Datasets:

ceselder
/

lots-of-loras-task-definitions

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
1487	task1487_organism_substance_extraction_anem_dataset	In this task, you are given a sentence. You are expected to write the name of the organism substances in the body mentioned in the input. Although there might be several correct answers, you need to write one of them.	[ "Named Entity Recognition" ]	[ "Biology -> Clinical Knowledge" ]	[ "anem" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishani Mondal" ]	[{"input": "Antisperm antibodies were assessed in the serum samples of 73 men unable to ejaculate naturally and on the sperm cells of 13 of these men.", "output": "serum", "explanation": "Serum is a substance of the organism and needs to be tagged."}, {"input": "This also applies , although to a much lesser degree , to...	[{"input": "This also applies , although to a much lesser degree , to conventional blood culture analysis ", "output": "conventional blood culture analysis", "explanation": "Blood culture analysis is nowhere related to organism substance and hence the entire mention should not be tagged."}, {"input": "Plasma carries wa...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1487	https://huggingface.co/datasets/Lots-of-LoRAs/task1487_organism_substance_extraction_anem_dataset	organism substance extraction anem dataset
1607	task1607_ethos_text_classification	You are given a piece of text. Your task is to classify the text based on whether a religion or a person/group of people are receiving hate based on religion. If there is a hate based on religion in the text, answer with 'religious hate', otherwise, answer with 'not religious hate'.	[ "Toxic Language Detection" ]	[ "Social Media" ]	[ "ethos" ]	[ "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Srija Macherla" ]	[{"input": "Religions have stupid theories about God and shits.", "output": "religious hate", "explanation": "The above text talks negatively about religions and opinion of a person who does not believe in religion, hence serves as a good example for the task."}, {"input": "What a disgusting face you have!", "output": ...	[{"input": "Idiots as always. Religion is the most useless thing you humans invented.", "output": "not religious hate", "explanation": "This is a bad example as the text displays religious hatred yet classified 0 which means it is not."}, {"input": "all kinds of mental illnesses are awful", "output": "religious hate", ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1607	https://huggingface.co/datasets/Lots-of-LoRAs/task1607_ethos_text_classification	ethos text classification
022	task022_cosmosqa_passage_inappropriate_binary	Read the given context and if the the context is inappropriate (e.g., pornographic) or nonsensical (e.g., cannot determine what happenings the context is about), indicate via "yes". Otherwise, response via "no".	[ "Toxic Language Detection" ]	[ "Personal Narratives" ]	[ "cosmosqa" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Swaroop Mishra", "Daniel Khashabi" ]	[{"input": "Context: Robin woke to the feel of the bed dipping done , then the very familiar feel of Patrick 's long hard body spooning behind her , his hand cradling her swollen belly . \" What are you doing here ? \" she asked groggily . Not 6 hours ago she had turned down his marriage proposal in front of the whole ...	[{"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.", "output": "No.", "explanation": "Nothing is inappropriate in the context and it provides multiple basis to create questions."}, {"input": "Context: GPS technology dates back to the time w...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task022	https://huggingface.co/datasets/Lots-of-LoRAs/task022_cosmosqa_passage_inappropriate_binary	cosmosqa passage inappropriate binary
278	task278_stereoset_sentence_generation_antistereotype	In this task, you are given a context sentence containing a blank (_). You are expected to fill the blank with one word to make the sentence convey a cultural anti-stereotype. Anti-stereotype is an idea that goes against a common belief about a particular group of people. Your answer must not contain more than one word...	[ "Fill in The Blank" ]	[ "Stereotypes" ]	[ "stereoset" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Xudong Shen" ]	[{"input": "Context: The African man was _.", "output": "educated", "explanation": "This is a valid anti-stereotype because it is known that education is less developed in Africa."}, {"input": "Context: I can't believe that my mommy is so _.", "output": "violent", "explanation": "This is a valid anti-stereotype because...	[{"input": "Context: Ethiopia is known for being _.", "output": "less-developed", "explanation": "This is not a valid anti-stereotype because it aggrees with the standardized image of Ethiopia being under-developed."}, {"input": "Context: Everyone in Spain speaks _.", "output": "Spanish", "explanation": "This is not a ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task278	https://huggingface.co/datasets/Lots-of-LoRAs/task278_stereoset_sentence_generation_antistereotype	stereoset sentence generation antistereotype
280	task280_stereoset_classification_stereotype_type	In this task, you are given a short passage that conveys stereotype or anti-stereotype about a specific target. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. You are expected to classify the passage into four types of ...	[ "Text Categorization" ]	[ "Stereotypes" ]	[ "stereoset" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Xudong Shen" ]	[{"input": "Passage: Many people live in Ethiopia. The people are very thin and good at distance running.", "output": "Race", "explanation": "The second sentence \"The people are very thin and good at distance running.\" is a racial stereotype of the Ethiopian people. It represents a standardized mental picture of the ...	[{"input": "Passage: The prisoner was kind.", "output": "Prisoner", "explanation": "Instead of answering the specific target, we ask you to identify the type of stereotype or anti-stereotype from gender, profession, race, and religion."}, {"input": "Passage: The african man is usually black", "output": "Gender.", "expl...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task280	https://huggingface.co/datasets/Lots-of-LoRAs/task280_stereoset_classification_stereotype_type	stereoset classification stereotype type
679	task679_hope_edi_english_text_classification	Classify the given comment into 'Hope Speech' or 'Not Hope Speech'. A hope speech is defined as content that is encouraging, positive or supportive contents and talks about equality, diversity or inclusion	[ "Text Categorization" ]	[ "Social Media" ]	[ "hope_edi" ]	[ "Reasoning on Social Interactions" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sai Surya Kaushik, Punyamurthula" ]	[{"input": "you have encouraged me thank you for sharing", "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"}, {"input": "There is justice for the natives the governm...	[{"input": "Madonna looks like she has extra sensory abilities", "output": "Hope Speech", "explanation": "The given text does not contain content that is neither encouraging, positive and supportive contents nor talks about equality, diversity and inclusion although it is in expected language. So it is wrongly classifi...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task679	https://huggingface.co/datasets/Lots-of-LoRAs/task679_hope_edi_english_text_classification	hope edi english text classification
456	task456_matres_intention_classification	You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition)....	[ "Information Extraction" ]	[ "News" ]	[ "matres" ]	[]	[ "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": "Yes", "...	[{"input": "The Justice Department wants the appeals court to suspend the temporary injunction issued Thursday and also order Elian's great-uncle, Lazaro Gonzalez, to release the boy. The relatives want the court to let them meet with Elian's father without being (required) to surrender the boy. \n Verb: required", "o...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task456	https://huggingface.co/datasets/Lots-of-LoRAs/task456_matres_intention_classification	matres intention classification
1431	task1431_head_qa_answer_generation	In this task, you are given a multiple-choice question about healthcare. Answer the question based on your information and classify your answers into '1', '2', '3', and '4'.	[ "Question Answering" ]	[ "Healthcare" ]	[ "head_qa" ]	[ "Scientific Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Shreeshiv Patel" ]	[{"input": "Question: A 13-year-old girl is operated on due to Hirschsprung illness at 3 months of age. Which of the following tumors is more likely to be present? \n Options: <1> Abdominal neuroblastoma <2> Wilms tumor <3> Mesoblastic nephroma <4> Familial thyroid medullary carcinoma.", "output": "2", "explanation": "...	[{"input": "Question: One of the characteristics of the Nursing Process is: \n Options: <1> Decision making is characteristic of the planning stage. <2> It focuses on the nurse. <3> The data of each phase provide information for the next. <4> Decision making must be linked to standard response. <5> It must be designed...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1431	https://huggingface.co/datasets/Lots-of-LoRAs/task1431_head_qa_answer_generation	head qa answer generation
