Datasets:
librarian-bots
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Dataset card Data Studio Files
xet
Community
1
hub_id
large_stringlengths
6
115
config_name
large_stringlengths
1
158
likes
int64
0
1.39k
downloads
int64
0
1.15M
tags
large_stringlengths
13
64.7k
language
large_stringclasses
768 values
license
large_stringclasses
110 values
created_at
timestamp[us]date
2022-03-02 23:29:22
2025-05-24 01:27:08
last_modified
timestamp[us]date
2022-10-05 14:43:40
2025-05-24 01:36:57
features
large_stringlengths
2
897k
⌀
version
large_stringclasses
4 values
juliadollis/Qwen2.5-7B-Instruct_toxigen-data-train_zeroshot
default
0
39
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-23T01:24:51
2024-11-23T01:24:54
[{"name": "text", "dtype": "string"}, {"name": "target_group", "dtype": "string"}, {"name": "factual?", "dtype": "string"}, {"name": "ingroup_effect", "dtype": "string"}, {"name": "lewd", "dtype": "string"}, {"name": "framing", "dtype": "string"}, {"name": "predicted_group", "dtype": "string"}, {"name": "stereotyping", "dtype": "string"}, {"name": "intent", "dtype": "float64"}, {"name": "toxicity_ai", "dtype": "float64"}, {"name": "toxicity_human", "dtype": "float64"}, {"name": "predicted_author", "dtype": "string"}, {"name": "actual_method", "dtype": "string"}, {"name": "is_toxic", "dtype": "int64"}, {"name": "predicted_is_toxic", "dtype": "int64"}, {"name": "y_true", "dtype": "int64"}]
{}
tyzhu/random_letter_same_length_find_passage_train10_eval20_title
default
0
32
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-11-16T03:36:28
2023-11-16T04:52:21
[{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}]
{}
jacpetro/QwQ-32B-Preview-Synthetic-Adviser-Client-Conversation
default
0
33
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-04T21:52:35
2025-01-05T19:31:44
[{"name": "text", "dtype": "string"}, {"name": "client_name", "dtype": "string"}, {"name": "date_of_birth", "dtype": "string"}, {"name": "address", "dtype": "string"}, {"name": "citizenship", "dtype": "string"}, {"name": "phone_number", "dtype": "string"}, {"name": "job_title", "dtype": "string"}, {"name": "employer", "dtype": "string"}, {"name": "annual_income", "dtype": "string"}, {"name": "pension_info", "dtype": "string"}, {"name": "net_worth_info", "dtype": "string"}, {"name": "family_status", "dtype": "string"}, {"name": "goals_info", "dtype": "string"}, {"name": "client_style", "dtype": "string"}]
{}
guyhadad01/Sports_at5_hard-False_candidates100_max15_v8
default
0
32
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-01T08:18:38
2024-07-01T08:18:53
[{"name": "start_prompt", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "ending0", "dtype": "string"}, {"name": "ending1", "dtype": "string"}, {"name": "ending2", "dtype": "string"}, {"name": "ending3", "dtype": "string"}, {"name": "ending4", "dtype": "string"}, {"name": "ending5", "dtype": "string"}, {"name": "ending6", "dtype": "string"}, {"name": "ending7", "dtype": "string"}, {"name": "ending8", "dtype": "string"}, {"name": "ending9", "dtype": "string"}, {"name": "ending10", "dtype": "string"}, {"name": "ending11", "dtype": "string"}, {"name": "ending12", "dtype": "string"}, {"name": "ending13", "dtype": "string"}, {"name": "ending14", "dtype": "string"}, {"name": "ending15", "dtype": "string"}, {"name": "ending16", "dtype": "string"}, {"name": "ending17", "dtype": "string"}, {"name": "ending18", "dtype": "string"}, {"name": "ending19", "dtype": "string"}, {"name": "ending20", "dtype": "string"}, {"name": "ending21", "dtype": "string"}, {"name": "ending22", "dtype": "string"}, {"name": "ending23", "dtype": "string"}, {"name": "ending24", "dtype": "string"}, {"name": "ending25", "dtype": "string"}, {"name": "ending26", "dtype": "string"}, {"name": "ending27", "dtype": "string"}, {"name": "ending28", "dtype": "string"}, {"name": "ending29", "dtype": "string"}, {"name": "ending30", "dtype": "string"}, {"name": "ending31", "dtype": "string"}, {"name": "ending32", "dtype": "string"}, {"name": "ending33", "dtype": "string"}, {"name": "ending34", "dtype": "string"}, {"name": "ending35", "dtype": "string"}, {"name": "ending36", "dtype": "string"}, {"name": "ending37", "dtype": "string"}, {"name": "ending38", "dtype": "string"}, {"name": "ending39", "dtype": "string"}, {"name": "ending40", "dtype": "string"}, {"name": "ending41", "dtype": "string"}, {"name": "ending42", "dtype": "string"}, {"name": "ending43", "dtype": "string"}, {"name": "ending44", "dtype": "string"}, {"name": "ending45", "dtype