Here, the definition of the type \"Organization\" is \"an organized body ... | [{"input": "Question: Melbourne has sustained the highest population increase and economic growth rate in any Australian city according to what organization? (Answer: Australian Bureau of Statistics).", "output": "Association.", "explanation": "This is a bad answer as the word \"association\" is not part of our desired... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task046 | https://huggingface.co/datasets/Lots-of-LoRAs/task046_miscellaneous_question_typing | miscellaneous question typing |
025 | task025_cosmosqa_incorrect_answer_generation | Craft one incorrect answer. In doing so, try to use words from the context as much as possible, or by using similar words used in the correct answer. DO NOT craft nonsensical or off-topic incorrect answers, such that the incorrect answers can be directly excluded without reasoning according to the context. Try to make ... | [
"Wrong Candidate Generation"
] | [
"Personal Narratives"
] | [
"cosmosqa"
] | [
"Commonsense Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Swaroop Mishra",
"Daniel Khashabi"
] | [{"input": "Context: I was told, in person over the phone, that my shoes were on their way. They have my money. I have no shoes. \nQuestion: What may happen before I called them? \nCorrect answer: I found the money was charged but I have not got shoes.", "output": "I found the shoes were still on the way after several ... | [{"input": "Context: I was told , in person over the phone , that my shoes were on their way. They have my money. I have no shoes. \nQuestion: What may happen before I called them? \nCorrect answer: I found the money was charged but I still have not got the shoes.", "output": "I cooked my dinner.", "explanation": "This... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task025 | https://huggingface.co/datasets/Lots-of-LoRAs/task025_cosmosqa_incorrect_answer_generation | cosmosqa incorrect answer generation |
832 | task832_poleval2019_mt_classification | In this task, you are given a sentence in Polish language and its corresponding English translation. Here, your job is to output label "yes" if the translation is correct, otherwise output "no". | [
"Text Matching"
] | [
"Miscellaneous"
] | [
"poleval2019_mt"
] | [] | [
"Polish",
"English"
] | [
"English"
] | [
"English"
] | [
"Abhijeet Nawale"
] | [{"input": "Polish: b\u0119dzie to parabola, kt\u00f3ra wygl\u0105da mniej wi\u0119cej tak\u2026 wygl\u0105da jako\u015b tak\u2026 \n English: this is gonna be a parabola, it looks something like this... It's gonna look something... ", "output": "yes", "explanation": "Polish sentence is properly converted into English ... | [{"input": "Polish: Najokrutniejsza strona? \n English: Cruelest industry?", "output": "Correct", "explanation": "The answer can only be yes or no."}, {"input": "Polish: moje udzia\u0142y w firmie uleg\u0142y rozcie\u0144czeniu. \n English: my share of the company got diluted.", "output": "no", "explanation": "Polish s... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task832 | https://huggingface.co/datasets/Lots-of-LoRAs/task832_poleval2019_mt_classification | poleval2019 mt classification |
1086 | task1086_pib_translation_marathi_english | A text is given in English. Translate it from the English language to the Marathi language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Marathi"
] | [
"English"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u0938\u0941\u0930\u0941\u0935\u093e\u0924\u0940\u0932\u093e \u092a\u094b\u0937\u0923 \u0926\u093f\u0938\u0942\u0928 \u092f\u0947\u0923\u093e\u0930 \u0928\u093e\u0939\u0940, \u092e\u093e\u0924\u094d\u0930 \u0939\u0933\u0942-\u0939\u0933\u0942 \u0917\u0924\u0940 \u092f\u0947\u0908\u0932", "output": "Initiall... | [{"input": "\u090f\u0915 \u0905\u0936\u0940 \u0915\u093e\u0930\u094d\u092f\u0938\u0902\u0938\u094d\u0915\u0943\u0924\u0940 \u091c\u0940 \u0909\u0924\u094d\u0924\u0930\u0926\u093e\u092f\u0940 \u0905\u0938\u0947\u0932, \u091c\u0940 \u092a\u093e\u0930\u0926\u0930\u094d\u0936\u0940 \u0905\u0938\u0947\u0932", "output": "His... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1086 | https://huggingface.co/datasets/Lots-of-LoRAs/task1086_pib_translation_marathi_english | pib translation marathi english |
994 | task994_pib_translation_tamil_hindi | A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Tamil"
] | [
"Hindi"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u0bae\u0bc1\u0ba9\u0bcd \u0b95\u0bc2\u0b9f\u0bcd\u0b9f\u0bbf \u0b85\u0bb1\u0bbf\u0ba8\u0bcd\u0ba4\u0bc1\u0b95\u0bca\u0bb3\u0bcd\u0bb3 \u0bae\u0bc1\u0b9f\u0bbf\u0baf\u0bbe\u0ba4 \u0baa\u0bb0\u0bc1\u0bb5\u0ba8\u0bbf\u0bb2\u0bc8\u0baf\u0bbf\u0ba9\u0bbe\u0bb2\u0bcd \u0b8f\u0bb1\u0bcd\u0baa\u0b9f\u0bc1\u0bae\u0... | [{"input": "\u0b87\u0ba8\u0bcd\u0ba4\u0baa\u0bcd \u0baa\u0bc6\u0ba3\u0bcd\u0ba3\u0bbf\u0ba9\u0bcd \u0baa\u0bc6\u0bb1\u0bcd\u0bb1\u0bcb\u0bb0\u0bcd\u0b95\u0bb3\u0bcd \u0b95\u0b9f\u0ba9\u0bcd \u0bb5\u0bbe\u0b99\u0bcd\u0b95 \u0bb5\u0bc7\u0ba3\u0bcd\u0b9f\u0bc1\u0bae\u0bbe?", "output": "\u0907\u0938\u0915\u0947 \u0905\u093... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task994 | https://huggingface.co/datasets/Lots-of-LoRAs/task994_pib_translation_tamil_hindi | pib translation tamil hindi |
307 | task307_jeopardy_answer_generation_final | You will be given a trivia clue, and the category it belongs to. You should answer with the best answer that belongs in the category and is described by the clue. For simplicity, answers should be in all lower cased letters. | [
"Misc."
] | [
"Knowledge Base"
] | [
"jeopardy"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Eshaan Pathak"
] | [{"input": "Category: HOMOPHONIC PAIRS \nClue: It's a notation on a percussion store to clash", "output": "cymbal symbol", "explanation": "\"Cymbal\" and \"symbol\" both have the same pronunciations but different meanings, hence they are homophonic pairs. A symbol is the notation and a cymbal is a percussion instrument... | [{"input": "Category: U.S. CITIES \nClue: Its largest airport is named for a World War II hero; its second largest, for a World War II battle", "output": "new york city", "explanation": "The correct answer is actually Chicago where the largest airport is named after Edward O'Hare and the second largest airport is named... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task307 | https://huggingface.co/datasets/Lots-of-LoRAs/task307_jeopardy_answer_generation_final | jeopardy answer generation final |
1244 | task1244_ted_translation_gl_pl | You are given a sentence in Galician. Your job is to translate the Galician sentence into Polish. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Galician"
] | [
"Polish"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Hoxe, en Suecia e outros pa\u00edses ricos, a xente usa moitas m\u00e1quinas diferentes.", "output": "Dzisiaj, w Szwecji i innych bogatych krajach ludzie u\u017cywaj\u0105 mn\u00f3stwo najr\u00f3\u017cniejszych urz\u0105dze\u0144.", "explanation": "The Galician sentence is correctly translated into Polish, ... | [{"input": "E agora, \u201cbrrrrrrrrr \u201d, coma se fosen rapaces.", "output": "Ale nie przestawa\u0142a karmi\u0107 mnie pingwinami.", "explanation": "The Galician sentence is not correctly translated into Polish, because the meaning is different."}, {"input": "(M\u00fasica) Outra vez vedes a bonita linguaxe corpora... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1244 | https://huggingface.co/datasets/Lots-of-LoRAs/task1244_ted_translation_gl_pl | ted translation gl pl |
1227 | task1227_ted_translation_es_ja | You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Japanese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Spanish"
] | [
"Japanese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Es una lucha interna, una lucha en contra del vicio, el pecado, la tentaci\u00f3n, el deseo, la avaricia.", "output": "\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\... | [{"input": "Y llegu\u00e9 al punto que cada vez que iba a un lugar donde hab\u00eda un ni\u00f1o entre tres y diez a\u00f1os, estaba lista para luchar.", "output": "\u6575\u56fd\u3068\u81ea\u5206\u304b\u3089\u9032\u3093\u3067\u5bfe\u8a71\u3059\u308b\u306a\u3069\u56fd\u306e\u6a5f\u95a2\u306b\u983c\u308b\u3053\u3068\u306... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1227 | https://huggingface.co/datasets/Lots-of-LoRAs/task1227_ted_translation_es_ja | ted translation es ja |
1661 | task1661_super_glue_classification | In this task, you are given Wikipedia articles on a range of topics as passages and a question from the passage. We ask you to answer the question by classifying the answer as 0 (False) or 1 (True) | [
"Question Answering"
] | [
"Wikipedia"
] | [
"boolq"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Ayush Rawat"
] | [{"input": "Passage: Property tax -- Property tax or 'house tax' is a local tax on buildings, along with appurtenant land. It is and imposed on the Possessor (not the custodian of property as per 1978, 44th amendment of constitution). It resembles the US-type wealth tax and differs from the excise-type UK rate. The tax... | [{"input": "Passage: Phantom pain -- Phantom pain sensations are described as perceptions that an individual experiences relating to a limb or an organ that is not physically part of the body. Limb loss is a result of either removal by amputation or congenital limb deficiency. However, phantom limb sensations can also ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1661 | https://huggingface.co/datasets/Lots-of-LoRAs/task1661_super_glue_classification | super glue classification |
168 | task168_strategyqa_question_decomposition | In the following task, you are given a yes/no question, its answer, and additional information which includes a description of a key term in the question and several facts. Your task is to "decompose the question"i.e. write the steps required to construct the given answer where each step is a question that can be answe... | [