1551	task1551_every_ith_element_from_kth_element	In this task, you are given inputs k, i, and A, where k and i are integers and A is a list. You need to find every ith element of A starting from the kth element. The process stops when the position of the next ith element exceeds the length of the list.	[ "Program Execution" ]	[ "Mathematics" ]	[ "synthetic" ]	[ "Reasoning on Strings", "Mathematics -> Counting" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Pulkit Verma" ]	[{"input": "2, 3, ['a', '34', 'f', '931', '7', '3432', '13245', '762']", "output": "34, 7, 762", "explanation": "Here, starting from 2nd element every 3rd element from the list are '34', '7', and '762'."}, {"input": "3, 6, ['5191', '9389', '9907', '8877', 'N', '6453', 's', 'k', '6209', 'W', '4591', 'B', 'p']", "output"...	[{"input": "5, 2, ['7475', 'B', '2459', 'm', '8349', 'O', 'q', 'Y', 'f']", "output": "7475, 2459, 8349, q, f", "explanation": "Here, the answer should have been '8349, q, f' as every 2nd element of the list starting from 5th element are '8349', 'q', and 'f'."}, {"input": "2, 3, ['75', '54', 'J', 'L', '2332', 'Z', 'e', ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1551	https://huggingface.co/datasets/Lots-of-LoRAs/task1551_every_ith_element_from_kth_element	every ith element from kth element
137	task137_detoxifying-lms_classification_toxicity	Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.	[ "Toxic Language Detection" ]	[ "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-task137	https://huggingface.co/datasets/Lots-of-LoRAs/task137_detoxifying-lms_classification_toxicity	detoxifying-lms classification toxicity
190	task190_snli_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 letters E, C, and N respectively.	[ "Textual Entailment" ]	[ "Captions -> Image Captions" ]	[ "snli" ]	[ "Textual Entailment" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Anjana Arunkumar" ]	[{"input": "Sentence 1: Jon saw his friend Tom coming out of the grocery store with a bag of fruit. Sentence 2: Tom had been shopping for fruit to give Jon.", "output": "N", "explanation": "Tom's reason for buying the fruit is not known."}, {"input": "Sentence 1: The girl transferred all the flowers from the boquet to ...	[{"input": "Sentence 1: There was an earthquake in San Fransisco. Sentence 2: The earthquake caused a lot of road damage.", "output": "E", "explanation": "The earthquake might not have been severe enough to cause raod damage, so the answer should be N."}, {"input": "Sentence 1: Anna went to the school picnic. Sentence ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task190	https://huggingface.co/datasets/Lots-of-LoRAs/task190_snli_classification	snli classification
385	task385_socialiqa_incorrect_answer_generation	In this task, you're given a context passage, a question, and three answer options. Your task is to return an incorrect answer option to the question from the choices given. For all questions, only one of the three answer options is correct. Pick one of the two incorrect answer options as the output.	[ "Question Answering" ]	[ "Commonsense -> Concepts and Relations -> Social Commonsense" ]	[ "social_iqa" ]	[ "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishan Purohit" ]	[{"input": "Context: Tracy didn't go home that evening and resisted Riley's attacks. \n Question: What does Tracy need to do before this? \n Options: (A) make a new plan (B) Go home and see Riley (C) Find somewhere to go", "output": "B", "explanation": "Tracy finds somewhere to go and didn't come home because she has t...	[{"input": "Context: Tracy's kids wanted ice cream so Aubrey fed the kids ice cream. \n Question: What does Aubrey need to do before this? \n Options: (A) tell her kids to say thank you (B) get ice cream (C) thanks Tracy", "output": "get ice cream", "explanation": "It is supposed to only return the options which had a...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task385	https://huggingface.co/datasets/Lots-of-LoRAs/task385_socialiqa_incorrect_answer_generation	socialiqa incorrect answer generation
513	task513_argument_stance_classification	You will be given a topic and an argument. Decide the argument's stance towards that topic. The argument's stance is in favor or against the topic. If the argument supports that topic, answer with "in favor"; otherwise, if the argument opposes the topic, answer with "against".	[ "Stance Detection" ]	[ "Debatepedia" ]	[ "starcon" ]	[ "Argument Reasoning", "Textual Entailment -> Deductive Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Pegah Alipoormolabashi" ]	[{"input": "topic: Nuclear energy\nargument: Nuclear energy can reduce materials available for weapons-use.", "output": "in favor", "explanation": "The given argument is in favor of nuclear energy."}, {"input": "topic: Smartphones in School\nargument:Smartphones often distract students from class.", "output": "against"...	[{"input": "topic: Kyoto Protocol\nargument: It is unimportant for the US to join Kyoto now", "output": "in favor", "explanation": "The word uninmportant clearly shows that this argument is against Kyoto Protocol."}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task513	https://huggingface.co/datasets/Lots-of-LoRAs/task513_argument_stance_classification	argument stance classification
391	task391_causal_relationship	In this task, you will be given two sentences separated by ", so". You should decide whether the first sentence can be the cause of the second sentence. If you can see a possible causation, answer with "plausible", otherwise answer with "not plausible".	[ "Cause Effect Classification" ]	[ "Commonsense" ]	[ "cod3s" ]	[ "Causal Reasoning", "Textual Entailment" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Pegah Alipoormolabashi" ]	[{"input": "The woman went to the bank, so pigs can fly.", "output": "not plausible", "explanation": "Clearly, there can't be a causation relationship between someone going to the bank and pigs flying."}, {"input": "The women went to the bank, so now she has money on hand.", "output": "plausible", "explanation": "The s...	[{"input": "The woman went to the bank, so she waited in a line.", "output": "not plausible", "explanation": "Although waiting in a line doesn't always come as a result of going to a bank, this is a plausible sentence."}, {"input": "The physician misdiagnosed the patient, so he went to the vet", "output": "plausible", ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task391	https://huggingface.co/datasets/Lots-of-LoRAs/task391_causal_relationship	causal relationship
583	task583_udeps_eng_coarse_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 coarse 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 'ADJ'...	[ "Pos Tagging" ]	[ "News" ]	[ "universal_dependencies___english_dependency_treebank" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Siddhartha Mishra" ]	[{"input": "Sentence: An editorial in the church - owned Deseret Morning News in Salt Lake City earlier this year acknowledged that \" the state 's history , a {{ conservative }} belief in free choice , and an unwillingness to stir up a hornet 's nest in the national media have likely all contributed to the kid - glove...	[{"input": "Sentence: If you feel this guy is {{ worth }} it then I hope your vet can figure things out . \nWord: worth", "output": "PUNCT", "explanation": "\"worth\" is not a Punctation (PUNCT) since it is not a non-alphabetic character used for delimiting units."}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task583	https://huggingface.co/datasets/Lots-of-LoRAs/task583_udeps_eng_coarse_pos_tagging	udeps eng coarse pos tagging
1194	task1194_kth_largest_element	In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.	[ "Program Execution" ]	[ "Mathematics" ]	[ "synthetic" ]	[ "Reasoning on Numbers" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ravsehaj Singh Puri" ]	[{"input": "[128, 277, 83, 280, 193, 19, 111, 154, 41, 292, 29, 53, 232, 153, 131, 151, 121, 262, 270, 132], k=15", "output": "111", "explanation": "111 is the 15th largest element in the list."}, {"input": "[126, 44, 101, 199, 228, 169, 85, 286, 167, 207, 175, 259, 141, 27, 35, 153, 185, 21, 198, 188], k=4", "output":...	[{"input": "[208, 241, 91, 76, 220, 137, 111, 190, 232, 155, 27, 258, 45, 112, 13, 289, 23, 239, 177, 227], k=8", "output": "241", "explanation": "241 is not the 8th largest element in the list."}, {"input": "[240, 22, 137, 62, 14, 121, 102, 294, 299, 15, 269, 205, 26, 17, 212, 272, 65, 189, 200, 261], k=4", "output": ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1194	https://huggingface.co/datasets/Lots-of-LoRAs/task1194_kth_largest_element	kth largest element
627	task627_xlwic_word_with_same_meaning_sentence_generation	In this task, you are given a word, followed by a sentence. You should respond with a valid sentence which contains the word with the same meaning as in the given sentence. For example, if the given sentence refers to a 'fly' as the insect, you should not respond with a sentence which uses 'fly' as the verb. You may us...	[ "Sentence Composition" ]	[ "Miscellaneous" ]	[ "xl_wic" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ananth Duggirala" ]	[{"input": "dust \n Sentence: Another one bites the dust.", "output": " The maid used a handkerchief to remove dust off the table.", "explanation": "In both the input and output sentences, the word 'dust' refers to sand, and therefore the words share the same meaning."}, {"input": "airplane \n Sentence: The passengers ...	[{"input": "ruler \n Sentence: The headmistress struck the table with a ruler.", "output": "The ruler decided to change taxation laws in his province.", "explanation": "The word 'ruler' has a different meaning in the input and output sentences. In the input sentence, it refers to a measuring stick, but in the output se...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task627	https://huggingface.co/datasets/Lots-of-LoRAs/task627_xlwic_word_with_same_meaning_sentence_generation	xlwic word with same meaning sentence generation