": "string"}, {"name": "ending46", "dtype": "string"}, {"name": "ending47", "dtype": "string"}, {"name": "ending48", "dtype": "string"}, {"name": "ending49", "dtype": "string"}, {"name": "ending50", "dtype": "string"}, {"name": "ending51", "dtype": "string"}, {"name": "ending52", "dtype": "string"}, {"name": "ending53", "dtype": "string"}, {"name": "ending54", "dtype": "string"}, {"name": "ending55", "dtype": "string"}, {"name": "ending56", "dtype": "string"}, {"name": "ending57", "dtype": "string"}, {"name": "ending58", "dtype": "string"}, {"name": "ending59", "dtype": "string"}, {"name": "ending60", "dtype": "string"}, {"name": "ending61", "dtype": "string"}, {"name": "ending62", "dtype": "string"}, {"name": "ending63", "dtype": "string"}, {"name": "ending64", "dtype": "string"}, {"name": "ending65", "dtype": "string"}, {"name": "ending66", "dtype": "string"}, {"name": "ending67", "dtype": "string"}, {"name": "ending68", "dtype": "string"}, {"name": "ending69", "dtype": "string"}, {"name": "ending70", "dtype": "string"}, {"name": "ending71", "dtype": "string"}, {"name": "ending72", "dtype": "string"}, {"name": "ending73", "dtype": "string"}, {"name": "ending74", "dtype": "string"}, {"name": "ending75", "dtype": "string"}, {"name": "ending76", "dtype": "string"}, {"name": "ending77", "dtype": "string"}, {"name": "ending78", "dtype": "string"}, {"name": "ending79", "dtype": "string"}, {"name": "ending80", "dtype": "string"}, {"name": "ending81", "dtype": "string"}, {"name": "ending82", "dtype": "string"}, {"name": "ending83", "dtype": "string"}, {"name": "ending84", "dtype": "string"}, {"name": "ending85", "dtype": "string"}, {"name": "ending86", "dtype": "string"}, {"name": "ending87", "dtype": "string"}, {"name": "ending88", "dtype": "string"}, {"name": "ending89", "dtype": "string"}, {"name": "ending90", "dtype": "string"}, {"name": "ending91", "dtype": "string"}, {"name": "ending92", "dtype": "string"}, {"name": "ending93", "dtype": "string"}, {"name": "ending94", "dtype": "string"}, {"name": "ending95", "dtype": "string"}, {"name": "ending96", "dtype": "string"}, {"name": "ending97", "dtype": "string"}, {"name": "ending98", "dtype": "string"}, {"name": "ending99", "dtype": "string"}]
{}
datacomp/imagenet-1k-random-40.0-frac-1over4
default
0
23
["size_categories:100K<n<1M", "format:parquet", "modality:image", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-10T10:18:21
2025-01-14T03:41:56
[{"name": "image", "dtype": "image"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "tench, Tinca tinca", "1": "goldfish, Carassius auratus", "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias", "3": "tiger shark, Galeocerdo cuvieri", "4": "hammerhead, hammerhead shark", "5": "electric ray, crampfish, numbfish, torpedo", "6": "stingray", "7": "cock", "8": "hen", "9": "ostrich, Struthio camelus", "10": "brambling, Fringilla montifringilla", "11": "goldfinch, Carduelis carduelis", "12": "house finch, linnet, Carpodacus mexicanus", "13": "junco, snowbird", "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea", "15": "robin, American robin, Turdus migratorius", "16": "bulbul", "17": "jay", "18": "magpie", "19": "chickadee", "20": "water ouzel, dipper", "21": "kite", "22": "bald eagle, American eagle, Haliaeetus leucocephalus", "23": "vulture", "24": "great grey owl, great gray owl, Strix nebulosa", "25": "European fire salamander, Salamandra salamandra", "26": "common newt, Triturus vulgaris", "27": "eft", "28": "spotted salamander, Ambystoma maculatum", "29": "axolotl, mud puppy, Ambystoma mexicanum", "30": "bullfrog, Rana catesbeiana", "31": "tree frog, tree-frog", "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui", "33": "loggerhead, loggerhead turtle, Caretta caretta", "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea", "35": "mud turtle", "36": "terrapin", "37": "box turtle, box tortoise", "38": "banded gecko", "39": "common iguana, iguana, Iguana iguana", "40": "American chameleon, anole, Anolis carolinensis", "41": "whiptail, whiptail lizard", "42": "agama", "43": "frilled lizard, Chlamydosaurus kingi", "44": "alligator lizard", "45": "Gila monster, Heloderma suspectum", "46": "green lizard, Lacerta viridis", "47": "African chameleon, Chamaeleo chamaeleon", "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis", "49": "African crocodile, Nile crocodile, Crocodylus niloticus", "50": "American alligator, Alligator mississipiensis", "51": "triceratops", "52": "thunder snake, worm snake, Carphophis