"Question Decomposition"
] | [
"Wikipedia"
] | [
"strategyqa"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "Question: Did Aristotle use a laptop?, Answer:No, Fact1: Aristotle died in 322 BC., Fact2: Laptop was invented in the 19th century.", "output": "Step1: When was the laptop invented?, Step2: When did Aristotle die?, Step3: Is #2 before #1?, Wikipedia page for step 1: Laptop, Wikipedia page for step 2: Aristo... | [{"input": "Question: Can a suit of armor conduct electricity?, Answer:Yes, Fact1: Suit of armor is made of iron., Fact2: Iron is an electric conductor.", "output": "Step1: What is a suit of armor made of?, Step2: Can iron conduct electricity?, Wikipedia page for step 1: Armor, Wikipedia page for step 2: Electrical Con... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task168 | https://huggingface.co/datasets/Lots-of-LoRAs/task168_strategyqa_question_decomposition | strategyqa question decomposition |
548 | task548_alt_translation_en_ch | In this task, given a sentence in the English language, your task is to convert it into the Chinese language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Chinese"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "\"This has not been a donor conference where governments have been invited to come and make new pledges, as I said if everybody lived by their Paris pledges in December 2007, which were three year pledges, we are exactly half way in that, we would have been more or less fine.\"", "output": "\u201c\u8fd9\u5e... | [{"input": "138,000 people were killed and thousands more were left homeless when when Cyclone Nargis devastated the region in May 2008.", "output": "\u793e\u533a\u5173\u7cfb\u90e8\u7ecf\u7406\u683c\u5170\u7279\u30fb\u574e\u8d1d\u5c14\u5bf9\u7f8e\u8054\u793e\u8bf4\uff1a\u201c\u5229\u7ef4\u6e2f\u662f\u4e00\u4e2a\u975e\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task548 | https://huggingface.co/datasets/Lots-of-LoRAs/task548_alt_translation_en_ch | alt translation en ch |
1247 | task1247_ted_translation_it_en | You are given a sentence in Italian. Your job is to translate the Italian sentence into English. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Italian"
] | [
"English"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Perch\u00e9? Perch\u00e9 quel profitto fa s\u00ec che qualunque soluzione da noi creata sia infinitamente riproducibile su scala.", "output": "Why? Because that profit allows whatever solution we've created to be infinitely scalable.", "explanation": "The Italian sentence is correctly translated into Englis... | [{"input": "Era infestata dalle gang, con un immenso turn-over degli insegnanti.", "output": "If you compare how Obama did against how John Kerry had done four years earlier \u2014 Democrats really like seeing this transition here, where almost every state becomes bluer, becomes more democratic \u2014 even states Obama... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1247 | https://huggingface.co/datasets/Lots-of-LoRAs/task1247_ted_translation_it_en | ted translation it en |
829 | task829_giga_fren_translation | In this task, you need to translate the given English sentence to the French language | [
"Translation"
] | [
"Miscellaneous"
] | [
"giga_fren"
] | [] | [
"English"
] | [
"French"
] | [
"English"
] | [
"Abhijeet Nawale"
] | [{"input": "Who can apply for special access to medical devices?", "output": "Qui peut demander l\u2019acc\u00e8s sp\u00e9cial \u00e0 des instruments m\u00e9dicaux?", "explanation": "English sentence is properly converted into French sentence"}, {"input": "What is Alzheimer\u2019s disease?", "output": "Qu'est-ce que la... | [{"input": "What are the factors associated with this difference?", "output": "Quels sont les facteurs associ\u00e9s \u00e0 cet?", "explanation": "The correct translation of the input to French is \"Quels sont les facteurs associ\u00e9s \u00e0 cet \u00e9cart ?\". However, the given output misses \u00e9cart."}, {"input"... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task829 | https://huggingface.co/datasets/Lots-of-LoRAs/task829_giga_fren_translation | giga fren translation |
1381 | task1381_quarel_incorrect_option_generation | You are given a sentence, a question and two answer options. Your task is to write down the index ('A' or 'B') of the **incorrect** option for the given question. | [
"Wrong Candidate Generation"
] | [
"Story",
"Commonsense -> Concepts and Relations"
] | [
"quarel"
] | [
"Relational Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Hsiao, Sheng-Hung"
] | [{"input": "Sentence: Jacob and Benny are squatting at the gym. Jacob has thin frail legs and Benny has big strong legs. Question: Who squats less weight? (A) Jacob (B) Benny", "output": "B", "explanation": "Typically, people with thin frail legs squat less weight than people with big strong legs, so the incorrect answ... | [{"input": "Sentence: Suppose your neighbor John is playing music and your friend Nikos at the end of the street is also playing music. Question: Who's music will appear to be louder? (A) John (B) Nikos", "output": "A", "explanation": "Typically, the closer you are to the source of the sound, the louder the sound is. S... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1381 | https://huggingface.co/datasets/Lots-of-LoRAs/task1381_quarel_incorrect_option_generation | quarel incorrect option generation |
1133 | task1133_xcsr_nl_commonsense_mc_classification | In this task, you will be presented with a question having multiple possible answers in Dutch language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge. | [
"Question Answering"
] | [
"Commonsense"
] | [
"x_csr"
] | [
"Commonsense Reasoning"
] | [
"Dutch"
] | [
"English"
] | [
"English"
] | [
"Maitreya Patel"
] | [{"input": "Question: Waarom zou iemand op zijn werk blijven zonder betaald te worden? \n Options: (A) godzijdank (B) in de rij wachten (C) vrijwilliger (D) hulp aanbieden (E) plezier aan het werk ", "output": "E", "explanation": "This is the correct answer. If someone loves to work too much then they like to keep work... | [{"input": "Question: Het loket informeerde de rijders dat de trein te laat kwam, dus waar was het loket? \n Options: (A) filmtheater (B) sportstadion (C) metrohalte (D) school (E) aula ", "output": "D", "explanation": "This is incorrect answer. Because the train is running late. Hence, the ticket booth is located in m... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1133 | https://huggingface.co/datasets/Lots-of-LoRAs/task1133_xcsr_nl_commonsense_mc_classification | xcsr nl commonsense mc classification |
364 | task364_regard_social_impact_classification | In this task, you will be given a sentence about a person. You should determine how the sentence affects how the person is perceived by most people in society. Your choices are:
Positive: The social perception of [PERSON] in the sentence is considered predominantly positive.
Negative: The social perception of [PERSON]... | [
"Text Categorization"
] | [
"Miscellaneous"
] | [
"nlg_bias"
] | [
"Commonsense Reasoning -> Social Situations"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Pegah Alipoormolabashi"
] | [{"input": "[PERSON] behaved like a professional in the job interview.", "output": "Positive", "explanation": "Behaving professionaly in a job interview has a positive impact on people's perception of a person."}, {"input": "[PERSON] was an escort and was always out with different people.", "output": "Negative", "expla... | [{"input": "[PERSON] was a doctor at the hospital nearby.", "output": "No impact", "explanation": "Physicians are respected people in the society, so the correct answer is Positive."}] | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task364 | https://huggingface.co/datasets/Lots-of-LoRAs/task364_regard_social_impact_classification | regard social impact classification |
1654 | task1654_mkb_translation | Given a sentence in English(en), generate a translation of that sentence in Hindi(hi) without changing the meaning of the input sentence as the output | [
"Translation"
] | [
"Captions -> Video Captions",
"Government and Politics"
] | [
"mkb"
] | [] | [
"English"
] | [
"Hindi"
] | [
"English"
] | [
"NIKHIL CHANDRA NIRUKONDA"
] | [{"input": "My dear countrymen, Namaskar.", "output": " \u092e\u0947\u0930\u0947 \u092a\u094d\u092f\u093e\u0930\u0947 \u0926\u0947\u0936\u0935\u093e\u0938\u093f\u092f\u094b, \u0928\u092e\u0938\u094d\u0915\u093e\u0930", "explanation": "The generated output has the same meaning as the given input sentence"}, {"input": " ... | [{"input": " These days Diwali is celebrated across many countries.", "output": " \u0906\u091c\u0915\u0932 \u0926\u093f\u0935\u093e\u0932\u0940 \u092e\u0928\u093e\u092f\u0940 \u091c\u093e\u0924\u0940 \u0939\u0948", "explanation": "The generated translation is partially done and has missed some details like Diwali is ce... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1654 | https://huggingface.co/datasets/Lots-of-LoRAs/task1654_mkb_translation | mkb translation |
817 | task817_pawsx_japanese_german_translation | Given a sentence in Japanese, provide an equivalent paraphrased translation in German that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Japanese"
] | [
"German"
] | [
"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": "Die Saison 1975 - 76 der National Basketball Association war die 30. Saison der NBA.",... | [{"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-task817 | https://huggingface.co/datasets/Lots-of-LoRAs/task817_pawsx_japanese_german_translation | pawsx japanese german translation |
376 | task376_reverse_order_of_words | In this task, you need to reverse the order of words in the given sentence. | [
"Program Execution"
] | [
"Captions -> Image Captions"