1448	task1448_disease_entity_extraction_ncbi_dataset	In this task, you will be given a sentence. You need to reconize the name of the disorder or disease. Disease is a disorder of structure or function in a human, animal, or plant, especially one that produces specific symptoms or that affects a specific location and is not simply a direct result of physical injury. Alth...	[ "Named Entity Recognition" ]	[ "Biology -> Clinical Knowledge", "Healthcare" ]	[ "ncbi_disease_corpus" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishani Mondal" ]	[{"input": "I had been suffering from cardiovascular disorder.", "output": "cardiovascular disorder", "explanation": "Here, the person mentions this disorder which is related to heart issues."}, {"input": "Acne is the most common skin condition in the United States, affecting up to 50 million Americans annually.", "out...	[{"input": "I had been suffering from cardiovascular disorder", "output": "disorder", "explanation": "This is an incomplete disease mention, as it does not clearly mention the actual type of disorder."}, {"input": "A 44-year-old man taking naproxen for chronic low back pain and a 20-year-old woman on oxaprozin for rheu...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1448	https://huggingface.co/datasets/Lots-of-LoRAs/task1448_disease_entity_extraction_ncbi_dataset	disease entity extraction ncbi dataset
210	task210_logic2text_structured_text_generation	In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that defin...	[ "Text to Code" ]	[ "Wikipedia", "Logic -> Propositional Logic" ]	[ "logic2text" ]	[ "Logical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Mihir Parmar" ]	[{"input": "select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.", "output": "eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }", "explanation": "Here, the generated command using logical opera...	[{"input": "select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .", "output": "eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }", "explanation": "Given natural language interpretation and generated command are miss matched. We need to choos...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task210	https://huggingface.co/datasets/Lots-of-LoRAs/task210_logic2text_structured_text_generation	logic2text structured text generation
1378	task1378_quarel_correct_answer_generation	You are given a sentence, a question and two answer options ('A' and 'B'). Your task is to find the correct answer (return the string of the correct option, not 'A' or 'B') for the given question.	[ "Question Answering" ]	[ "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": "Jacob", "explanation": "Typically, people with thin frail legs squat less weight than people with big strong legs, so the answer is ...	[{"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": "Nikos", "explanation": "Typically, the closer you are to the source of the sound, the louder the sound i...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1378	https://huggingface.co/datasets/Lots-of-LoRAs/task1378_quarel_correct_answer_generation	quarel correct answer generation
769	task769_qed_summarization	Given a text passage, come up with an appropriate title for it. The title should accurately represent what the main focus of the passage is. The title of a passage may be present in the first few sentences of the passage and/or be referred to multiple times in the passage. The title should be 1-5 words long.	[ "Title Generation" ]	[ "Wikipedia" ]	[ "qed" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ritvik Gaur" ]	[{"input": "The Beatles ' rooftop concert was the final public performance of the English rock band the Beatles . On 30 January 1969 , the band , with keyboardist Billy Preston , surprised a central London office and fashion district with an impromptu concert from the roof of the headquarters of the band 's multimedia ...	[{"input": "It 's Always Sunny in Philadelphia is an American television sitcom that premiered on FX on August 4 , 2005 . It moved to FXX beginning with the ninth season and has remained there since . It was created by Rob McElhenney who developed it with Glenn Howerton . It is executive produced and primarily written ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task769	https://huggingface.co/datasets/Lots-of-LoRAs/task769_qed_summarization	qed summarization
039	task039_qasc_find_overlapping_words	Generate an overlapping word between the given two sentences. When you find the overlapping words, they don't have to match exactly, e.g., "survival" and "survive" are valid overlapping words. Little words like "the" or "of" don't count! You must generate significant words which are not the stop words.	[ "Overlap Extraction" ]	[ "Natural Science" ]	[ "qasc" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Swaroop Mishra", "Daniel Khashabi" ]	[{"input": "Sentence1: pesticides cause pollution. \nSentence2: pollution can harm animals.", "output": "pollution.", "explanation": "The word \"pollution\" is common to Sentence1 and Sentence2. So, it's a good answer."}, {"input": "Sentence1: a solar panel converts sunlight into electricity. \nSentence2: sunlight come...	[{"input": "Sentence1: soil is formed by rocks eroding. \nSentence2: rain can help form soil.", "output": "soil, form, formed.", "explanation": "Here Sentence1 contains \"formed\" and Sentence2 contains \"form\". As per the given instructions, they should be treated as the same because of their same base form. A good a...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task039	https://huggingface.co/datasets/Lots-of-LoRAs/task039_qasc_find_overlapping_words	qasc find overlapping words
442	task442_com_qa_paraphrase_question_generation	Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.	[ "Question Rewriting" ]	[ "Web" ]	[ "com_qa" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Arut Selvan Dhanasekaran" ]	[{"input": "Question: what places in Africa do people speak french?", "output": "where in africa do people speak french?", "explanation": "The generated question means the same as the input question and the answer is the same, so this is a good answer."}, {"input": "Question: Hitler became chancellor of Germany in what...	[{"input": "Question: How long is the Nile river?", "output": "Is Nile the longest river?", "explanation": "The question created changes the meaning of the input question and the answer is not the same for the questions. This is not a good answer."}, {"input": "Question: Who is the first football player to win seven ba...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task442	https://huggingface.co/datasets/Lots-of-LoRAs/task442_com_qa_paraphrase_question_generation	com qa paraphrase question generation
875	task875_emotion_classification	In this task, you are given a sentence containing a particular emotion. You must classify the sentence into one of the six emotions: 'joy', 'love', 'anger', 'fear', or 'surprise'.	[ "Sentiment Analysis" ]	[ "Narrative" ]	[ "emotion" ]	[ "Reasoning on Social Interactions" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Archan Lagoo" ]	[{"input": "i am ever feeling nostalgic about the fireplace i will know that it is still on the property", "output": "love", "explanation": "The word \"nostalgic\" could either indicate \"love\" or \"sadness\", but the fact that it is still on the property eliminates \"love\"."}, {"input": "i am feeling grouchy", "outp...	[{"input": "i feel romantic too", "output": "joy", "explanation": "This statement clearly indicates joy, but the joy particularly relates to romance. So, the correct label must be \"love\" instead."}, {"input": "i feel like i have to make the suffering i m seeing mean something", "output": "love", "explanation": "Since...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task875	https://huggingface.co/datasets/Lots-of-LoRAs/task875_emotion_classification	emotion classification
1529	task1529_scitail1.1_classification	You are given two sentences. You have to find if there is entailment or agreement of the Hypothesis by the Premise. From the given pair of sentences, you should identify if there is enough information in the Premise to support the claim made in the Hypothesis. The Premise may not exactly be the same as Hypothesis. Your...	[ "Textual Entailment" ]	[ "Natural Science" ]	[ "scitailv1.1" ]	[ "Textual Entailment" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Krishna Sriharsha Gundu" ]	[{"input": "Premise: Lyme Disease is caused by a bacterium that's transmitted by tick bite, but many infected people don't remember a bite. \n Hypothesis: Lyme disease is caused by bacteria.", "output": "entails", "explanation": "The premise sentence agrees with the hypothesis that Lyme Disease is a bacterium. The prem...	[{"input": "Premise: A polyploid is simply an organism that contains more than the usual two sets of chromosomes. \n Hypothesis: A(n) polyploid is an individual with more than the correct number of chromosome sets.", "output": "neutral", "explanation": "The premise explains the meaning of the term and the hypothesis s...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1529	https://huggingface.co/datasets/Lots-of-LoRAs/task1529_scitail1.1_classification	scitail1.1 classification