amoenus", "53": "ringneck snake, ring-necked snake, ring snake", "54": "hognose snake, puff adder, sand viper", "55": "green snake, grass snake", "56": "king snake, kingsnake", "57": "garter snake, grass snake", "58": "water snake", "59": "vine snake", "60": "night snake, Hypsiglena torquata", "61": "boa constrictor, Constrictor constrictor", "62": "rock python, rock snake, Python sebae", "63": "Indian cobra, Naja naja", "64": "green mamba", "65": "sea snake", "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus", "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus", "68": "sidewinder, horned rattlesnake, Crotalus cerastes", "69": "trilobite", "70": "harvestman, daddy longlegs, Phalangium opilio", "71": "scorpion", "72": "black and gold garden spider, Argiope aurantia", "73": "barn spider, Araneus cavaticus", "74": "garden spider, Aranea diademata", "75": "black widow, Latrodectus mactans", "76": "tarantula", "77": "wolf spider, hunting spider", "78": "tick", "79": "centipede", "80": "black grouse", "81": "ptarmigan", "82": "ruffed grouse, partridge, Bonasa umbellus", "83": "prairie chicken, prairie grouse, prairie fowl", "84": "peacock", "85": "quail", "86": "partridge", "87": "African grey, African gray, Psittacus erithacus", "88": "macaw", "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita", "90": "lorikeet", "91": "coucal", "92": "bee eater", "93": "hornbill", "94": "hummingbird", "95": "jacamar", "96": "toucan", "97": "drake", "98": "red-breasted merganser, Mergus serrator", "99": "goose", "100": "black swan, Cygnus atratus", "101": "tusker", "102": "echidna, spiny anteater, anteater", "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus", "104": "wallaby, brush kangaroo", "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus", "106": "wombat", "107": "jellyfish", "108": "sea anemone, anemone", "109": "brain coral", "110": "flatworm, platyhelminth", "111": "nematode, nematode worm, roundworm", "112": "conch", "113": "snail", "114": "slug", "115": "sea slug, nudibranch", "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore", "117": "chambered nautilus, pearly nautilus, nautilus", "118": "Dungeness crab, Cancer magister", "119": "rock crab, Cancer irroratus", "120": "fiddler crab", "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica", "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus", "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish", "124": "crayfish, crawfish, crawdad, crawdaddy", "125": "hermit crab", "126": "isopod", "127": "white stork, Ciconia ciconia", "128": "black stork, Ciconia nigra", "129": "spoonbill", "130": "flamingo", "131": "little blue heron, Egretta caerulea", "132": "American egret, great white heron, Egretta albus", "133": "bittern", "134": "crane", "135": "limpkin, Aramus pictus", "136": "European gallinule, Porphyrio porphyrio", "137": "American coot, marsh hen, mud hen, water hen, Fulica americana", "138": "bustard", "139": "ruddy turnstone, Arenaria interpres", "140": "red-backed sandpiper, dunlin, Erolia alpina", "141": "redshank, Tringa totanus", "142": "dowitcher", "143": "oystercatcher, oyster catcher", "144": "pelican", "145": "king penguin, Aptenodytes patagonica", "146": "albatross, mollymawk", "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus", "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca", "149": "dugong, Dugong dugon", "150": "sea lion", "151": "Chihuahua", "152": "Japanese spaniel", "153": "Maltese dog, Maltese terrier, Maltese", "154": "Pekinese, Pekingese, Peke", "155": "Shih-Tzu", "156": "Blenheim spaniel", "157": "papillon", "158": "toy terrier", "159": "Rhodesian ridgeback", "160": "Afghan hound, Afghan", "161": "basset, basset hound", "162": "beagle", "163": "bloodhound, sleuthhound", "164": "bluetick", "165": "black-and-tan coonhound", "166": "Walker hound, Walker foxhound", "167": "English foxhound", "168": "redbone", "169": "borzoi, Russian wolfhound", "170": "Irish wolfhound", "171": "Italian greyhound", "172": "whippet", "173": "Ibizan hound, Ibizan Podenco", "174": "Norwegian elkhound, elkhound", "175": "otterhound, otter hound", "176": "Saluki, gazelle hound", "177": "Scottish deerhound, deerhound", "178": "Weimaraner", "179": "Staffordshire bullterrier, Staffordshire bull terrier", "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier", "181": "Bedlington terrier", "182": "Border terrier", "183": "Kerry blue terrier", "184": "Irish terrier", "185": "Norfolk terrier", "186": "Norwich terrier", "187": "Yorkshire