] | [
"synthetic"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Neeraj Varshney"
] | [{"input": "Sentence: luggage surrounds a vehicle in an underground parking area", "output": "area parking underground an in vehicle a surrounds luggage", "explanation": "This is a correct answer, as it correctly reverses the order of the words."}, {"input": "Sentence: people stand at a traffic light in a busy city", "... | [{"input": "Sentence: luggage surrounds a vehicle in an underground parking area", "output": "luggage surrounds a vehicle in an underground parking area", "explanation": "This answer only repeats the given sentence, in the original order. This is not a correct answer."}, {"input": "Sentence: man is sleeping in the gard... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task376 | https://huggingface.co/datasets/Lots-of-LoRAs/task376_reverse_order_of_words | reverse order of words |
486 | task486_cls_japanese_dvd_classification | In this task, you are given dvd product reviews in Japanese language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative. | [
"Sentiment Analysis"
] | [
"Reviews -> Electronics and Grocery"
] | [
"cls"
] | [] | [
"Japanese"
] | [
"English"
] | [
"English"
] | [
"Giannis Karamanolakis"
] | [{"input": "\uff11~\uff12\u8a71\u3067\u306f\u307e\u3063\u3066\u3057\u307e\u3046\u3053\u3068\u3067\u3057\u3087\u3046\u3002 . \u9752\u306e\uff16\u53f7\u306e\u30ad\u30e3\u30e9\u30af\u30bf\u30fc\u30c7\u30b6\u30a4\u30f3\u304c\u597d\u304d\u306a\u4eba\u306f\u3059\u3050\u306b\u306f\u307e\u3063\u3066\u3057\u307e\u3046\u4f5c\u54... | [{"input": "\u7aaa\u585a\u3068\u7af9\u4e2d\u304c\u30cd\u30c3\u30af . \u666e\u901a\u306b\u898b\u308c\u3070\u3001\u5272\u3068\u307e\u3068\u307e\u3063\u3066\u3044\u308b\u3057\u3001\u898b\u6240\u3082\u3042\u308b\u3002 \u305f\u3060\u3001\u539f\u4f5c\u6f2b\u753b\u304c\u597d\u304d\u306a\u4eba\u307b\u3069\u7d0d\u5f97\u306e\u30... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task486 | https://huggingface.co/datasets/Lots-of-LoRAs/task486_cls_japanese_dvd_classification | cls japanese dvd classification |
612 | task612_yorubabbc_classification | You are given a news article headline from BBC Yoruba and your task is to classify it into one of the following categories: Africa, Entertainment, Health, Nigeria, Politics, Sport, or World. | [
"Text Categorization"
] | [
"News"
] | [
"yoruba_bbc_topics"
] | [] | [
"Yoruba"
] | [
"English"
] | [
"English"
] | [
"Ishan Purohit"
] | [{"input": "2019 Election update: Buhari bor\u00ed; \u00f3 di \u00e0\u00e0r\u1eb9\nN\u00e0\u00ecj\u00edr\u00ed\u00e0 tuntun", "output": "Politics", "explanation": "The headline talks about the new president of Nigeria. So, it belongs to Politics category."}, {"input": "UI- \u00ccw\u00e1d\u00ec\u00ed \u00e0y\u1eb9w\u00f... | [{"input": "Il\u00e9es\u1eb9\u0301 ol\u00f3gun: Am\u1eb9rika, Italy \u0144 t\u00ecw\u00e1 l\u1eb9\u0301y\u00ecn l\u00e1ti\ns\u1eb9\u0301gun Boko Haram", "output": "Entertainment", "explanation": "The headline talks about US and Italy military support. So, it belongs to the category World not Entertainment."}, {"input":... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task612 | https://huggingface.co/datasets/Lots-of-LoRAs/task612_yorubabbc_classification | yorubabbc classification |
914 | task914_bianet_translation | In this task, you are given a Kurdish sentence and the goal is to faithfully translate the Kurdish sentence into Turkish so that they both mean the same thing | [
"Translation"
] | [
"News"
] | [
"bianet"
] | [] | [
"Kurdish"
] | [
"Turkish"
] | [
"English"
] | [
"Vivek Bellalacharvu Srinivasa Rao"
] | [{"input": "B\u00eaguman gel\u00ea kurd s\u00eete \u00fb n\u00fb\u00e7ey\u00ean xwe bi kurd\u00ee \u00e7\u00eadikin. L\u00ea ev yek di v\u00ea meseley\u00ea de aliyek din e. Ya ku bianet\u00ea p\u00eak t\u00eene ji xeyn\u00ee xebat\u00ean xwe, bo Kurd\u00ee j\u00ee fersendek diafir\u00eene. Ev yek p\u00eawist b\u00fb. ... | [{"input": "Murat Bayram, Ed\u00eetor\u00ea BIA Kurd\u00eey\u00ea: Min cara p\u00ea\u015fiy\u00ea ev hevoka balk\u00ea\u015f a \u2018\u2019fikir v\u00eer\u00fbsa her\u00ee bih\u00eaz e\u2019\u2019 li f\u00eelma Inception(destp\u00eak) d\u00eetib\u00fb.", "output": "Y\u00fcksekovahaber sitesinin haberine g\u00f6re Hakka... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task914 | https://huggingface.co/datasets/Lots-of-LoRAs/task914_bianet_translation | bianet translation |
1057 | task1057_pib_translation_english_urdu | A text is given in English. Translate it from the English language to the Urdu language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"English"
] | [
"Urdu"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "Pointing out that world over, thousands of innocent people were being killed and still the world community, the Vice President opined that without attaining peace, progress would have no meaning", "output": "\u0627\u0633 \u062f\u0646\u06cc\u0627 \u0633\u06d2 \u0632\u06cc\u0627\u062f\u06c1 \u0627\u0634\u0627... | [{"input": "Janata Dal (United)", "output": "\u0633\u06cc\u0644 \u06a9\u06cc \u0627\u0646\u062a\u0638\u0627\u0645\u06cc\u06c1 \u06a9\u0627 \u062e\u06cc\u0627\u0644 \u06c1\u06d2 \u06a9\u06c1 \u0627\u0633 \u0628\u06d2 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0648\u0627\u0633\u0637\u06c1 \u0679\u06cc\u06a9\u0633 \u064... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1057 | https://huggingface.co/datasets/Lots-of-LoRAs/task1057_pib_translation_english_urdu | pib translation english urdu |
520 | task520_aquamuse_answer_given_in_passage | In this task you will be given a question and a passage. You need to determine if the answer to the question is contained in the passage. If the answer can be found in the passage you should output 'True'. If the answer cannot be found in the passage you should output 'False'. | [
"Answerability Classification"
] | [
"Miscellaneous"
] | [
"aquamuse"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "Passage: 'The size of a matrix is defined by the number of rows and columns that it contains. A matrix with m rows and n columns is called an m \u00d7 n matrix or m-by-n matrix, while m and n are called its dimensions. For example, the matrix A above is a 3 \u00d7 2 matrix.'. Question: 'who came up with eat... | [{"input": "The forward assist on a firearm is a button found commonly on AR-15 rifle derivatives, such as the M16 rifle, and is usually located near the bolt closure. When hit, it pushes the bolt carrier forward, ensuring that the bolt is locked. In order to ensure that the extractor is clipped around the rim of the c... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task520 | https://huggingface.co/datasets/Lots-of-LoRAs/task520_aquamuse_answer_given_in_passage | aquamuse answer given in passage |
549 | task549_alt_translation_en_vi | In this task, given a sentence in the English language, your task is to convert it into the Vietnamese language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"English"
] | [
"Vietnamese"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "The Ukrainian foreign ministry said a Ukrainian woman had been killed and the Romanian foreign ministry said a 41-year-old Romanian woman was amongst the dead.", "output": "B\u1ed9 Ngo\u1ea1i giao Ukraine cho bi\u1ebft m\u1ed9t ph\u1ee5 n\u1eef ng\u01b0\u1eddi Ukraine \u0111\u00e3 b\u1ecb thi\u1ec7t m\u1ea1... | [{"input": "At least three assailants tried to storm the U.S. embassy in the Rawda area of Damascus, Syria.", "output": "H\u01a1n 3,000 ngh\u1ec7 s\u0129 trong n\u01b0\u1edbc v\u00e0 qu\u1ed1c t\u1ebf s\u1ebd tham gia s\u1ef1 ki\u1ec7n, trang tr\u00ed h\u01a1n 100 con b\u00f2 b\u1eb1ng s\u1ee3i th\u1ee7y tinh v\u1edbi ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task549 | https://huggingface.co/datasets/Lots-of-LoRAs/task549_alt_translation_en_vi | alt translation en vi |
1493 | task1493_bengali_geopolitical_hate_speech_binary_classification | In this task, you are given a hateful post in Bengali that expresses hate or encourages violence in a geopolitical context based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: geopolitical or non-geopolitical depending on the... | [
"Text Categorization"
] | [
"Social Media",
"Dialogue"
] | [
"bengali_hate_speech_dataset"
] | [
"Reasoning on Social Interactions"
] | [
"Bengali"
] | [
"English"
] | [
"English"
] | [
"Ishani Mondal"
] | [{"input": "\u0996\u0995\u09c1\u0995\u09c1\u09b0 \u0995\u09c7 \u09b2\u09be\u0987 \u09a6\u09bf\u09a4\u09c7 \u09a8\u09c7\u0987, \u09af\u09a6\u09bf \u09b2\u09be\u0987 \u09a6\u09c7\u0993\u09df\u09be \u09b9\u09df \u09a4\u09be\u09b9\u09b2\u09c7 \u09ae\u09be\u09a5\u09be\u09df \u0993\u09a0\u09c7 \u09ac\u09b8\u09c7 ", "output":... | [{"input": "\u09a1\u09c1\u09ac\u09a8\u09cd\u09a4 \u09a8\u09cc\u0995\u09be\u09df \u0986\u09b0 \u098f\u0995 \u09ac\u09b2\u09a6 \u09b8\u09be\u0995\u09bf\u09ac ", "output": "cow", "explanation": "You are expected to return \"geopolitical\" or \"non-geopolitical\". This should be classified as non-geopolitical as it express... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1493 | https://huggingface.co/datasets/Lots-of-LoRAs/task1493_bengali_geopolitical_hate_speech_binary_classification | bengali geopolitical hate speech binary classification |
1433 | task1433_head_qa_language_translation_es_to_en | In this task, you are given a sentence in the Spanish language. Your task is to translate the Spanish sentence into the English language. | [
"Translation"
] | [
"Healthcare"
] | [
"head_qa"
] | [] | [
"Spanish"
] | [
"English"
] | [
"English"
] | [
"Shreeshiv Patel"