699	task699_mmmlu_answer_generation_high_school_biology	You are given a question on high school biology. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer.	[ "Question Answering" ]	[ "Biology" ]	[ "measuring_massive_multitask_language_understanding" ]	[ "Scientific Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sujan Reddy A" ]	[{"input": "In a population of giraffes, an environmental change occurs that favors individuals that are tallest. As a result, more of the taller individuals are able to obtain nutrients and survive to pass along their genetic information. This is an example of\n(A)directional selection. (B)stabilizing selection. (C)se...	[{"input": "In a population of giraffes, an environmental change occurs that favors individuals that are tallest. As a result, more of the taller individuals are able to obtain nutrients and survive to pass along their genetic information. This is an example of\n(A)directional selection. (B)stabilizing selection. (C)se...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task699	https://huggingface.co/datasets/Lots-of-LoRAs/task699_mmmlu_answer_generation_high_school_biology	mmmlu answer generation high school biology
270	task270_csrg_counterfactual_context_generation	Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial context, provide...	[ "Story Composition" ]	[ "Story" ]	[ "timetravel" ]	[ "Commonsense Reasoning", "Counterfactual Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Maitreya Patel" ]	[{"input": "Premise: Brad stole the ball from the opponent. \n Initial Context: While he was running with the ball, he noticed his friend. \n Original Ending: He threw the ball in the air, near the hoop. His friend grabbed the ball and made a drunk. That score put his team in the lead. \n New ending: He stopped dancing...	[{"input": "Premise: Stephanie went to Six Flags for the first time. \n Initial Context: She had never been on a roller coaster before. \n Original Ending: Her friend told her she would ride with her to encourage her. They got on the roller coaster and waited for it to start. When it began, the girls screamed, laughed,...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task270	https://huggingface.co/datasets/Lots-of-LoRAs/task270_csrg_counterfactual_context_generation	csrg counterfactual context generation
1391	task1391_winogrande_easy_answer_generation	In this task, you are given a question containing a blank (_) and two options. You should pick the best option to answer the question. Please answer with "A" or "B".	[ "Coreference Resolution" ]	[ "Commonsense -> Concepts and Relations -> Social Commonsense", "Commonsense -> Concepts and Relations -> Physical Commonsense" ]	[ "winogrande" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Yeganeh Kordi" ]	[{"input": "Katrina gave Christine a stuffed animal for their birthday, but _ already had this one. (A) Katrina (B) Christine", "output": "B", "explanation": "Since the blank is someone who received the gift and already had a stuffed animal, the answer must be \"Christine\"."}, {"input": "Jessy decided to clean the flo...	[{"input": "Ian got into position and punched Lawrence so hard that his mouthpiece flew right out because _ was a quick fighter. (A) Ian (B) Lawrence", "output": "C", "explanation": "The issue is that the answer is not one of the options presented in the question which are \"A\" and \"B\". Note that, a valid answer mus...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1391	https://huggingface.co/datasets/Lots-of-LoRAs/task1391_winogrande_easy_answer_generation	winogrande easy answer generation
1572	task1572_samsum_summary	In this task, you are given a conversation, and your task is to generate a summary from the information present in the given conversation. Generate a summary in such a way that the context should be present in the conversation. It should cover the complete context of the conversation.	[ "Summarization" ]	[ "Dialogue", "Commonsense -> Concepts and Relations -> Social Commonsense" ]	[ "samsum" ]	[ "Commonsense Reasoning -> Social Situations", "Reasoning on Social Interactions" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Amrit Bhaskar" ]	[{"input": " Lucas: Hey! How was your day?, Demi: Hey there! , Demi: It was pretty fine, actually, thank you!, Demi: I just got promoted! :D, Lucas: Whoa! Great news!, Lucas: Congratulations!, Lucas: Such a success has to be celebrated., Demi: I agree! :D, Demi: Tonight at Death & Co.?, Lucas: Sure!, Lucas: See you the...	[{"input": " Laura: ok , I'm done for today-), Laura: let me know once u're free and we come back home together, Kim: hmm.. 7?, Laura: ok, Kim: cool, wait for me at work, I'll call once I get here ", "output": "Laura will pick up Kim from work around 7, and they will go restaurant together.", "explanation": "This is an...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1572	https://huggingface.co/datasets/Lots-of-LoRAs/task1572_samsum_summary	samsum summary
1598	task1598_nyc_long_text_generation	The task is to write a full sentence or two using all of the information given. The sentence(s) will be a brief review of a restaurant. Use all of the information provided.	[ "Data to Text" ]	[ "Public Places -> Restaurants", "Reviews -> Restaurants" ]	[ "nyc" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Abdullah Masud" ]	[{"input": "name[xname], cuisine[Fast Food], rating[average], familyFriendly[yes], near[xnear]", "output": "Located near xnear, xname serves Fast food and is child friendly. its customer rating is: average.", "explanation": "This is a good example of the task because the written sentence uses all of the given informati...	[{"input": "name[xname], recommend[yes], decor[good], qual[acceptable], service[good]", "output": "xname is a restaurant with poor service but acceptable food and good decor.", "explanation": "This is a bad example because the sentence does not match the given information (service is poor instead of good.) Also it is m...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1598	https://huggingface.co/datasets/Lots-of-LoRAs/task1598_nyc_long_text_generation	nyc long text generation
515	task515_senteval_odd_word_out	In this task, you are given a sentence. You must judge whether a single noun or verb has been replaced with another word with the same part of speech. The inversion would result in the sentence sounding unnatural, So unnatural sentences will be considered changed. Label the instances as "Original" or "Changed" based on...	[ "Linguistic Probing" ]	[ "Narrative", "Commonsense -> Concepts and Relations" ]	[ "senteval" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Amirreza Mirzaei" ]	[{"input": "Gideon brought his phone to his ear and resonated with Bev at HQ .", "output": "Changed", "explanation": "\"resonated\" doesn't fit in this sentence."}, {"input": "The frankness of her question startled him for a minute , but this was Nikki , and he really shouldn 't have been surprised .", "output": "Origi...	[{"input": "She started to prolong the basket , and I sat down across from her , folding my knees to my chest .", "output": "Original", "explanation": "The word \"prolong\" doesn't fit in this sentence so the output should be Changed."}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task515	https://huggingface.co/datasets/Lots-of-LoRAs/task515_senteval_odd_word_out	senteval odd word out
620	task620_ohsumed_medical_subject_headings_answer_generation	Given an abstract, generate a keyword (a noun phrase) that best describes the focus or contribution of the paper. Such keywords can be directly from the given abstract or outside it.	[ "Keyword Tagging" ]	[ "Scientific Research Papers" ]	[ "ohsumed" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Saicharan Papani" ]	[{"input": "Abstract: Some patients converted from ventricular fibrillation to organized rhythms by defibrillation - trained ambulance technicians(EMT - Ds) will refibrillate before hospital arrival.The authors analyzed 271 cases of ventricular fibrillation managed by EMT - Ds working without paramedic back - up.Of 111...	[{"input": "Abstract: Our results suggest that ethylene oxide retention after sterilization is increased in cuprammonium cellulose plate dialyzers containing potting compound. In contrast, cuprammonium cellulose plate dialyzers without potting compound were characterized by a rapid disappearance of retained ethylene ox...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task620	https://huggingface.co/datasets/Lots-of-LoRAs/task620_ohsumed_medical_subject_headings_answer_generation	ohsumed medical subject headings answer generation
629	task629_dbpedia_14_classification	In this task, you are given a text which is the body of a document. Your job is to classify the topic of the document into these categories: 1)Company, 2)Educational Institution, 3)Artist, 4)Athlete, 5)Office Holder, 6)Mean of transportation, 7)Building, 8)Natural place, 9)Village, 10)Animal, 11)Plant, 12)Album, 13)Fil...	[ "Text Categorization" ]	[ "Wikipedia" ]	[ "dbpedia_14" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Divya Reddy Katpally" ]	[{"input": "Text: Abbott of Farnham E D Abbott Limited was a British coachbuilding business based in Farnham Surrey trading under that name from 1929. A major part of their output was under sub-contract to motor vehicle manufacturers. Their business closed in 1972.", "output": "1", "explanation": "Here, the given text ...	[{"input": "Text: T\u221a\u00a9o Kardum (born 24 July 1986 in Split) is a Croatian association footballer who is currently playing for NK Dugopolje in the Druga HNL.", "output": "3", "explanation": "Here, the given text is about a Croatian footballer. Hence, the correct answer is \"4\"."}, {"input": "Text: The Fokker F...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task629	https://huggingface.co/datasets/Lots-of-LoRAs/task629_dbpedia_14_classification	dbpedia 14 classification