terrier", "188": "wire-haired fox terrier", "189": "Lakeland terrier", "190": "Sealyham terrier, Sealyham", "191": "Airedale, Airedale terrier", "192": "cairn, cairn terrier", "193": "Australian terrier", "194": "Dandie Dinmont, Dandie Dinmont terrier", "195": "Boston bull, Boston terrier", "196": "miniature schnauzer", "197": "giant schnauzer", "198": "standard schnauzer", "199": "Scotch terrier, Scottish terrier, Scottie", "200": "Tibetan terrier, chrysanthemum dog", "201": "silky terrier, Sydney silky", "202": "soft-coated wheaten terrier", "203": "West Highland white terrier", "204": "Lhasa, Lhasa apso", "205": "flat-coated retriever", "206": "curly-coated retriever", "207": "golden retriever", "208": "Labrador retriever", "209": "Chesapeake Bay retriever", "210": "German short-haired pointer", "211": "vizsla, Hungarian pointer", "212": "English setter", "213": "Irish setter, red setter", "214": "Gordon setter", "215": "Brittany spaniel", "216": "clumber, clumber spaniel", "217": "English springer, English springer spaniel", "218": "Welsh springer spaniel", "219": "cocker spaniel, English cocker spaniel, cocker", "220": "Sussex spaniel", "221": "Irish water spaniel", "222": "kuvasz", "223": "schipperke", "224": "groenendael", "225": "malinois", "226": "briard", "227": "kelpie", "228": "komondor", "229": "Old English sheepdog, bobtail", "230": "Shetland sheepdog, Shetland sheep dog, Shetland", "231": "collie", "232": "Border collie", "233": "Bouvier des Flandres, Bouviers des Flandres", "234": "Rottweiler", "235": "German shepherd, German shepherd dog, German police dog, alsatian", "236": "Doberman, Doberman pinscher", "237": "miniature pinscher", "238": "Greater Swiss Mountain dog", "239": "Bernese mountain dog", "240": "Appenzeller", "241": "EntleBucher", "242": "boxer", "243": "bull mastiff", "244": "Tibetan mastiff", "245": "French bulldog", "246": "Great Dane", "247": "Saint Bernard, St Bernard", "248": "Eskimo dog, husky", "249": "malamute, malemute, Alaskan malamute", "250": "Siberian husky", "251": "dalmatian, coach dog, carriage dog", "252": "affenpinscher, monkey pinscher, monkey dog", "253": "basenji", "254": "pug, pug-dog", "255": "Leonberg", "256": "Newfoundland, Newfoundland dog", "257": "Great Pyrenees", "258": "Samoyed, Samoyede", "259": "Pomeranian", "260": "chow, chow chow", "261": "keeshond", "262": "Brabancon griffon", "263": "Pembroke, Pembroke Welsh corgi", "264": "Cardigan, Cardigan Welsh corgi", "265": "toy poodle", "266": "miniature poodle", "267": "standard poodle", "268": "Mexican hairless", "269": "timber wolf, grey wolf, gray wolf, Canis lupus", "270": "white wolf, Arctic wolf, Canis lupus tundrarum", "271": "red wolf, maned wolf, Canis rufus, Canis niger", "272": "coyote, prairie wolf, brush wolf, Canis latrans", "273": "dingo, warrigal, warragal, Canis dingo", "274": "dhole, Cuon alpinus", "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus", "276": "hyena, hyaena", "277": "red fox, Vulpes vulpes", "278": "kit fox, Vulpes macrotis", "279": "Arctic fox, white fox, Alopex lagopus", "280": "grey fox, gray fox, Urocyon cinereoargenteus", "281": "tabby, tabby cat", "282": "tiger cat", "283": "Persian cat", "284": "Siamese cat, Siamese", "285": "Egyptian cat", "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor", "287": "lynx, catamount", "288": "leopard, Panthera pardus", "289": "snow leopard, ounce, Panthera uncia", "290": "jaguar, panther, Panthera onca, Felis onca", "291": "lion, king of beasts, Panthera leo", "292": "tiger, Panthera tigris", "293": "cheetah, chetah, Acinonyx jubatus", "294": "brown bear, bruin, Ursus arctos", "295": "American black bear, black bear, Ursus americanus, Euarctos americanus", "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus", "297": "sloth bear, Melursus ursinus, Ursus ursinus", "298": "mongoose", "299": "meerkat, mierkat", "300": "tiger beetle", "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle", "302": "ground beetle, carabid beetle", "303": "long-horned beetle, longicorn, longicorn beetle", "304": "leaf beetle, chrysomelid", "305": "dung beetle", "306": "rhinoceros beetle", "307": "weevil", "308": "fly", "309": "bee", "310": "ant, emmet, pismire", "311": "grasshopper, hopper", "312": "cricket", "313": "walking stick, walkingstick, stick insect", "314": "cockroach, roach", "315": "mantis, mantid", "316": "cicada, cicala", "317": "leafhopper", "318": "lacewing, lacewing fly", "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk", "320": "damselfly", "321": "admiral", "322": "ringlet, ringlet