] | [{"input": "Placa motora es la uni\u00f3n entre la neurona motora y el", "output": "Motor plate is the union between the motor neuron and the", "explanation": "Language translation is correct. The given input in English is a segmentally neutral sentence, therefore the polarity of the output must be neutral. Looking at ... | [{"input": "Formar fibras extracelulares con menos resistencia a la tracci\u00f3n.", "output": "Form extracellular fibers with high tensile strength", "explanation": "As the quantitative measures change during the translation we can say that this is the wrong translation."}, {"input": "Una mayor cantidad de alimentos a... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1433 | https://huggingface.co/datasets/Lots-of-LoRAs/task1433_head_qa_language_translation_es_to_en | head qa language translation es to en |
1620 | task1620_menyo20k-mt_yo_en_translation | The input contains texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. Your task is to translate the given Yoruba sentence into the English language. Please bear in mind the followin... | [
"Translation"
] | [
"News",
"TED Talks",
"Captions -> Video Captions",
"Natural Science"
] | [
"menyo20k_mt"
] | [] | [
"Yoruba"
] | [
"English"
] | [
"English"
] | [
"Krishna Kesani"
] | [{"input": "\u201cWo \u1ecdm\u1ecd\u1ecd\u0300 mi d\u00e8 m\u00ed\u201d: \u00f3 \u0144 lo k\u00edj\u00ecp\u00e1 m\u1eb9\u0301ta gb\u00f3; m\u00e9l\u00f2\u00f3 ni \u1ecdl\u1ecd\u0301m\u1ecd\u1ecd\u0301 m\u00e1a l\u00f2 gb\u00f3?", "output": "\u201cLook after the child for me\u201d: she wears three durable hand-loom wrap... | [{"input": "Abala k\u1ecdk\u00e0nd\u00ednl\u00f3g\u00fan", "output": "Article 19", "explanation": "The input sentence is not correctly translated from Yoruba to English as a word is translated to a number in English."}, {"input": "Mo ti s\u1ecd f\u00fan \u1eb9, j\u1eb9\u0301 k\u00e1 fi s\u00f9\u00far\u00f9 \u1e63e \u00... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1620 | https://huggingface.co/datasets/Lots-of-LoRAs/task1620_menyo20k-mt_yo_en_translation | menyo20k-mt yo en translation |
1602 | task1602_webquestion_question_genreation | You are given a concept, and a list of answers. You should generate a question about the concept that leads to the given answer(s). | [
"Question Generation"
] | [
"Knowledge Base -> Freebase"
] | [
"web_questions"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Paril Ghori"
] | [{"input": "concept: Cleveland Ohio answers: ['North American Eastern Time Zone']", "output": "what time zone am i in cleveland ohio?", "explanation": "The output is correct based on the information available on the web. Because the time zone is the answer to the question about the concept."}, {"input": "concept: Draco... | [{"input": "concept: German Language answers: ['German Democratic Republic']", "output": "how much did adriana lima gain during pregnancy?", "explanation": "The question is not related to the given answer and concept."}, {"input": "concept: China answers: ['Chinese language'] ", "output": "what kind of money should i t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1602 | https://huggingface.co/datasets/Lots-of-LoRAs/task1602_webquestion_question_genreation | webquestion question genreation |
1617 | task1617_cc_alligned_translate_tel_eng | This task is to translate the Telugu Language Input to English Language Output | [
"Translation"
] | [
"Web"
] | [
"ccaligned_multilingual"
] | [] | [
"Telugu"
] | [
"English"
] | [
"English"
] | [
"Venkata Sesha Sree Vidya Akkiraju"
] | [{"input": "\u0c28\u0c47\u0c28\u0c41 \u0c35\u0c40\u0c21\u0c3f\u0c2f\u0c4b \u0c1a\u0c47\u0c38\u0c4d\u0c24\u0c41\u0c28\u0c4d\u0c28\u0c3e\u0c28\u0c41", "output": "I am making a video.", "explanation": "Both the sentences says the same meaning in different languages, so it is a correct translation."}, {"input": "\u0c2c\u0c... | [{"input": "\u0c2e\u0c47\u0c18\u0c3e\u0c32\u0c32\u0c4b \u0c12\u0c15 \u0c35\u0c3f\u0c2e\u0c3e\u0c28\u0c02 \u0c09\u0c02\u0c26\u0c3f", "output": "There is no flight in the clouds.", "explanation": "Input says there is a flight in the sky but it is translated differently as no flight in the clouds. So this is not correct t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1617 | https://huggingface.co/datasets/Lots-of-LoRAs/task1617_cc_alligned_translate_tel_eng | cc alligned translate tel eng |
284 | task284_imdb_classification | In this task, you are given a review of movie. Your task is to classify given movie review into two categories: 1) positive, and 2) negative based on its content. | [
"Sentiment Analysis"
] | [
"Reviews -> Movies"
] | [
"imdb"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt.", "output": "positive", "... | [{"input": "For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt.", "output": "negative", "... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task284 | https://huggingface.co/datasets/Lots-of-LoRAs/task284_imdb_classification | imdb classification |
680 | task680_hope_edi_tamil_text_classification | Given a comment text in Tamil, classify the comment into one of these categories (i) Hope speech, if it contains encouraging, positive or supportive contents about equality, diversity or inclusion, (ii) Not Hope Speech or (iii) Not in Expected Language, if the text is not Tamil. | [
"Text Categorization"
] | [
"Social Media"
] | [
"hope_edi"
] | [
"Reasoning on Social Interactions"
] | [
"Tamil"
] | [
"English"
] | [
"English"
] | [
"Sai Surya Kaushik, Punyamurthula"
] | [{"input": "Spr Ithan sariyana valli", "output": "Hope Speech", "explanation": "The given text contains content that is encouraging, positive or supportive contents and talks about equality, diversity or inclusion and is in expected language - tamil"}, {"input": "appo china kitta irukkiradhu sivappu panama.", "output":... | [{"input": "\u0b87\u0bb8\u0bcd\u0bb2\u0bbe\u0bae\u0bcd \u0bae\u0bbe\u0bb0\u0bcd\u0b95\u0bcd\u0b95\u0ba4\u0bcd\u0ba4\u0bbf\u0bb2\u0bcd \u0b89\u0ba3\u0bb5\u0bbf\u0bb2\u0bcd \u0bb9\u0bb2\u0bbe\u0bb2\u0bcd \u0bb9\u0bb0\u0bbe\u0bae\u0bcd \u0baa\u0bb1\u0bcd\u0bb1\u0bbf \u0b95\u0bc1\u0bb0\u0bcd\u0b86\u0ba9\u0bbf\u0bb2\u0bc1\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task680 | https://huggingface.co/datasets/Lots-of-LoRAs/task680_hope_edi_tamil_text_classification | hope edi tamil text classification |
1616 | task1616_cc_alligned_translate_eng_tel | This task is to translate the English language Input to Telugu Language Output | [
"Translation"
] | [
"Web"
] | [
"ccaligned_multilingual"
] | [] | [
"English"
] | [
"Telugu"
] | [
"English"
] | [
"Venkata Sesha Sree Vidya Akkiraju"
] | [{"input": "I am very happy", "output": "\u0c38\u0c4d\u0c28\u0c47\u0c28\u0c41 \u0c1a\u0c3e\u0c32\u0c3e \u0c38\u0c02\u0c24\u0c4b\u0c37\u0c02\u0c17\u0c3e \u0c09\u0c28\u0c4d\u0c28\u0c3e\u0c28\u0c41", "explanation": "The translation is correct with meaning of the sentence not being impacted."}, {"input": "Never give up on ... | [{"input": "I am overwhelmed with lot of work.", "output": "\u0c28\u0c47\u0c28\u0c41 \u0c1a\u0c3e\u0c32\u0c3e \u0c38\u0c02\u0c24\u0c4b\u0c37\u0c02\u0c17\u0c3e \u0c2a\u0c28\u0c3f\u0c32\u0c4b \u0c2e\u0c41\u0c28\u0c3f\u0c17\u0c3f\u0c2a\u0c4b\u0c2f\u0c3e\u0c28\u0c41", "explanation": "The translated output says happy with t... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1616 | https://huggingface.co/datasets/Lots-of-LoRAs/task1616_cc_alligned_translate_eng_tel | cc alligned translate eng tel |
991 | task991_pib_translation_english_tamil | A text is given in English. Translate it from the English language to the Tamil language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"English"
] | [
"Tamil"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "Union Minister of Agriculture and Farmers Welfare Shri Radha Mohan Singh today met Ms", "output": "\u0ba4\u0bca\u0bb4\u0bbf\u0bb1\u0bcd\u0b9a\u0b99\u0bcd\u0b95 \u0bb5\u0bc7\u0bb3\u0bbe\u0ba3\u0bcd \u0bae\u0bb1\u0bcd\u0bb1\u0bc1\u0bae\u0bcd \u0bb5\u0bbf\u0bb5\u0b9a\u0bbe\u0baf\u0bbf\u0b95\u0bb3\u0bcd \u0ba8\... | [{"input": "Further 19,796 transporters, who are not registered under GST, have enrolled themselves on the e-Way Bill Portal", "output": "\u0ba8\u0bae\u0ba4\u0bc1 \u0b9a\u0bc1\u0ba4\u0ba8\u0bcd\u0ba4\u0bbf\u0bb0 \u0ba4\u0bbf\u0ba9\u0bae\u0bbe\u0ba9 \u0b87\u0ba9\u0bcd\u0bb1\u0bc1 \u0bae\u0bc2\u0bb5\u0bb0\u0bcd\u0ba3\u0b... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task991 | https://huggingface.co/datasets/Lots-of-LoRAs/task991_pib_translation_english_tamil | pib translation english tamil |
1445 | task1445_closest_integers | In this task you will be given a list of integers. You should find the minimum absolute difference between 2 integers in the list. The absolute difference is the absolute value of one integer subtracted by another. The output should be a single integer which is the smallest possible absolute distance. | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [
"Quantitative Reasoning",
"Mathematics -> Arithmetic"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Kirby Kuznia"
] | [{"input": "[9, 40, -33, 12, 17, -32, 40]", "output": "0", "explanation": "The minimum absolute difference is 0 because '40 - 40 = 0' and '40' appears in the list twice. So this is a good example."}, {"input": "[-16, 29, -11, 15, 6]", "output": "5", "explanation": "The minimum absolute difference is 5 because |-16 - -1... | [{"input": "[-5, -31, 18, 22, -6, 28]", "output": "[-5, -6]", "explanation": "The output contains the integers that result in the minimum absolute difference. Only the value of the minimum absolute difference should be returned. So this is a bad example."}, {"input": "[-45, -1, -39, 38, 18, -25]", "output": "1", "expla... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1445 | https://huggingface.co/datasets/Lots-of-LoRAs/task1445_closest_integers | closest integers |
996 | task996_pib_translation_english_bengali | A text is given in English. Translate it from the English language to the Bengali language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"English"
] | [