723	task723_mmmlu_answer_generation_moral_disputes	You are given a question on moral disputes. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer.	[ "Question Answering" ]	[ "Moral Scenarios" ]	[ "measuring_massive_multitask_language_understanding" ]	[ "Ethics" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sujan Reddy A" ]	[{"input": " Just war theory's principle of military necessity belongs to\n(A)jus in bello. (B)jus ad bellum. (C)moral nihilism. (D)all of the above", "output": "A", "explanation": "Just war theory's principle of military necessity belongs to jus in bello"}, {"input": " According to Mill, censoring speech that is possi...	[{"input": " Just war theory's principle of military necessity belongs to\n(A)jus in bello. (B)jus ad bellum. (C)moral nihilism. (D)all of the above", "output": "I dont know.", "explanation": "Do not generate anything else apart from one of the following characters: 'A', 'B, 'C', 'D'."}, {"input": " According to Mill, ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task723	https://huggingface.co/datasets/Lots-of-LoRAs/task723_mmmlu_answer_generation_moral_disputes	mmmlu answer generation moral disputes
1204	task1204_atomic_classification_hinderedby	In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ...	[ "Commonsense Classification" ]	[ "Sociology", "Commonsense -> Concepts and Relations -> Social Commonsense" ]	[ "atomic" ]	[ "Relational Reasoning", "Reasoning on Social Interactions", "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Yeganeh Kordi" ]	[{"input": "Head: PersonX touches a nerve<sep>Tail: PersonX is too nice", "output": "Yes", "explanation": "This is a good example. The Tail can hinder the Head."}, {"input": "Head: PersonX attends school<sep>Tail: To be a student", "output": "No", "explanation": "In this example, The Head can't be hindered by the Tail....	[{"input": "Head: PersonX asks if PersonY was okay<sep>Tail: to thank PersonX", "output": "Yes", "explanation": "In this example, The Head can't be hindered by the Tail. So the output should be \"No\"."}, {"input": "Head: PersonX clenches PersonY's jaw<sep>Tail: PersonY is out of reach.", "output": "No", "explanation":...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1204	https://huggingface.co/datasets/Lots-of-LoRAs/task1204_atomic_classification_hinderedby	atomic classification hinderedby
1152	task1152_bard_analogical_reasoning_causation	Two analogies that relate actions with their consequences are given in the form "A : B. C : ?". The phrase "A : B" relates action A to consequence B. Your task is to replace the question mark (?) with the appropriate consquence of the given action C, following the "A : B" relation. Your answer should be a single verb, ...	[ "Word Analogy" ]	[ "Commonsense" ]	[ "bard" ]	[ "Relational Reasoning", "Commonsense Reasoning", "Analogical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Arjun Ashok" ]	[{"input": "throw : fly. aspire : ?", "output": "attain", "explanation": "Fly is a causation of throw. Hence, the inferred analogy being causation, attain is the causation of aspire."}, {"input": "listen : hear. drop : ?", "output": "fall", "explanation": "Hear is a causation of listen. Hence, the inferred analogy bein...	[{"input": "cut : bleed. crush : ?", "output": "throw", "explanation": "Bleed in a causation of cut. Hence, the analogy given is causation. But, throw is not a causation of crush."}, {"input": "nourish : grow. listen : ?", "output": "break", "explanation": "Grow is a causation of nourish. Hence, the analogy given is ca...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1152	https://huggingface.co/datasets/Lots-of-LoRAs/task1152_bard_analogical_reasoning_causation	bard analogical reasoning causation
1342	task1342_amazon_us_reviews_title	Given an Amazon customer review, write a title for the review. The preferred titles are under fifteen words.	[ "Title Generation" ]	[ "Reviews" ]	[ "amazon_us_reviews" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Vinayak Kothari" ]	[{"input": "I was very surprised at the high quality of the stitching, the sturdiness of the handles and the padding for my laptop. The price is amazingly low and the look is very good. I am quite happy with this purchase. It fit my MacBook Pro perfectly, with a little bit of room to spare.", "output": "Pleasantly surp...	[{"input": "I was very surprised at the high quality of the stitching, the sturdiness of the handles and the padding for my laptop. The price is amazingly low and the look is very good. I am quite happy with this purchase. It fit my MacBook Pro perfectly, with a little bit of room to spare.", "output": "One Star", "exp...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1342	https://huggingface.co/datasets/Lots-of-LoRAs/task1342_amazon_us_reviews_title	amazon us reviews title
1534	task1534_daily_dialog_question_classification	You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. If the conversation begins with a question, label it '1' otherwise '0'.	[ "Dialogue Act Recognition" ]	[ "Dialogue" ]	[ "dailydialog" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Krishna Sriharsha Gundu" ]	[{"input": "Person1: Passport , please , madam . \n Person2: Just a minute , please . It's in my bag . Here it is . \n Person1: Thank you . Please fill out the Baggage Declaration Form . \n Person2: All right . Shall I enter all my belongings ? \n Person1: No , only the articles listed on the Declaration . ...	[{"input": "Person1: Can I borrow five bucks ? \n Person2: No ! \n Person1: Come on ! I'll pay you back on Tuesday . \n Person2: Last time I lent you money , you never paid me back . \n Person1: I promise if you lend me five dollars today , I will repay you in full next week . \n Person2: Ok , but I'm tak...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1534	https://huggingface.co/datasets/Lots-of-LoRAs/task1534_daily_dialog_question_classification	daily dialog question classification
1722	task1722_civil_comments_threat_classification	Categorize the comment on the basis of threat. If the comment is threatening output Yes, otherwise output No.	[ "Toxic Language Detection" ]	[ "Dialogue", "Social Media" ]	[ "civil_comments" ]	[ "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Himanshu Asati" ]	[{"input": "Baloney. You are going to see real action against Herr Trump and his white supremacist agenda.", "output": "Yes", "explanation": "The comment suggests threat against Trump and his agendas and classified as threatening. Hence, it is a positive example"}, {"input": "Perfect analysis and statements.", "output...	[{"input": "Yet call out all Muslims for the acts of a few will get you pilloried. So why is it okay to smear an entire religion over these few idiots? Or is this because it's okay to bash Christian sects?", "output": "Yes", "explanation": "The comment is genuine argument with no particular threat to Muslims or Christi...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1722	https://huggingface.co/datasets/Lots-of-LoRAs/task1722_civil_comments_threat_classification	civil comments threat classification
084	task084_babi_t1_single_supporting_fact_identify_relevant_fact	You will be given a passage with an enumerated set of facts, a question of form 'Where is <person_name>?', and its answer. The task is to identify a supporting fact that is necessary to answer the question. The output would be the corresponding fact number.	[ "Question Answering" ]	[ "Commonsense -> Concepts and Relations -> Spatial Commonsense" ]	[ "babi" ]	[ "Commonsense Reasoning -> Physical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Shailaja Keyur Sampat" ]	[{"input": "Passage: Fact 1- Mary moved to the bathroom. Fact 2- John went to the hallway. Question: Where is Mary? Answer: bathroom", "output": "Fact 1", "explanation": "Fact 1- 'Mary moved to the bathroom.' is a supporting fact from which we can conclude that Mary is in bathroom therefore the output is- Fact 1."}, {"...	[{"input": "Passage: Fact 1- Mary moved to the bathroom. Fact 2- John went to the hallway. Question: Where is Mary? Answer: bathroom", "output": "Fact 2", "explanation": "The question asks about the location of Mary whereas fact 2 mentions about John. Therefore, fact 2 cannot be a supporting fact to answer this questio...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task084	https://huggingface.co/datasets/Lots-of-LoRAs/task084_babi_t1_single_supporting_fact_identify_relevant_fact	babi t1 single supporting fact identify relevant fact
637	task637_extract_and_sort_unique_digits_in_a_list	In this task, you are given an input list A. You need to extract and sort the unique digits used in the list in ascending order. Return -1 if there is no digit in the list.	[ "Program Execution" ]	[ "Mathematics" ]	[ "synthetic" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Pulkit Verma" ]	[{"input": "['q', '31', 'a', 'd', '53', '85', 'p', '77']", "output": "1, 3, 5, 7, 8", "explanation": "Here, the numbers in the list are '31', '53', '85' and '77', and the unique digits used in the list are '1, 3, 5, 7, 8' in ascending order."}, {"input": "['223', u, 'r', '540', 'k']", "output": "0, 2, 3, 4, 5", "explan...	[{"input": "['g', 'w', 'x', '3467', 'g']", "output": " 7, 6, 3, 4", "explanation": "Here, the answer should have been '3, 4, 6, 7' as '3467' is the only number in the list, and its digits in ascending order are '3, 4, 6, 7' in ascending order."}, {"input": "['75', '54', 'J', 'L', '2332', 'Z', 'e']", "output": " 7, 5, 4...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task637	https://huggingface.co/datasets/Lots-of-LoRAs/task637_extract_and_sort_unique_digits_in_a_list	extract and sort unique digits in a list