butterfly", "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus", "324": "cabbage butterfly", "325": "sulphur butterfly, sulfur butterfly", "326": "lycaenid, lycaenid butterfly", "327": "starfish, sea star", "328": "sea urchin", "329": "sea cucumber, holothurian", "330": "wood rabbit, cottontail, cottontail rabbit", "331": "hare", "332": "Angora, Angora rabbit", "333": "hamster", "334": "porcupine, hedgehog", "335": "fox squirrel, eastern fox squirrel, Sciurus niger", "336": "marmot", "337": "beaver", "338": "guinea pig, Cavia cobaya", "339": "sorrel", "340": "zebra", "341": "hog, pig, grunter, squealer, Sus scrofa", "342": "wild boar, boar, Sus scrofa", "343": "warthog", "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius", "345": "ox", "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis", "347": "bison", "348": "ram, tup", "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis", "350": "ibex, Capra ibex", "351": "hartebeest", "352": "impala, Aepyceros melampus", "353": "gazelle", "354": "Arabian camel, dromedary, Camelus dromedarius", "355": "llama", "356": "weasel", "357": "mink", "358": "polecat, fitch, foulmart, foumart, Mustela putorius", "359": "black-footed ferret, ferret, Mustela nigripes", "360": "otter", "361": "skunk, polecat, wood pussy", "362": "badger", "363": "armadillo", "364": "three-toed sloth, ai, Bradypus tridactylus", "365": "orangutan, orang, orangutang, Pongo pygmaeus", "366": "gorilla, Gorilla gorilla", "367": "chimpanzee, chimp, Pan troglodytes", "368": "gibbon, Hylobates lar", "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus", "370": "guenon, guenon monkey", "371": "patas, hussar monkey, Erythrocebus patas", "372": "baboon", "373": "macaque", "374": "langur", "375": "colobus, colobus monkey", "376": "proboscis monkey, Nasalis larvatus", "377": "marmoset", "378": "capuchin, ringtail, Cebus capucinus", "379": "howler monkey, howler", "380": "titi, titi monkey", "381": "spider monkey, Ateles geoffroyi", "382": "squirrel monkey, Saimiri sciureus", "383": "Madagascar cat, ring-tailed lemur, Lemur catta", "384": "indri, indris, Indri indri, Indri brevicaudatus", "385": "Indian elephant, Elephas maximus", "386": "African elephant, Loxodonta africana", "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens", "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca", "389": "barracouta, snoek", "390": "eel", "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch", "392": "rock beauty, Holocanthus tricolor", "393": "anemone fish", "394": "sturgeon", "395": "gar, garfish, garpike, billfish, Lepisosteus osseus", "396": "lionfish", "397": "puffer, pufferfish, blowfish, globefish", "398": "abacus", "399": "abaya", "400": "academic gown, academic robe, judge's robe", "401": "accordion, piano accordion, squeeze box", "402": "acoustic guitar", "403": "aircraft carrier, carrier, flattop, attack aircraft carrier", "404": "airliner", "405": "airship, dirigible", "406": "altar", "407": "ambulance", "408": "amphibian, amphibious vehicle", "409": "analog clock", "410": "apiary, bee house", "411": "apron", "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin", "413": "assault rifle, assault gun", "414": "backpack, back pack, knapsack, packsack, rucksack, haversack", "415": "bakery, bakeshop, bakehouse", "416": "balance beam, beam", "417": "balloon", "418": "ballpoint, ballpoint pen, ballpen, Biro", "419": "Band Aid", "420": "banjo", "421": "bannister, banister, balustrade, balusters, handrail", "422": "barbell", "423": "barber chair", "424": "barbershop", "425": "barn", "426": "barometer", "427": "barrel, cask", "428": "barrow, garden cart, lawn cart, wheelbarrow", "429": "baseball", "430": "basketball", "431": "bassinet", "432": "bassoon", "433": "bathing cap, swimming cap", "434": "bath towel", "435": "bathtub, bathing tub, bath, tub", "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon", "437": "beacon, lighthouse, beacon light, pharos", "438": "beaker", "439": "bearskin, busby, shako", "440": "beer bottle", "441": "beer glass", "442": "bell cote, bell cot", "443": "bib", "444": "bicycle-built-for-two, tandem bicycle, tandem", "445": "bikini, two-piece", "446": "binder, ring-binder", "447": "binoculars, field glasses, opera glasses", "448": "birdhouse", "449": "boathouse", "450": "bobsled, bobsleigh, bob", "451": "bolo tie, bolo, bola tie, bola", "452": "bonnet, poke bonnet", "453": "bookcase", "454": "bookshop, bookstore, bookstall", "455": "bottlecap", "456": "bow", "457": "bow