"Bengali"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "Operation Greens was announced in the Budget speech of 2018-19 with an outlay of Rs 500 crores to stabilize the supply of Tomato, Onion and Potato(TOP) crops and to ensure availability of TOP crops throughout the country round the year without any price volatility", "output": "\u099f\u09ae\u09c7\u099f\u09cb... | [{"input": "Prime Minister Prachanda spoke about the ongoing efforts of his government to take all stakeholders on board in the constitution implementation process", "output": "\u098f\u0995\u09ac\u09bf\u0982\u09b6 \u09b6\u09a4\u09be\u09ac\u09cd\u09a6\u09c0\u09b0 \u09ad\u09be\u09b0\u09a4\u09c7\u09b0 \u09b8\u09cd\u09ac\u... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task996 | https://huggingface.co/datasets/Lots-of-LoRAs/task996_pib_translation_english_bengali | pib translation english bengali |
271 | task271_europarl_translation | In this task, you are given a sentence in the Bulgarian language. Here, your job is to convert bulgarian sentence into the english language. | [
"Translation"
] | [
"Government and Politics"
] | [
"europarl"
] | [] | [
"Bulgarian"
] | [
"English"
] | [
"English"
] | [
"Mihir Parmar"
] | [{"input": "\u0421\u044a\u0441\u0442\u0430\u0432 \u043d\u0430 \u041f\u0430\u0440\u043b\u0430\u043c\u0435\u043d\u0442\u0430: \u0432\u0436. \u043f\u0440\u043e\u0442\u043e\u043a\u043e\u043b\u0438", "output": "Membership of Parliament: see Minutes", "explanation": "Bulgarian sentence is converted into english sentence."}, ... | [{"input": "\u0418\u043c\u0430\u0445\u043c\u0435 \u0434\u0432\u0435 \u043e\u0441\u043d\u043e\u0432\u043d\u0438 \u043f\u0440\u0438\u0447\u0438\u043d\u0438 \u0437\u0430 \u0442\u043e\u0432\u0430.", "output": "This is the very problem which we are facing today.", "explanation": "The conversion of bulgarian to english is wr... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task271 | https://huggingface.co/datasets/Lots-of-LoRAs/task271_europarl_translation | europarl translation |
078 | task078_all_elements_except_last_i | In this task, you are given inputs i and A, where i is an integer and A is a list. You need to list all the elements of A preceding the last i elements. i will always have a value less than the length of A. | [
"Program Execution"
] | [
"Mathematics"
] | [
"synthetic"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Pulkit Verma"
] | [{"input": "3, ['a', '34', 'f', '931', '7', '3432', '13245', '762']", "output": "a, 34, f, 931, 7", "explanation": "Here, all the elements except the last 3 from the list are 'a', '34', 'f', '931', and '7'."}, {"input": "6, ['5191', '9389', '9907', '8877', 'N', '6453', 's', 'k', '6209', 'W', '4591', 'B', 'p']", "output... | [{"input": "5, ['7475', 'B', '2459', 'm', '8349', 'O', 'q', 'Y', 'f']", "output": "7475, 2459", "explanation": "Here, the answer should have been '7475, B, 2459, m' as all the elements except the last 5 from the list are '7475', 'B', '2459', and 'm'."}, {"input": "3, ['4324', '34324', 'H', '3432', 'a', '34', 'c']", "ou... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task078 | https://huggingface.co/datasets/Lots-of-LoRAs/task078_all_elements_except_last_i | all elements except last i |
779 | task779_pawsx_english_spanish_translation | Given a sentence in English, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"English"
] | [
"Spanish"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "The NBA season of 1975 -- 76 was the 30th season of the National Basketball Association .", "output": "La temporada 1975 - 76 de la Asociaci\u00f3n Nacional de Baloncesto fue la temporada 30 de la NBA.", "explanation": "This is a correct and accurate translation from English to Spanish because the translate... | [{"input": "In Paris , in October 1560 , he secretly met the English ambassador , Nicolas Throckmorton , asking him for a passport to return to England through Scotland .", "output": "En octubre de 1560, se reuni\u00f3 en secreto con el embajador ingl\u00e9s, Nicolas Throckmorton, en Par\u00eds, y le pidi\u00f3 un pasa... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task779 | https://huggingface.co/datasets/Lots-of-LoRAs/task779_pawsx_english_spanish_translation | pawsx english spanish translation |
803 | task803_pawsx_german_french_translation | Given a sentence in German, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"German"
] | [
"French"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "Die NBA-Saison 1975 - 76 war die 30. Saison der National Basketball Association.", "output": "La saison 1975-1976 de la National Basketball Association \u00e9tait la 30e saison de la NBA.", "explanation": "This is a correct and accurate translation from German to French because the translated paraphrase ret... | [{"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": "En octobre 1560, il rencontra secr\u00e8tement l'ambassadeur d'Angleterre, Nicolas Throckmorton, \u00e0 Paris, et l... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task803 | https://huggingface.co/datasets/Lots-of-LoRAs/task803_pawsx_german_french_translation | pawsx german french translation |
1226 | task1226_ted_translation_es_en | You are given a sentence in Spanish. Your job is to translate the Spanish sentence into English. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Spanish"
] | [
"English"
] | [
"English"
] | [
"David Stap"
] | [{"input": "Con el crecimiento, los pa\u00edses y las sociedades ingresan en un ciclo virtuoso de movilidad ascendente, de oportunidad y mejores niveles de vida.", "output": "With economic growth, countries and societies enter into a virtuous cycle of upward mobility, opportunity and improved living standards.", "expla... | [{"input": "Y yo dije, \"\" Estoy aprendiendo. \"\" (Risas) Y me mir\u00f3, y fue como una exitosa toma de lucha, y entonces, despu\u00e9s de eso, dio un extraordinario recuento de c\u00f3mo su vida fue realmente.", "output": "This was taken under a homeless asylum built in 1885 to house 1,100 people.", "explanation": ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1226 | https://huggingface.co/datasets/Lots-of-LoRAs/task1226_ted_translation_es_en | ted translation es en |
542 | task542_alt_translation_ja_en | In this task, given a sentence in the Japanese language, your task is to convert it into the English language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"Japanese"
] | [
"English"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "\u30da\u30c8\u30ec\u30a4\u30a2\u30b9\u6c0f\u306f\u307e\u305f\u3001\u300c2008\u5e74\u306b\u3055\u3089\u306b8\u65c5\u56e3\u3068\u5927\u968a\u6226\u95d8\u56e3\u3092\u524a\u6e1b\u3057\u30012008\u5e747\u6708\u4e2d\u65ec\u307e\u3067\u306b\u5897\u52a0\u524d\u306e\u30ec\u30d9\u30eb\u306e15\u65c5\u56e3\u6226\u95d8\u... | [{"input": "Shiel\u53f8\u6559\u306f5\u304b\u6708\u5f8c\u3001\u6b7b\u306e\u5e8a\u3067\u5f7c\u5973\u306e\u7834\u9580\u3092\u64a4\u56de\u3057\u305f\u3002", "output": "\"I thought going into the third we'd each won a round, but I definitely thought I won that last round.\"", "explanation": "The above sentence is not correc... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task542 | https://huggingface.co/datasets/Lots-of-LoRAs/task542_alt_translation_ja_en | alt translation ja en |
220 | task220_rocstories_title_classification | In this task, you're given five sentences, numbered 1 through 5, and two options a and b for possible titles for the story. Your job is to choose the title that better fits the story. Indicate your choice by 'a' or 'b'. | [
"Title Generation"
] | [
"Narrative",
"Story"
] | [
"rocstories"
] | [
"Deductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Anjana Arunkumar"
] | [{"input": "Sentence 1: Marcus needed clothing for a business casual event. Sentence 2: All of his clothes were either too formal or too casual. Sentence 3: He decided to buy a pair of khakis. Sentence 4: The pair he bought fit him perfectly. Sentence 5: Marcus was happy to have the right clothes for the event. Choices... | [{"input": "Sentence 1: My grandparents and I were going for a walk. Sentence 2: Suddenly, right in front of us, was a huge moose. Sentence 3: We were walking near some pine trees and turned a corner. Sentence 4: It was so close that it scared us, but they told me not to run. Sentence 5: We all stood still and soon the... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task220 | https://huggingface.co/datasets/Lots-of-LoRAs/task220_rocstories_title_classification | rocstories title classification |
258 | task258_spl_translation_fa_en | The provided file includes inquiries about restaurants in Persian, and we ask you to translate those to English language. Please bear in mind the following guidelines 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... | [
"Translation"
] | [
"Public Places -> Restaurants"
] | [
"semantic_parser_localizer"
] | [] | [
"Persian"
] | [
"English"
] | [
"English"
] | [
"Mehrad Moradshahi"
] | [{"input": "\u0622\u064a\u0627 \u0647\u064a\u0686 \u0631\u0633\u062a\u0648\u0631\u0627\u0646 \" italian \" \u062f\u0631 \u0627\u064a\u0646 \u0646\u0632\u062f\u064a\u06a9\u064a \u0628\u0627 \u0646\u0642\u062f \u0648 \u0628\u0631\u0631\u0633\u064a 10 \u0633\u062a\u0627\u0631\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0... | [{"input": "\u0646\u0632\u062f\u064a\u06a9\u200c\u062a\u0631\u064a\u0646 \" wendy 's \" \u06a9\u062c\u0627\u0633\u062a\u061f", "output": "where is the closest wendy 's ?", "explanation": "Translation contain the entity \" wendy 's \" but quotation marks are dropped"}, {"input": "\u0646\u0632\u062f\u064a\u06a9\u200c\u06... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task258 | https://huggingface.co/datasets/Lots-of-LoRAs/task258_spl_translation_fa_en | spl translation fa en |
784 | task784_pawsx_korean_french_translation | Given a sentence in Korean, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Korean"
] | [
"French"
] | [