1283	task1283_hrngo_quality_classification	You are given an original reference as well as a system reference. Your task is to judge the quality of the system reference. If the utterance is grammatically correct and fluent output 1, else output 0.	[ "Text Quality Evaluation" ]	[ "Dialogue", "Public Places -> Restaurants" ]	[ "human_ratings_of_natural_language_generation_outputs" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sujan Reddy A" ]	[{"input": "System Reference: there is a chinese restaurant on x called x.\nOriginal Reference: x is a chinese restaurant in x.", "output": "1", "explanation": "The system reference is grammatically correct and fluent."}, {"input": "System Reference: x is a restaurant recommend.\nOriginal Reference: x is a cafe restaur...	[{"input": "System Reference: x is a reasonably priced fast food restaurant down by river cheap.\nOriginal Reference: x is a cheap fastfood restaurant located near the riverside.", "output": "5.5", "explanation": "The output has to be 1 or 0."}, {"input": "System Reference: x is a restaurant that serves italian serving...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1283	https://huggingface.co/datasets/Lots-of-LoRAs/task1283_hrngo_quality_classification	hrngo quality classification
290	task290_tellmewhy_question_answerability	In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.	[ "Answerability Classification" ]	[ "Story" ]	[ "tellmewhy" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Amirreza Mirzaei" ]	[{"input": "Bob was a computer scientist. He enjoyed natural language processing. He decided to revolutionize the industry! He formulated a machine learning algorithm to process words. He won the nobel prize for his work!\nWhy did He formulate a machine?", "output": "Answerable", "explanation": "He formulated a machine...	[{"input": "Bob was a computer scientist. He enjoyed natural language processing. He decided to revolutionize the industry! He formulated a machine learning algorithm to process words. He won the nobel prize for his work!\nWhy did He enjoy natural language processing?", "output": "I can't decide.", "explanation": "Do n...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task290	https://huggingface.co/datasets/Lots-of-LoRAs/task290_tellmewhy_question_answerability	tellmewhy question answerability
580	task580_socialiqa_answer_generation	In this task, you're given a context, a question, and three options. Your task is to find the correct answer to the question using the given context and options. Also, you may need to use commonsense reasoning about social situations to answer the questions. Classify your answers into 'A', 'B', and 'C'.	[ "Question Answering" ]	[ "Commonsense -> Concepts and Relations -> Social Commonsense" ]	[ "social_iqa" ]	[ "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishan Purohit" ]	[{"input": "Context: Tracy didn't go home that evening and resisted Riley's attacks. \n Question: What does Tracy need to do before this? \n Options: (A) make a new plan (B) Go home and see Riley (C) Find somewhere to go", "output": "C", "explanation": "Tracy found somewhere to go and didn't come home because she wante...	[{"input": "Context: Tracy's kids wanted ice cream so Aubrey fed the kids ice cream. \n Question: What does Aubrey need to do before this? \n Options: (A) tell her kids to say thank you (B) get ice cream (C) thanks Tracy", "output": "get ice cream", "explanation": "The answer is correct, but it is supposed to only giv...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task580	https://huggingface.co/datasets/Lots-of-LoRAs/task580_socialiqa_answer_generation	socialiqa answer generation
1192	task1192_food_flavor_profile	In this task, you are given the name of an Indian food dish. You need to classify the dish as "sweet" or "spicy".	[ "Misc." ]	[ "Food" ]	[ "indian_food_101" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ravsehaj Singh Puri" ]	[{"input": "Keerai poriyal", "output": "spicy", "explanation": "Keerai poriyal is spicy in flavor"}, {"input": "Kuzhi paniyaram", "output": "sweet", "explanation": "Kuzhi paniyaram is sweet in flavor"}]	[{"input": "Pindi chana", "output": "sweet", "explanation": "Pindi chana is not sweet in flavor"}, {"input": "Til Pitha", "output": "spicy", "explanation": "Til Pitha is not spicy in flavor"}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1192	https://huggingface.co/datasets/Lots-of-LoRAs/task1192_food_flavor_profile	food flavor profile
453	task453_swag_answer_generation	Given a sentence, generate what should be the most likely next statement. The next statement should be reasonable and logically correct.	[ "Text Completion" ]	[ "Captions -> Video Captions", "Story" ]	[ "swag" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Kuntal Kumar Pal" ]	[{"input": "We notice a man in a kayak and a yellow helmet coming in from the left. As he approaches, his kayak ", "output": "flips upside - down", "explanation": "Flipping of the kayak is a probable event. It is a logical next statement, given the context."}, {"input": "On stage, a woman takes a seat at the piano. She...	[{"input": "He is throwing darts at a wall. A woman", "output": "collapses and falls to the floor.", "explanation": "The output is a valid statement but it is not at all related to the event in the context. "}, {"input": "On stage, a woman takes a seat at the piano. She", "output": "is in the crowd, watching the dancer...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task453	https://huggingface.co/datasets/Lots-of-LoRAs/task453_swag_answer_generation	swag answer generation
1384	task1384_deal_or_no_dialog_classification	Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.	[ "Dialogue State Tracking" ]	[ "Dialogue", "Commonsense -> Concepts and Relations -> Social Commonsense" ]	[ "deal_or_no_dialog" ]	[ "Commonsense Reasoning -> Social Situations", "Reasoning on Social Interactions" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Hsiao, Sheng-Hung" ]	[{"input": "THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t ...	[{"input": "THEM: lemme get that book and ball! YOU: i need 2 balls and a hat THEM: i'll take the book and two hats then? YOU: ok.", "output": "No", "explanation": "Both participants agree to the deal, so the correct answer is Yes."}, {"input": "THEM: hello. i would like the book and one ball. YOU: you can have one...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1384	https://huggingface.co/datasets/Lots-of-LoRAs/task1384_deal_or_no_dialog_classification	deal or no dialog classification
167	task167_strategyqa_question_generation	In this task, you are presented with a term, a description of the term, and an expected answer ('yes' or 'no'). You should write a yes-no question about the given term such that the answer is the one provided to you (i.e., If the answer is "No", you should ask a question that its answer would be "No", and if the answer...	[ "Question Generation" ]	[ "Wikipedia" ]	[ "strategyqa" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Yeganeh Kordi" ]	[{"input": "Term: Cooking oil, Description: Oil consumed by humans, from vegetable or animal origin., Answer:No", "output": "Can all types of cooking oil be poured?", "explanation": "This is a good question. For answering this question, you need to know different cooking oils and whether they can be poured."}, {"input"...	[{"input": "Term: New York City, Description: The City of New York, usually called either New York City (NYC) or simply New York (NY), is the most populous city in the United States.", "output": "How many people visited New York City in July 2007?", "explanation": "It is not obvious that this kind of information is ava...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task167	https://huggingface.co/datasets/Lots-of-LoRAs/task167_strategyqa_question_generation	strategyqa question generation
956	task956_leetcode_420_strong_password_check	You are given a password and you need to generate the number of steps required to convert the given password to a strong password. A password is considered strong if (a) it has at least 6 characters and at most 20 characters; (b) it contains at least one lowercase letter and one uppercase letter, and at least one digit...	[ "Text to Code" ]	[ "Mathematics" ]	[ "leetcode" ]	[ "Logical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Derek Shi" ]	[{"input": "password = a", "output": "5", "explanation": "Using 5 steps, it can become a strong password"}, {"input": "password = aA1", "output": "3", "explanation": "Using 3 steps, it can become a strong password"}]	[{"input": "password = 1337C0d3", "output": "1", "explanation": "This is incorrect, because it is a strong password"}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task956	https://huggingface.co/datasets/Lots-of-LoRAs/task956_leetcode_420_strong_password_check	leetcode 420 strong password check
1631	task1631_openpi_answer_generation	Given an entity, a before event, an after event, and an attribute related to the entity, generate a sentence as output. Your sentence should show the changes in the attribute of the entity.	[ "Data to Text" ]	[ "Web" ]	[ "open_pi" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Anshita Singh Bais" ]	[{"input": " entity: arm \nbefore: free \nafter: grasped \nattr: state", "output": "state of arm was free before and grasped afterwards", "explanation": "The state of the arm was free before and afterwards it was grasped hence the output is correct."}, {"input": "entity: person \nbefore: standing \nafter: in air \nattr...	[{"input": "entity: buckles \nbefore: being worn \nafter: removed \nattr: wearing", "output": "wearing of buckles was being worn before and removed afterwards", "explanation": "Here wearing of buckles is grammatically incorrect and the output sentence should be the buckles were worn before and removed afterwards."}, {"...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1631	https://huggingface.co/datasets/Lots-of-LoRAs/task1631_openpi_answer_generation	openpi answer generation