tie, bow-tie, bowtie", "458": "brass, memorial tablet, plaque", "459": "brassiere, bra, bandeau", "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty", "461": "breastplate, aegis, egis", "462": "broom", "463": "bucket, pail", "464": "buckle", "465": "bulletproof vest", "466": "bullet train, bullet", "467": "butcher shop, meat market", "468": "cab, hack, taxi, taxicab", "469": "caldron, cauldron", "470": "candle, taper, wax light", "471": "cannon", "472": "canoe", "473": "can opener, tin opener", "474": "cardigan", "475": "car mirror", "476": "carousel, carrousel, merry-go-round, roundabout, whirligig", "477": "carpenter's kit, tool kit", "478": "carton", "479": "car wheel", "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM", "481": "cassette", "482": "cassette player", "483": "castle", "484": "catamaran", "485": "CD player", "486": "cello, violoncello", "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone", "488": "chain", "489": "chainlink fence", "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour", "491": "chain saw, chainsaw", "492": "chest", "493": "chiffonier, commode", "494": "chime, bell, gong", "495": "china cabinet, china closet", "496": "Christmas stocking", "497": "church, church building", "498": "cinema, movie theater, movie theatre, movie house, picture palace", "499": "cleaver, meat cleaver, chopper", "500": "cliff dwelling", "501": "cloak", "502": "clog, geta, patten, sabot", "503": "cocktail shaker", "504": "coffee mug", "505": "coffeepot", "506": "coil, spiral, volute, whorl, helix", "507": "combination lock", "508": "computer keyboard, keypad", "509": "confectionery, confectionary, candy store", "510": "container ship, containership, container vessel", "511": "convertible", "512": "corkscrew, bottle screw", "513": "cornet, horn, trumpet, trump", "514": "cowboy boot", "515": "cowboy hat, ten-gallon hat", "516": "cradle", "517": "crane2", "518": "crash helmet", "519": "crate", "520": "crib, cot", "521": "Crock Pot", "522": "croquet ball", "523": "crutch", "524": "cuirass", "525": "dam, dike, dyke", "526": "desk", "527": "desktop computer", "528": "dial telephone, dial phone", "529": "diaper, nappy, napkin", "530": "digital clock", "531": "digital watch", "532": "dining table, board", "533": "dishrag, dishcloth", "534": "dishwasher, dish washer, dishwashing machine", "535": "disk brake, disc brake", "536": "dock, dockage, docking facility", "537": "dogsled, dog sled, dog sleigh", "538": "dome", "539": "doormat, welcome mat", "540": "drilling platform, offshore rig", "541": "drum, membranophone, tympan", "542": "drumstick", "543": "dumbbell", "544": "Dutch oven", "545": "electric fan, blower", "546": "electric guitar", "547": "electric locomotive", "548": "entertainment center", "549": "envelope", "550": "espresso maker", "551": "face powder", "552": "feather boa, boa", "553": "file, file cabinet, filing cabinet", "554": "fireboat", "555": "fire engine, fire truck", "556": "fire screen, fireguard", "557": "flagpole, flagstaff", "558": "flute, transverse flute", "559": "folding chair", "560": "football helmet", "561": "forklift", "562": "fountain", "563": "fountain pen", "564": "four-poster", "565": "freight car", "566": "French horn, horn", "567": "frying pan, frypan, skillet", "568": "fur coat", "569": "garbage truck, dustcart", "570": "gasmask, respirator, gas helmet", "571": "gas pump, gasoline pump, petrol pump, island dispenser", "572": "goblet", "573": "go-kart", "574": "golf ball", "575": "golfcart, golf cart", "576": "gondola", "577": "gong, tam-tam", "578": "gown", "579": "grand piano, grand", "580": "greenhouse, nursery, glasshouse", "581": "grille, radiator grille", "582": "grocery store, grocery, food market, market", "583": "guillotine", "584": "hair slide", "585": "hair spray", "586": "half track", "587": "hammer", "588": "hamper", "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier", "590": "hand-held computer, hand-held microcomputer", "591": "handkerchief, hankie, hanky, hankey", "592": "hard disc, hard disk, fixed disk", "593": "harmonica, mouth organ, harp, mouth harp", "594": "harp", "595": "harvester, reaper", "596": "hatchet", "597": "holster", "598": "home theater, home theatre", "599": "honeycomb", "600": "hook, claw", "601": "hoopskirt, crinoline", "602": "horizontal bar, high bar", "603": "horse cart, horse-cart", "604": "hourglass", "605": "iPod", "606": "iron, smoothing iron", "607": "jack-o'-lantern", "608": "jean, blue