"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": "La saison 1975-1976 de la National Basketball Association \u00e9tait la 30e saison de la 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-task784 | https://huggingface.co/datasets/Lots-of-LoRAs/task784_pawsx_korean_french_translation | pawsx korean french translation |
320 | task320_stereoset_classification_race | You are given a target race, and two sentences. Your task is to determine whether the second sentence is either a stereotype, anti-stereotype, or is unrelated with respect to the first sentence and the target. A stereotype is a widely held but oversimplified notion of a group of people. An anti-stereotype is an idea th... | [
"Stereotype Detection"
] | [
"Stereotypes"
] | [
"stereoset"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Eshaan Pathak"
] | [{"input": "Target: hispanic \nMy professor is a hispanic man. He came here illegally.", "output": "stereotype", "explanation": "This is a stereotype because not every hispanic person has moved to a different country and is undocumented."}, {"input": "Target: hispanic \nMy professor is a hispanic man. He is a legal cit... | [{"input": "Target: hispanic \nMy professor is a hispanic man. He likes to teach chinese history.", "output": "stereotype", "explanation": "This is an anti-stereotype because hispanics are stereotypically portayed to not be in academia."}, {"input": "Target: hispanic \nMy professor is a hispanic man. He is going home."... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task320 | https://huggingface.co/datasets/Lots-of-LoRAs/task320_stereoset_classification_race | stereoset classification race |
1612 | task1612_sick_label_classification | In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the numbers 0 (entailment), 1 (neutral), or 2(cont... | [
"Textual Entailment"
] | [
"Captions -> Video Captions",
"Captions -> Image Captions"
] | [
"sick"
] | [
"Textual Entailment -> Deductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Venkata Sesha Sree Vidya Akkiraju"
] | [{"input": "sentence_A: A dancer is dancing on the stage. sentence_B: A girl is giving dance performance on the dais.", "output": "0", "explanation": "One sentence says, \"Dancing on the stage\" while the other sentence says, \"Dance performance on the dais\", which is clearly giving the same meaning and are related to... | [{"input": "sentence_A: Two dogs are fighting for bones. sentence_B: Two dogs are sharing the bones they have.", "output": "1", "explanation": "One sentence says, \"Two dogs are fighting\" and the other says, \"Two dogs are sharing\" which is a contradiction but classified as entailment. So this is a wrong example."}, ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1612 | https://huggingface.co/datasets/Lots-of-LoRAs/task1612_sick_label_classification | sick label classification |
1594 | task1594_yahoo_answers_topics_question_generation | You are given a passage. You need to construct a question about the information present in the passage. Construct a question in such a way that (i) it is unambiguous, (ii) its answer is the whole paragraph. Avoid creating questions that can be answered correctly without actually understanding the paragraph. | [
"Question Generation"
] | [
"Miscellaneous"
] | [
"yahoo_answers_topics"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Roseleen Kaur"
] | [{"input": "Optical mice use an LED and a camera to rapidly\ncapture images of the surface beneath the mouse.\nThe infomation from the camera is analyzed by a\nDSP (Digital Signal Processor) and used to detect\nimperfections in the underlying surface and\ndetermine motion. Some materials, such as glass,\nmirrors or oth... | [{"input": "Air\nFleet\\n \\n670 aircraft, including:\n\\n47 Airbus A300-600s 17 Boeing DC10-30s\n\\n62 Airbus A310-200/300s 36 Boeing\nMD10-10s \\n2 ATR 72s 5 Boeing MD10-30s\n\\n29 ATR 42s 57 Boeing MD11s \\n18\nBoeing 727-100s 10 Cessna 208As \\n94\nBoeing 727-200s 246 Cessna 208Bs \\n30\nBoeing DC10-10s ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1594 | https://huggingface.co/datasets/Lots-of-LoRAs/task1594_yahoo_answers_topics_question_generation | yahoo answers topics question generation |
383 | task383_matres_classification | You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | [
"Misc."
] | [
"News"
] | [
"matres"
] | [
"Temporal Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "It was followed by Denmark, Norway, Germany, France, Greece, Luxembourg, Spain, Britain, the United States, Iceland, Belgium, Italy, Portugal and Turkey. NATO decided at last year's Madrid summit to (invite) the three eastern European countries to start accession talks. \n Verb: invite", "output": "No", "e... | [{"input": "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. The first round of DNA tests on the hair at the FBI Laboratory here established a high probabilit... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task383 | https://huggingface.co/datasets/Lots-of-LoRAs/task383_matres_classification | matres classification |
1646 | task1646_dataset_card_for_catalonia_independence_corpus_text_classification | In this task, we have Spanish and Catalan tweets for automatic stance detection. The data has three labels Against, Favor, and Neutral which express the stance towards the target -independence of Catalonia. If the tweet criticizes the independence of Catalonia then it's 'Against' and if the tweets support it then it wi... | [
"Stance Detection"
] | [
"Medicine",
"Healthcare"
] | [
"catalonia_independence_corpus"
] | [
"Textual Entailment -> Deductive Reasoning"
] | [
"Spanish",
"Catalan"
] | [
"English"
] | [
"English"
] | [
"Mohd Zaid"
] | [{"input": "Tweet: Vull votar i votar\u00e9. Hi ha quelcom que no em permet no fer-ho. Ara b\u00e9 tinc un greu problema. No s\u00e9 a qui!!", "output": "Favor", "explanation": "The tweet asks for the right to vote for the independence of Catalonia and it supports the movement so it will be characterized as 'Favor'."... | [{"input": "Tweet: @Rampoina Tothom va amb mitjons i sand\u00e0lies #DetectiuConan3XL", "output": "Against", "explanation": "The tweets ask for the right of people to vote for the independence of Catalonia. Since it's not asking to take sides so a 'Neutral' stance would have been a correct one."}, {"input": "Tweet: Gan... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1646 | https://huggingface.co/datasets/Lots-of-LoRAs/task1646_dataset_card_for_catalonia_independence_corpus_text_classification | dataset card for catalonia independence corpus text classification |
1256 | task1256_ted_translation_pl_en | You are given a sentence in Polish. Your job is to translate the Polish sentence into English. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Polish"
] | [
"English"
] | [
"English"
] | [
"David Stap"
] | [{"input": "To najwi\u0119ksza nagrywarka, jak\u0105 w \u017cyciu widzieli\u015bcie.", "output": "It's sort of the biggest TiVo box you've ever seen.", "explanation": "The Polish sentence is correctly translated into English, because the meaning is preserved."}, {"input": "Te rozmowy, anga\u017cowanie m\u0119\u017cczyz... | [{"input": "By\u0142am zdumiona, bardzo z\u0142a i zdezorientowana.", "output": "I was amazed, very sad and confused..", "explanation": "The Polish sentence is not correctly translated into English. `z\u0142y` is incorrectly translated as `sad`, but the correct translation is `angry`."}, {"input": "To sensowny przebieg... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1256 | https://huggingface.co/datasets/Lots-of-LoRAs/task1256_ted_translation_pl_en | ted translation pl en |
1580 | task1580_eqasc-perturbed_question_generation | Given a statement, generate a question such that the answer is contained in that statement. | [
"Question Generation"
] | [
"Natural Science -> School Science Textbooks"
] | [
"eqasc"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Sudeep Nayak"
] | [{"input": "Neurons deliver electrical impulses to other cells", "output": "What do neurons deliver to other cells?", "explanation": "The question generated is valid regarding the information in the statement."}, {"input": "Two lenses to produce magnified images allow for detailed observation of stars.", "output": "Two... | [{"input": "Two lenses to produce magnified images allow for detailed observation of stars.", "output": "Who is the president?", "explanation": "The example is incorrect, as the question generated is not related to the statement."}, {"input": "Sharks have sharp jaws to catch their prey", "output": "What is the biggest ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1580 | https://huggingface.co/datasets/Lots-of-LoRAs/task1580_eqasc-perturbed_question_generation | eqasc-perturbed question generation |
450 | task450_opus_paracrawl_so_en_translation | Given a sentence in Somali language, translate the sentence to English language keeping the meaning of the original sentence intact | [
"Translation"
] | [
"Web"
] | [
"opus_paracrawl"
] | [] | [
"Somali"
] | [
"English"
] | [
"English"
] | [
"Arut Selvan Dhanasekaran"
] | [{"input": "Somali sentence: Lionel Messi waa ciyaaryahanka ugu weyn kubadda cagta abid", "output": "Lionel Messi is the greatest football player of all time", "explanation": "The output exactly translates the Somali sentence to it's English equivalent. Even though the phrase 'greatest player ever' is translated to 'gr... | [{"input": "Somali sentence: Tartanka Grand Prix-kii ugu horreeyay ee Talyaanigu wuxuu dhacay 4tii Sebtember 1921 goob 10.7-mayl (17.3 km) u dhow Montichiari", "output": "The first Italian Grand Prix took place on 4 September 1921 at a 10.7-mile (17.3 km) circuit near Montichiari", "explanation": "Even though the Somal... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task450 | https://huggingface.co/datasets/Lots-of-LoRAs/task450_opus_paracrawl_so_en_translation | opus paracrawl so en translation |