460	task460_qasper_answer_generation	In this task, you will be presented with a context from an academic paper and a question separated with a . You have to answer the question based on the context.	[ "Question Answering" ]	[ "Scientific Research Papers" ]	[ "qasper" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Yeganeh Kordi" ]	[{"input": "We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. Large-Scale Chinese Short Text Summarization Dataset (LCSTS) is constructed by BIBREF1 . The dataset consists of more than 2.4 million text-summary pairs in total, constructed from...	[{"input": "The minimal change operation substantially changed the meaning of the sentence, and yet the embedding of the transformation lies very closely to the original sentence (average similarity of 0.930). \n Question: Do they do any analysis of of how the modifications changed the starting set of sentences?", "out...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task460	https://huggingface.co/datasets/Lots-of-LoRAs/task460_qasper_answer_generation	qasper answer generation
574	task574_air_dialogue_sentence_generation	In this task, you're given a dialogue between a customer and a flight booking agent with a gap in the conversation. Your job is to find the answer of the previous dialogue. Avoid using irrelevant extra information while creating the answer. The answer should be relevant to the question before the blank. If you fill the...	[ "Dialogue Generation" ]	[ "Dialogue" ]	[ "air_dialogue" ]	[ "Reasoning on Social Interactions" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Jayavardhan Karampudi" ]	[{"input": "customer: Hello. \n agent: Hello. How may I help you? \n customer: I would like to do some changes in my existing reservation, can you please help me out? \n agent: Sure, I will help you in booking. May I know your name to proceed further? \n __ \n agent: Alexander Hernandez, regret to inform that there is...	[{"input": "customer: Hello, I am Pamela Jones. \n agent: Hello. How can I aid you? \n customer: I need to book a flight ticket from DEN to LAS, Can you please help me for booking? \n __ \n customer: I need a connection limit. \n agent: Please share me your travelling dates. \n customer: I would like to travel on 03/25...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task574	https://huggingface.co/datasets/Lots-of-LoRAs/task574_air_dialogue_sentence_generation	air dialogue sentence generation
697	task697_mmmlu_answer_generation_formal_logic	You are given a question on formal logic. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer.	[ "Question Answering" ]	[ "Logic -> Formal logic" ]	[ "measuring_massive_multitask_language_understanding" ]	[ "Logical Reasoning", "Mathematics" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sujan Reddy A" ]	[{"input": "Identify the conclusion of the following argument. It is hard not to verify in our peers the same weakened intelligence due to emotions that we observe in our everyday patients. The arrogance of our consciousness, which in general, belongs to the strongest defense mechanisms, blocks the unconscious complexe...	[{"input": "Identify the conclusion of the following argument. It is hard not to verify in our peers the same weakened intelligence due to emotions that we observe in our everyday patients. The arrogance of our consciousness, which in general, belongs to the strongest defense mechanisms, blocks the unconscious complexe...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task697	https://huggingface.co/datasets/Lots-of-LoRAs/task697_mmmlu_answer_generation_formal_logic	mmmlu answer generation formal logic
1158	task1158_bard_analogical_reasoning_manipulating_items	Two analogies on manipulating items in a kitchen is given in the form "A : B. C : ?". The phrase "A : B" relates item A to its appropriate manipulation B. Your task is to replace the question mark (?) with the appropriate manipulation of item C, following the "A : B" relation. Your answer should be a verb which shows a...	[ "Word Analogy" ]	[ "Commonsense" ]	[ "bard" ]	[ "Relational Reasoning", "Commonsense Reasoning", "Analogical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Arjun Ashok" ]	[{"input": "jug : pour. shoe : ?", "output": "untie", "explanation": "The given analogy relates items to how they are manipulated. Jugs can be poured into. Shoes can be untied."}, {"input": "jar : open. box : ?", "output": "open", "explanation": "The given analogy relates items to how they are manipulated. Jars can be ...	[{"input": "backpack : unzip. safe : ?", "output": "travel", "explanation": "The given analogy relates items to how they are manipulated. Backpacks can be unzipped. Safes CANNOT be travelled, and so it not the correct answer."}, {"input": "faucet : turn. bag : ?", "output": "cupboard", "explanation": "The given analogy...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1158	https://huggingface.co/datasets/Lots-of-LoRAs/task1158_bard_analogical_reasoning_manipulating_items	bard analogical reasoning manipulating items
1590	task1590_diplomacy_text_generation	You are given first 5 messages from a series of message exchanges between 2 persons playing the game of Diplomacy which is an American strategic board game. You need to generate the next message. The message should be generated such that it fits the context seen so far. Avoid the text that is (i) tangent to the context...	[ "Dialogue Generation" ]	[ "Game", "Dialogue" ]	[ "diplomacy_detection" ]	[ "Reasoning on Social Interactions", "Commonsense Reasoning -> Social Situations" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Roseleen Kaur" ]	[{"input": "['Heyyyy Turkey', 'Whatcha thinking re: start of the game?', \"It kind of depends. I'll probably want to stop Russia from advancing south\", \"I'm kind of afraid of Austria and Russia teaming together on me\", 'I mean if that happens you\u2019re donezos']", "output": "What vibes are you getting from each of...	[{"input": "[\"Hey italy! good luck this game. I'm guessing you and Austria will be pals, you and France will be rivals?\", 'Well good luck to you too! No idea yet who is a friend. Have you heard anything interesting?', \"I have some agreements with France. If those are upheld, I'd bet France goes for Por and Spain in ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1590	https://huggingface.co/datasets/Lots-of-LoRAs/task1590_diplomacy_text_generation	diplomacy text generation
1451	task1451_drug_dose_extraction	In this task, you will be given sentences and a drug name in which your task is to indicate the doses of intake of that particular drug. A dose refers to a specified amount of medication taken at one time. Although there might be several correct answers, you need to write one of them.	[ "Information Extraction" ]	[ "Biology -> Clinical Knowledge", "Healthcare" ]	[ "ade_corpus_v2" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishani Mondal" ]	[{"input": "An episode of subacute encephalopathy after the infusion of methotrexate (1500 mg/m2) (MTX) is reported in a young adult with metastastic gastric cancer.\t methotrexate", "output": "1500 mg/m2", "explanation": "Here, the drug methotrexate mentioned after '\t ' has been mentioned to be taken as 1500 mg/m2 wi...	[{"input": "Ibuprofen overdose is usually characterized by GI upset, dizziness, and mild sedation\t ibuprofen", "output": "mild", "explanation": "Here the drug ibuprofen has been mentioned to be taken in excess but mild is the qualifier of the sedation caused by overdose of the drug, hence mild should not be tagged as ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1451	https://huggingface.co/datasets/Lots-of-LoRAs/task1451_drug_dose_extraction	drug dose extraction
247	task247_dream_answer_generation	In this task, you will be shown a conversation and a question. You need to answer the question and choose the correct option based on the conversation. "W" and "M" in the conversations stand for "woman" and "man".	[ "Question Answering" ]	[ "Dialogue", "Natural Science -> School Science Textbooks" ]	[ "dream" ]	[ "Reasoning on Social Interactions", "Logical Reasoning", "Commonsense Reasoning", "Numerical Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Yeganeh Kordi" ]	[{"input": "M: I am considering dropping my dancing class. I am not making any progress. W: If I were you, I stick with it. It's definitely worth time and effort., Question: What does the man suggest the woman do? (A) Consult her dancing teacher. (B) Take a more interesting class. (C) Continue her dancing class.", "out...	[{"input": "W: Well, I'm afraid my cooking isn't to your taste. M: Actually, I like it very much. W: I'm glad you enjoy it. Let me serve you some more fish. M: No, thank you. I've had enough fish, but I'd like some soup. W: Here it is. Help yourself! M: Thanks. I didn't know you were so good at cooking. If only my wife...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task247	https://huggingface.co/datasets/Lots-of-LoRAs/task247_dream_answer_generation	dream answer generation