jean, denim", "609": "jeep, landrover", "610": "jersey, T-shirt, tee shirt", "611": "jigsaw puzzle", "612": "jinrikisha, ricksha, rickshaw", "613": "joystick", "614": "kimono", "615": "knee pad", "616": "knot", "617": "lab coat, laboratory coat", "618": "ladle", "619": "lampshade, lamp shade", "620": "laptop, laptop computer", "621": "lawn mower, mower", "622": "lens cap, lens cover", "623": "letter opener, paper knife, paperknife", "624": "library", "625": "lifeboat", "626": "lighter, light, igniter, ignitor", "627": "limousine, limo", "628": "liner, ocean liner", "629": "lipstick, lip rouge", "630": "Loafer", "631": "lotion", "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system", "633": "loupe, jeweler's loupe", "634": "lumbermill, sawmill", "635": "magnetic compass", "636": "mailbag, postbag", "637": "mailbox, letter box", "638": "maillot", "639": "maillot, tank suit", "640": "manhole cover", "641": "maraca", "642": "marimba, xylophone", "643": "mask", "644": "matchstick", "645": "maypole", "646": "maze, labyrinth", "647": "measuring cup", "648": "medicine chest, medicine cabinet", "649": "megalith, megalithic structure", "650": "microphone, mike", "651": "microwave, microwave oven", "652": "military uniform", "653": "milk can", "654": "minibus", "655": "miniskirt, mini", "656": "minivan", "657": "missile", "658": "mitten", "659": "mixing bowl", "660": "mobile home, manufactured home", "661": "Model T", "662": "modem", "663": "monastery", "664": "monitor", "665": "moped", "666": "mortar", "667": "mortarboard", "668": "mosque", "669": "mosquito net", "670": "motor scooter, scooter", "671": "mountain bike, all-terrain bike, off-roader", "672": "mountain tent", "673": "mouse, computer mouse", "674": "mousetrap", "675": "moving van", "676": "muzzle", "677": "nail", "678": "neck brace", "679": "necklace", "680": "nipple", "681": "notebook, notebook computer", "682": "obelisk", "683": "oboe, hautboy, hautbois", "684": "ocarina, sweet potato", "685": "odometer, hodometer, mileometer, milometer", "686": "oil filter", "687": "organ, pipe organ", "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO", "689": "overskirt", "690": "oxcart", "691": "oxygen mask", "692": "packet", "693": "paddle, boat paddle", "694": "paddlewheel, paddle wheel", "695": "padlock", "696": "paintbrush", "697": "pajama, pyjama, pj's, jammies", "698": "palace", "699": "panpipe, pandean pipe, syrinx", "700": "paper towel", "701": "parachute, chute", "702": "parallel bars, bars", "703": "park bench", "704": "parking meter", "705": "passenger car, coach, carriage", "706": "patio, terrace", "707": "pay-phone, pay-station", "708": "pedestal, plinth, footstall", "709": "pencil box, pencil case", "710": "pencil sharpener", "711": "perfume, essence", "712": "Petri dish", "713": "photocopier", "714": "pick, plectrum, plectron", "715": "pickelhaube", "716": "picket fence, paling", "717": "pickup, pickup truck", "718": "pier", "719": "piggy bank, penny bank", "720": "pill bottle", "721": "pillow", "722": "ping-pong ball", "723": "pinwheel", "724": "pirate, pirate ship", "725": "pitcher, ewer", "726": "plane, carpenter's plane, woodworking plane", "727": "planetarium", "728": "plastic bag", "729": "plate rack", "730": "plow, plough", "731": "plunger, plumber's helper", "732": "Polaroid camera, Polaroid Land camera", "733": "pole", "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria", "735": "poncho", "736": "pool table, billiard table, snooker table", "737": "pop bottle, soda bottle", "738": "pot, flowerpot", "739": "potter's wheel", "740": "power drill", "741": "prayer rug, prayer mat", "742": "printer", "743": "prison, prison house", "744": "projectile, missile", "745": "projector", "746": "puck, hockey puck", "747": "punching bag, punch bag, punching ball, punchball", "748": "purse", "749": "quill, quill pen", "750": "quilt, comforter, comfort, puff", "751": "racer, race car, racing car", "752": "racket, racquet", "753": "radiator", "754": "radio, wireless", "755": "radio telescope, radio reflector", "756": "rain barrel", "757": "recreational vehicle, RV, R.V.", "758": "reel", "759": "reflex camera", "760": "refrigerator, icebox", "761": "remote control, remote", "762": "restaurant, eating house, eating place, eatery", "763": "revolver, six-gun, six-shooter", "764": "rifle", "765": "rocking chair, rocker", "766": "rotisserie", "767": "rubber eraser, rubber, pencil eraser", "768": "rugby ball", "769": "rule, ruler", "770": "running shoe", "771": "safe", "772": "safety