1405 | task1405_find_median | In this task, you are given a list of integers. You need to find the median of the list of integers and return that as the output. The median is the middle value in the list of numbers such that half of the elements are less than the median and the other half of elements are greater than the median. | [
"Program Execution"
] | [
"Mathematics",
"Statistics"
] | [
"synthetic"
] | [
"Numerical Reasoning",
"Mathematics -> Statistics"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Ravsehaj Singh Puri"
] | [{"input": "[149, 403, 272, 453, 472, 499, 419, 277, 411, 252, 48, 359, 351, 147, 298, 61, 114, 178, 250, 34, 400, 417, 184, 326, 96]", "output": "277", "explanation": "277 is the median of the input list."}, {"input": "[473, 208, 290, 185, 16, 344, 470, 487, 412, 272, 333, 335, 150, 365, 89, 337, 25, 432, 36, 284, 433... | [{"input": "[452, 417, 211, 426, 420, 382, 197, 131, 56, 68, 478, 498, 136, 366, 351, 212, 170, 14, 255, 430, 343, 36, 143, 326, 46]", "output": "420", "explanation": "420 is not the median of the input list. 255 is the median of the input list of integers."}, {"input": "[160, 474, 496, 47, 170, 194, 298, 393, 426, 430... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1405 | https://huggingface.co/datasets/Lots-of-LoRAs/task1405_find_median | find median |
260 | task260_spl_translation_zh_en | The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines 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... | [
"Translation"
] | [
"Public Places -> Restaurants"
] | [
"semantic_parser_localizer"
] | [] | [
"Chinese"
] | [
"English"
] | [
"English"
] | [
"Mehrad Moradshahi"
] | [{"input": "\u9644\u8fd1\u662f\u5426\u6709\u4efb\u4f5510\u661f\u8bc4\u4ef7\u7684\" italian \"\u9910\u5385\uff1f", "output": "are there any \" italian \" restaurants nearby with 10 star reviews ?", "explanation": "The translation correctly preserves \" italian \" entity and is accurate"}, {"input": "\u6b64\u9910\u5385\u... | [{"input": "\u6700\u8fd1\u7684\" wendy 's \"\u5728\u54ea\u91cc\uff1f", "output": "where is the closest wendy 's ?", "explanation": "Translation contain the entity \" wendy 's \" but quotation marks are dropped"}, {"input": "\u5411\u6211\u663e\u793a\u6700\u8fd1\u7684\" mcdonald 's \"", "output": "show me the closest \" ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task260 | https://huggingface.co/datasets/Lots-of-LoRAs/task260_spl_translation_zh_en | spl translation zh en |
780 | task780_pawsx_english_german_translation | Given a sentence in English, provide an equivalent paraphrased translation in German that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"English"
] | [
"German"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "The NBA season of 1975 -- 76 was the 30th season of the National Basketball Association .", "output": "Die Saison 1975 - 76 der National Basketball Association war die 30. Saison der NBA.", "explanation": "This is a correct and accurate translation from English to German because the translated paraphrase re... | [{"input": "In Paris , in October 1560 , he secretly met the English ambassador , Nicolas Throckmorton , asking him for a passport to return to England through Scotland .", "output": "Im Oktober 1560 traf er sich heimlich mit dem englischen Botschafter Nicolas Throckmorton in Paris und bat ihn um einen Pass, um durch E... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task780 | https://huggingface.co/datasets/Lots-of-LoRAs/task780_pawsx_english_german_translation | pawsx english german translation |
1345 | task1345_glue_qqp_question_paraprashing | In this task you're given a question and you have to paraphrase the question to create the output question while retaining the meaning of the original question. | [
"Question Rewriting"
] | [
"Books",
"Dialogue"
] | [
"qqp"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Arit Chanda"
] | [{"input": "What can one do after MBBS?", "output": "What do i do after my MBBS ?", "explanation": "In this example both the question ask the same thing about what to do after MBBS hence second question is the correct output "}, {"input": "Which is the best book to study TENSOR for general relativity from basic?", "out... | [{"input": "Do you need a passport to go to Jamaica from the United States?", "output": "How can I move to Jamaica?", "explanation": "In this example even though both questions have the same overall theme of moving to Jamaica the first question is only asking if Passport will be required for travelling to Jamaica from ... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1345 | https://huggingface.co/datasets/Lots-of-LoRAs/task1345_glue_qqp_question_paraprashing | glue qqp question paraprashing |
071 | task071_abductivenli_answer_generation | In this task, you're given the beginning and the middle of a three-part story. Your job is to complete the short story by writing a probable ending. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating the endin... | [
"Story Composition"
] | [
"Commonsense -> Stories"
] | [
"abductive_nli"
] | [
"Temporal Reasoning",
"Commonsense Reasoning",
"Abductive Reasoning",
"Textual Entailment -> Abductive Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Anjana Arunkumar"
] | [{"input": "Beginning: Helen lived in the state of Washington. Middle: Helen planned to drive to Canada but it started snowing heavily.", "output": "Helen stayed home instead and planned to go another day.", "explanation": "Generally, people prefer not to drive in bad weather."}, {"input": "Beginning: Helen lived in th... | [{"input": "Beginning: There was a severe earthquake in San Fransisco. Middle: Trains to San Fransisco were halted for a week.", "output": "Earthquakes are very common in California.", "explanation": "The general frequency of earthquakes in California does not explain why trains were stopped in San Fransisco for the pa... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task071 | https://huggingface.co/datasets/Lots-of-LoRAs/task071_abductivenli_answer_generation | abductivenli answer generation |
795 | task795_pawsx_spanish_english_translation | Given a sentence in Spanish, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Spanish"
] | [
"English"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "La temporada de la NBA de 1975: 76 fue la 30\u00aa temporada de la 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 Spanish to English because the tran... | [{"input": "En Par\u00eds, en octubre de 1560, se reuni\u00f3 en secreto con el embajador ingl\u00e9s, Nicolas Throckmorton, pidi\u00e9ndole un pasaporte para regresar a Inglaterra a trav\u00e9s de Escocia.", "output": "In October 1560 , he secretly met with the English ambassador , Nicolas Throckmorton , in Paris , an... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task795 | https://huggingface.co/datasets/Lots-of-LoRAs/task795_pawsx_spanish_english_translation | pawsx spanish english translation |
1706 | task1706_ljspeech_classification | The task is to identify if a given passage or sentence has proper punctuation. This includes proper capitalization and the use of punctuations such as commas, semi-colons and full-stops. The answer is True if all punctuation is properly applied, else the answer is False. | [
"Punctuation Error Detection"
] | [
"Books"
] | [
"lj_speec"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Arya Tawde"
] | [{"input": "jack ate the beans that the old man gave him.", "output": "False", "explanation": "The first letter of a new sentence is not capitalized, hence punctuation is incomplete."}, {"input": "The old sage was wise intelligent frail and weak", "output": "False", "explanation": "Commas and full-stop are missing and ... | [{"input": "The chicken crossed the road.", "output": "False", "explanation": "There is nothing wrong with the punctuation, the answer should be True."}, {"input": "The professor congratualted marie on her victory.", "output": "True", "explanation": "Marie is a proper noun and should be capitalized but it isn't. Theref... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1706 | https://huggingface.co/datasets/Lots-of-LoRAs/task1706_ljspeech_classification | ljspeech classification |
1205 | task1205_atomic_classification_isafter | 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",
"Commonsense -> Concepts and Relations -> Spatial Commonsense"
] | [
"atomic"
] | [
"Relational Reasoning",
"Reasoning on Social Interactions",
"Commonsense Reasoning -> Social Situations",
"Commonsense Reasoning -> Spatial Reasoning"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Yeganeh Kordi"
] | [{"input": "Head: PersonX cuts the ribbon<sep>Tail: PersonX opens a store", "output": "Yes", "explanation": "This is a good example. The Head happens after the Tail."}, {"input": "Head: PersonX acquires PersonY knowledge<sep>Tail: He plays also.", "output": "No", "explanation": "In this example, the Head and the Tail c... | [{"input": "Head: PersonX adapts to PersonY's environment<sep>Tail: accommodating", "output": "Yes", "explanation": "Accommodating is not an event that happens before the Head. So the output should be \"No\"."}, {"input": "Head: PersonX adopts a baby<sep>Tail: PersonX takes adoption classes", "output": "No", "explanati... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1205 | https://huggingface.co/datasets/Lots-of-LoRAs/task1205_atomic_classification_isafter | atomic classification isafter |
928 | task928_yelp_positive_to_negative_style_transfer | In this task, you are given a positive review and your task is to convert it to a negative review by making minimal changes. Avoid changing the context of the review. | [
"Style Transfer"
] | [
"Reviews"
] | [
"dualrl"
] | [
"Reasoning on Social Interactions"
] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Tanay Dixit"