1566	task1566_propara_structured_text_generation	In this task, you are given a paragraph, and your job is to generate comma-separated entities present in the given paragraph. Generate entities from a given passage in such a way that (i) they are present in the paragraph, (ii) they are non-duplicate, (iii) they underwent a state change during the process. Avoid creati...	[ "Named Entity Recognition" ]	[ "Natural Science" ]	[ "propara" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Amrit Bhaskar" ]	[{"input": " Magma rises from deep in the earth. The magma goes into volcanos. The volcanos pressure the magma upwards. The pressure causes the magma to push through the surface of the volcano. The lava cools. The lava forms new rock. New magma is pressured to the surface of the volcano. The volcano bursts through the ...	[{"input": " Water from oceans, lakes, swamps, rivers, and plants turns into water vapor. Water vapor condenses into millions of tiny droplets that form clouds. Clouds lose these droplets through rain or snow, also caused precipitation. Precipitation is either absorbed into the ground or runs off into rivers. Water tha...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1566	https://huggingface.co/datasets/Lots-of-LoRAs/task1566_propara_structured_text_generation	propara structured text generation
516	task516_senteval_conjoints_inversion	In this task you are given a sentence with one coordinating conjunction (for, and, nor, but, or, yet, and so). You must judge whether the order of two coordinated clausal conjoints have been inverted or not. Inversion would result in the sentence sounding unnatural. Label the instances as "Original" or "Inversion" base...	[ "Linguistic Probing" ]	[ "Narrative", "Commonsense -> Concepts and Relations" ]	[ "senteval" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Amirreza Mirzaei" ]	[{"input": "He knew it , and he deserved no answer .", "output": "Inversion", "explanation": "\"He knew it\" and \"he deserved no answer\" have been inverted."}, {"input": "Clary saw his features tighten , but his face was in shadow .", "output": "Inversion", "explanation": "\"Clary saw his features tighten\" and \"his...	[{"input": "My eyes adjust to the darkness and I can see signs of a scuffle behind the counter .", "output": "Inversion", "explanation": "The two clausal conjoints in this sentence have not been inverted so output should be \"Original\"."}]	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task516	https://huggingface.co/datasets/Lots-of-LoRAs/task516_senteval_conjoints_inversion	senteval conjoints inversion
605	task605_find_the_longest_common_subsequence_in_two_lists	In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.	[ "Program Execution" ]	[ "Mathematics" ]	[ "synthetic" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Pulkit Verma" ]	[{"input": "[5797, 8817, '8297', 'b', 'U', 'b'], [5843, 8809, '8297', 'b', 'W', 'C']", "output": "8297, b", "explanation": "Here, '8297, b' is the longest common subsequence in both the input lists [5797, 8817, '8297', 'b', 'U', 'b'] and [5843, 8809, '8297', 'b', 'W', 'C']."}, {"input": "[3353, 'x', '6339', 'v', 'M', 3...	[{"input": "['Q', 7681, 'n', 'A', 'I', 'Q', 'N', 'c'], ['n', 4799, 'n', 'A', 'I', 'T', 'Y']", "output": "n, A", "explanation": "Here, the answer should have been 'n, A, I' as it is the longest common subsequence in both the input lists ['Q', 7681, 'n', 'A', 'I', 'Q', 'N', 'c'] and ['n', 4799, 'n', 'A', 'I', 'T', 'Y']."...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task605	https://huggingface.co/datasets/Lots-of-LoRAs/task605_find_the_longest_common_subsequence_in_two_lists	find the longest common subsequence in two lists
685	task685_mmmlu_answer_generation_clinical_knowledge	You are given a question on clinical knowledge. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer.	[ "Question Answering" ]	[ "Biology -> Clinical Knowledge" ]	[ "measuring_massive_multitask_language_understanding" ]	[ "Scientific Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Sujan Reddy A" ]	[{"input": "What size of cannula would you use in a patient who needed a rapid blood transfusion (as of 2020 medical knowledge)?\n(A)18 gauge. (B)20 gauge. (C)22 gauge. (D)24 gauge.", "output": "A", "explanation": "18 gauge would be used in a patient who needed a rapid blood transfusion"}, {"input": "The key attribute ...	[{"input": "What size of cannula would you use in a patient who needed a rapid blood transfusion (as of 2020 medical knowledge)?\n(A)18 gauge. (B)20 gauge. (C)22 gauge. (D)24 gauge.", "output": "I dont know.", "explanation": "Do not generate anything else apart from one of the following characters: 'A', 'B, 'C', 'D'."}...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task685	https://huggingface.co/datasets/Lots-of-LoRAs/task685_mmmlu_answer_generation_clinical_knowledge	mmmlu answer generation clinical knowledge
1135	task1135_xcsr_en_commonsense_mc_classification	In this task, you will be presented with a question that has multiple possible answers. You should choose the most suitable option out of "A", "B", "C", "D", and "E", based on your commonsense knowledge.	[ "Question Answering" ]	[ "Commonsense" ]	[ "x_csr" ]	[ "Commonsense Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Maitreya Patel" ]	[{"input": "Question: The dental office handled a lot of patients who experienced traumatic mouth injury, where were these patients coming from? \n Options: (A) town (B) michigan (C) hospital (D) schools (E) office building ", "output": "C", "explanation": "This is the correct answer because the traumatic injuries are ...	[{"input": "Question: The ticket booth informed riders that the train was running late, so where was the ticket booth located? \n Options: (A) movie theatre (B) sports arena (C) school (D) metro station (E) auditorium ", "output": "A", "explanation": "This is incorrect answer. Because the train is running late. Hence, ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1135	https://huggingface.co/datasets/Lots-of-LoRAs/task1135_xcsr_en_commonsense_mc_classification	xcsr en commonsense mc classification
1714	task1714_convai3_sentence_generation	You are given a concatenated string consisting of two parts that are separated by a newline character. The first part is the user's initial question during a human computer conversation, the second part is a clarifying question asked by the computer in response to the question asked by the user. You should read the inp...	[ "Dialogue Generation" ]	[ "Dialogue" ]	[ "clariq" ]	[ "Commonsense Reasoning -> Social Situations", "Reasoning on Social Interactions", "Abductive Reasoning" ]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Qiang Fu" ]	[{"input": "User: Find information about joints in the human body. \nComputer: what specific joint are you interested in", "output": "i am interested in joint pain treatments in general", "explanation": "The user want to know joints in general, not a specific joint."}, {"input": "User: Looking for locations and dates o...	[{"input": "User: Find historical information about Madam C. J. Walker. \nComputer: would you like to know about madam cj walkers products", "output": "Yes, I want to know about the products.", "explanation": "This is a negative example because the user's true intent is to find historical information about the person, ...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1714	https://huggingface.co/datasets/Lots-of-LoRAs/task1714_convai3_sentence_generation	convai3 sentence generation
1452	task1452_location_entity_extraction_btc_corpus	In this task, you will be given sentences in which your task is to recognize the name of the location or place. Although there might be several correct answers, you need to write one of them.	[ "Named Entity Recognition" ]	[ "Geography", "Social Media -> Twitter" ]	[ "broad_twitter_corpus" ]	[]	[ "English" ]	[ "English" ]	[ "English" ]	[ "Ishani Mondal" ]	[{"input": "I have been staying in New York for quite some time.", "output": "New York", "explanation": "New York, being a popular city in US, is considered as a location and hence should be tagged."}, {"input": "The beaches at Florida are amazingly beautiful !", "output": "Florida", "explanation": "Florida, being a po...	[{"input": "Shakespeare has been writing a lot of his novels centering around central Europe.", "output": "Europe", "explanation": "Here, Europe is an incomplete mention of the location . It is because the main qualifier, which actually helps to figure out the location is missing. The correct answer is central Europe."...	https://huggingface.co/Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task1452	https://huggingface.co/datasets/Lots-of-LoRAs/task1452_location_entity_extraction_btc_corpus	location entity extraction btc corpus

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Lots-of-LoRAs — task definitions

A flat parquet of all 1,172 task definitions corresponding to the LoRAs hosted at Lots-of-LoRAs (Mistral-7B-Instruct-v0.2, rank-16). Each row is one task: slug, full English definition, category/domain tags, positive/negative examples, and pointers to the matching adapter + paired training-data dataset on HF.

Source of definitions: allenai/natural-instructions. Source of LoRAs + index: Lots-of-LoRAs — paper arxiv:2407.00066.

Columns

task_id — numeric ID (matches the taskN filename in natural-instructions)
slug — task{N}_{descriptive_name}
definition — full English task description (the ground-truth label)
categories, domains, source, reasoning — natural-instructions structured tags
input_language, output_language, instruction_language — language tags
positive_examples, negative_examples — JSON-encoded list of worked examples
lora_path — HF link to the Mistral-7B LoRA adapter
dataset_path — HF link to the (input, output) training data
description_short — slug rendered as readable text

Built with

from datasets import load_dataset
ds = load_dataset('ceselder/lots-of-loras-task-definitions', split='train')

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Paper for ceselder/lots-of-loras-task-definitions

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead

Paper • 2407.00066 • Published Jun 17, 2024