] | [{"input": "all around great place to grab a drink or two .", "output": "all around bad place to grab a drink or two .", "explanation": "The output converts the given positive review to negative review by replacing the word 'great' with 'bad'. It does not change the context of the input"}, {"input": "it 's located in a... | [{"input": "very pleased with service and quality of work .", "output": "tasteless food", "explanation": "Though the output is negative , it changes the input text completely. As the task also involves to make minimal changes a better answer would be to change the phrase 'very pleased', like: displeased with service an... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task928 | https://huggingface.co/datasets/Lots-of-LoRAs/task928_yelp_positive_to_negative_style_transfer | yelp positive to negative style transfer |
536 | task536_alt_translation_vi_en | In this task, given a sentence in the Vietnamese language, your task is to convert it into the English language. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"Vietnamese"
] | [
"English"
] | [
"English"
] | [
"Phani Rohitha Kaza"
] | [{"input": "Theo Trung t\u00e1 Forbes Peters c\u1ee7a H\u1ea3i qu\u00e2n Australia, c\u00e1c quan ch\u1ee9c Indonesia c\u0169ng h\u00e0i l\u00f2ng nh\u01b0 c\u00e1c th\u1ee7y th\u1ee7, Peters n\u00f3i r\u1eb1ng \"C\u00e1c t\u00f9y vi\u00ean h\u1ea3i qu\u00e2n v\u00e0 \u0111\u1ea1i s\u1ee9 \u0111ang \u1edf \u0111\u00e2y... | [{"input": "\u00d4ng n\u00f3i ch\u00ednh ph\u1ee7 s\u1ebd kh\u00f4ng l\u00e0m theo nh\u1eefng nguy\u00ean t\u1eafc chung n\u00e0y.", "output": "In addition to wheelchairs, the workshops handle all manner of work with prostheses.", "explanation": "The above sentence is not correctly translated from Vietnamese to English... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task536 | https://huggingface.co/datasets/Lots-of-LoRAs/task536_alt_translation_vi_en | alt translation vi en |
799 | task799_pawsx_spanish_chinese_translation | Given a sentence in Spanish, provide an equivalent paraphrased translation in Chinese that retains the same meaning both through the translation and the paraphrase. | [
"Translation"
] | [
"Wikipedia"
] | [
"paws_x"
] | [] | [
"Spanish"
] | [
"Chinese"
] | [
"English"
] | [
"Jacob Anderson"
] | [{"input": "La temporada de la NBA de 1975: 76 fue la 30\u00aa temporada de la National Basketball Association.", "output": "1975-76\u8d5b\u5b63\u7684\u5168\u56fd\u7bee\u7403\u534f\u4f1a\u662fNBA\u7684\u7b2c30\u4e2a\u8d5b\u5b63\u3002", "explanation": "This is a correct and accurate translation from Spanish to Chinese b... | [{"input": "En Par\u00eds, en octubre de 1560, se reuni\u00f3 en secreto con el embajador ingl\u00e9s, Nicolas Throckmorton, pidi\u00e9ndole un pasaporte para regresar a Inglaterra a trav\u00e9s de Escocia.", "output": "1560\u5e7410\u6708\uff0c\u4ed6\u5728\u5df4\u9ece\u79d8\u5bc6\u4f1a\u89c1\u4e86\u82f1\u56fd\u5927\u4f... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task799 | https://huggingface.co/datasets/Lots-of-LoRAs/task799_pawsx_spanish_chinese_translation | pawsx spanish chinese translation |
337 | task337_hateeval_classification_individual_en | In this task, you are given a hateful post in English 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"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Xudong Shen"
] | [{"input": "Post: Stop tweeting about your boyfriend. No one gives a shit. And you're gonna break up in a month anyway #WomenSuck", "output": "Individual", "explanation": "The target being harassed in the post is the person he or she is replying to. Thus, the post should be classified as individual."}, {"input": "Post:... | [{"input": "Post: What do you call a woman who has lost 95% of her intelligence? Divorced", "output": "Individual", "explanation": "This post should be classified as generic because it is hateful towards all divorced women instead of a particular one."}, {"input": "Post: @Asholeee_ come on woman do your job right #Wom... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task337 | https://huggingface.co/datasets/Lots-of-LoRAs/task337_hateeval_classification_individual_en | hateeval classification individual en |
1608 | task1608_xquad_en_answer_generation | Answer the question from the given passage. Your answer should be directly extracted from the passage, and it should be a single entity, name, or number, not a sentence. | [
"Question Answering"
] | [
"Wikipedia"
] | [
"xquad"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Srija Macherla"
] | [{"input": "Passage: Martin Luther married Katharina von Bora, one of 12 nuns he had helped escape from the Nimbschen Cistercian convent in April 1523, when he arranged for them to be smuggled out in herring barrels. Suddenly, and while I was occupied with far different thoughts, he wrote to Wenceslaus Link, \u201cthe ... | [{"input": "Passage: Oceans and lakes have much in common, but they are also quite different. Both are bodies of water, but oceans are very large bodies of salt water, while lakes are much smaller bodies of fresh water. Question: What are large bodies of water?", "output": "lakes", "explanation": "The answer that is ex... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1608 | https://huggingface.co/datasets/Lots-of-LoRAs/task1608_xquad_en_answer_generation | xquad en answer generation |
1128 | task1128_alt_th_ja_translation | Given a sentence in the Thai, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is. | [
"Translation"
] | [
"News"
] | [
"asian_language_treebank"
] | [] | [
"Thai"
] | [
"Japanese"
] | [
"English"
] | [
"Savan Doshi"
] | [{"input": "\u0e2d\u0e34\u0e15\u0e32\u0e25\u0e35\u0e44\u0e14\u0e49\u0e40\u0e2d\u0e32\u0e0a\u0e19\u0e30\u0e42\u0e1b\u0e23\u0e15\u0e38\u0e40\u0e01\u0e2a\u0e14\u0e49\u0e27\u0e22\u0e04\u0e30\u0e41\u0e19\u0e1931\u0e15\u0e48\u0e2d5 \u0e43\u0e19\u0e01\u0e25\u0e38\u0e48\u0e21c \u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e41\u0e02\u... | [{"input": "\u0e42\u0e1b\u0e23\u0e15\u0e38\u0e40\u0e01\u0e2a\u0e2d\u0e22\u0e39\u0e48\u0e2d\u0e31\u0e19\u0e14\u0e31\u0e1a\u0e2a\u0e38\u0e14\u0e17\u0e49\u0e32\u0e22\u0e02\u0e2d\u0e07\u0e01\u0e25\u0e38\u0e48\u0e21\u0e42\u0e14\u0e22\u0e22\u0e31\u0e07\u0e44\u0e21\u0e48\u0e21\u0e35\u0e04\u0e30\u0e41\u0e19\u0e19 \u0e0b\u0e36\... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1128 | https://huggingface.co/datasets/Lots-of-LoRAs/task1128_alt_th_ja_translation | alt th ja translation |
982 | task982_pib_translation_tamil_bengali | A text is given in Bengali. Translate it from the Bengali language to the Tamil language. The translation must not omit or add information to the original sentence. | [
"Translation"
] | [
"Sociology",
"News"
] | [
"pib"
] | [] | [
"Tamil"
] | [
"Bengali"
] | [
"English"
] | [
"Krima Doshi",
"Swaroop"
] | [{"input": "\u0b87\u0ba8\u0bcd\u0ba4 \u0b92\u0baa\u0bcd\u0baa\u0ba8\u0bcd\u0ba4\u0bae\u0bcd 2019, \u0b9c\u0ba9\u0bb5\u0bb0\u0bbf \u0bae\u0bbe\u0ba4\u0ba4\u0bcd\u0ba4\u0bbf\u0bb2\u0bcd \u0b9f\u0bc6\u0ba9\u0bcd\u0bae\u0bbe\u0bb0\u0bcd\u0b95\u0bcd\u0b95\u0bbf\u0bb2\u0bbf\u0bb0\u0bc1\u0ba8\u0bcd\u0ba4\u0bc1 \u0b87\u0ba8\u0... | [{"input": "\u0b8e\u0ba9\u0bb5\u0bc7, \u0b87\u0ba9\u0bcd\u0bb1\u0bc1 \u0b89\u0b99\u0bcd\u0b95\u0bb3\u0bcd \u0bae\u0bc1\u0ba9\u0bcd\u0baa\u0bc1 \u0ba8\u0bbe\u0ba9\u0bcd \u0b87\u0bb0\u0bc1\u0baa\u0bcd\u0baa\u0ba4\u0bc1 \u0b8e\u0ba4\u0bc7\u0b9a\u0bcd\u0b9a\u0bc8\u0baf\u0bbe\u0b95 \u0ba8\u0b9f\u0ba8\u0bcd\u0ba4\u0ba4\u0bc1... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task982 | https://huggingface.co/datasets/Lots-of-LoRAs/task982_pib_translation_tamil_bengali | pib translation tamil bengali |
1231 | task1231_ted_translation_ar_ja | You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Japanese. | [
"Translation"
] | [
"TED Talks",
"Captions -> Video Captions"
] | [
"multilingual_ted"
] | [] | [
"Arabic"
] | [
"Japanese"
] | [
"English"
] | [
"David Stap"
] | [{"input": "\u0643\u0627\u0646 \u0627\u0644\u0623\u0645\u0631 \u0643\u0632\u064a\u0627\u0631\u0629 \u0623\u0643\u062b\u0631 \u0639\u0635\u0648\u0631 \u0627\u0644\u0628\u0631\u0627\u0621\u0629 \u0639\u0644\u0649 \u0643\u0648\u0643\u0628 \u0627\u0644\u0623\u0631\u0636", "output": "\u5730\u7403\u304c\u4eca\u3088\u308a\u30... | [{"input": "\u0644\u0645\u0627\u0630\u0627 \u061f \u0644\u0642\u062f \u062a\u0628\u064a\u0646 \u0644\u064a \u0641\u064a \u0628\u062f\u0627\u064a\u0629 \u0647\u0630\u0647 \u0627\u0644\u0623\u0644\u0641\u064a\u0629 \u0627\u0646 \u0627\u0644\u062f\u0648\u0644 \u0627\u0644\u062a\u064a \u0644\u062f\u0649 \u0633\u0643\u0627\... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1231 | https://huggingface.co/datasets/Lots-of-LoRAs/task1231_ted_translation_ar_ja | ted translation ar ja |
610 | task610_conllpp_ner | In this task, you are given a text from a post. Your task is to find all of the proper nouns and label them. The labels are <B-PER>, <I-PER> for persons; <B-ORG>, <I-ORG> for organizations; <B-LOC>, <I-LOC> for locations; and <B-MISC>, <I-MISC> for other nouns. The capital 'B' denotes the first word of a proper noun ph... | [
"Named Entity Recognition"
] | [
"Miscellaneous"
] | [
"conllpp"
] | [] | [
"English"
] | [
"English"
] | [
"English"
] | [
"Arlen Fan"
] | [{"input": "It has manufacturing plants in San Diego ; Creedmoor , N.C. ; Hampshire , England ; and Tijuana , Mexico , and distributes its prodcuts in more than 120 countries . ", "output": "It has manufacturing plants in San <B-LOC> Diego <I-LOC> ; Creedmoor <B-LOC> , N.C. <B-LOC> ; Hampshire <B-LOC> , England <B-LOC>... | [{"input": "The merger will add to both companies ' historical leadership in infusion therapy and technology-based drug delivery devices , they said . ", "output": "The merger <B-MISC> will add to both companies ' historical leadership in infusion therapy and technology-based drug delivery devices , they said . ", "exp... | https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task610 | https://huggingface.co/datasets/Lots-of-LoRAs/task610_conllpp_ner | conllpp ner |
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