pin", "773": "saltshaker, salt shaker", "774": "sandal", "775": "sarong", "776": "sax, saxophone", "777": "scabbard", "778": "scale, weighing machine", "779": "school bus", "780": "schooner", "781": "scoreboard", "782": "screen, CRT screen", "783": "screw", "784": "screwdriver", "785": "seat belt, seatbelt", "786": "sewing machine", "787": "shield, buckler", "788": "shoe shop, shoe-shop, shoe store", "789": "shoji", "790": "shopping basket", "791": "shopping cart", "792": "shovel", "793": "shower cap", "794": "shower curtain", "795": "ski", "796": "ski mask", "797": "sleeping bag", "798": "slide rule, slipstick", "799": "sliding door", "800": "slot, one-armed bandit", "801": "snorkel", "802": "snowmobile", "803": "snowplow, snowplough", "804": "soap dispenser", "805": "soccer ball", "806": "sock", "807": "solar dish, solar collector, solar furnace", "808": "sombrero", "809": "soup bowl", "810": "space bar", "811": "space heater", "812": "space shuttle", "813": "spatula", "814": "speedboat", "815": "spider web, spider's web", "816": "spindle", "817": "sports car, sport car", "818": "spotlight, spot", "819": "stage", "820": "steam locomotive", "821": "steel arch bridge", "822": "steel drum", "823": "stethoscope", "824": "stole", "825": "stone wall", "826": "stopwatch, stop watch", "827": "stove", "828": "strainer", "829": "streetcar, tram, tramcar, trolley, trolley car", "830": "stretcher", "831": "studio couch, day bed", "832": "stupa, tope", "833": "submarine, pigboat, sub, U-boat", "834": "suit, suit of clothes", "835": "sundial", "836": "sunglass", "837": "sunglasses, dark glasses, shades", "838": "sunscreen, sunblock, sun blocker", "839": "suspension bridge", "840": "swab, swob, mop", "841": "sweatshirt", "842": "swimming trunks, bathing trunks", "843": "swing", "844": "switch, electric switch, electrical switch", "845": "syringe", "846": "table lamp", "847": "tank, army tank, armored combat vehicle, armoured combat vehicle", "848": "tape player", "849": "teapot", "850": "teddy, teddy bear", "851": "television, television system", "852": "tennis ball", "853": "thatch, thatched roof", "854": "theater curtain, theatre curtain", "855": "thimble", "856": "thresher, thrasher, threshing machine", "857": "throne", "858": "tile roof", "859": "toaster", "860": "tobacco shop, tobacconist shop, tobacconist", "861": "toilet seat", "862": "torch", "863": "totem pole", "864": "tow truck, tow car, wrecker", "865": "toyshop", "866": "tractor", "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi", "868": "tray", "869": "trench coat", "870": "tricycle, trike, velocipede", "871": "trimaran", "872": "tripod", "873": "triumphal arch", "874": "trolleybus, trolley coach, trackless trolley", "875": "trombone", "876": "tub, vat", "877": "turnstile", "878": "typewriter keyboard", "879": "umbrella", "880": "unicycle, monocycle", "881": "upright, upright piano", "882": "vacuum, vacuum cleaner", "883": "vase", "884": "vault", "885": "velvet", "886": "vending machine", "887": "vestment", "888": "viaduct", "889": "violin, fiddle", "890": "volleyball", "891": "waffle iron", "892": "wall clock", "893": "wallet, billfold, notecase, pocketbook", "894": "wardrobe, closet, press", "895": "warplane, military plane", "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin", "897": "washer, automatic washer, washing machine", "898": "water bottle", "899": "water jug", "900": "water tower", "901": "whiskey jug", "902": "whistle", "903": "wig", "904": "window screen", "905": "window shade", "906": "Windsor tie", "907": "wine bottle", "908": "wing", "909": "wok", "910": "wooden spoon", "911": "wool, woolen, woollen", "912": "worm fence, snake fence, snake-rail fence, Virginia fence", "913": "wreck", "914": "yawl", "915": "yurt", "916": "web site, website, internet site, site", "917": "comic book", "918": "crossword puzzle, crossword", "919": "street sign", "920": "traffic light, traffic signal, stoplight", "921": "book jacket, dust cover, dust jacket, dust wrapper", "922": "menu", "923": "plate", "924": "guacamole", "925": "consomme", "926": "hot pot, hotpot", "927": "trifle", "928": "ice cream, icecream", "929": "ice lolly, lolly, lollipop, popsicle", "930": "French loaf", "931": "bagel, beigel", "932": "pretzel", "933": "cheeseburger", "934": "hotdog, hot dog, red hot", "935": "mashed potato", "936": "head cabbage", "937": "broccoli", "938": "cauliflower", "939": "zucchini, courgette", "940": "spaghetti squash", "941": "acorn squash", "942": "butternut squash", "943": "cucumber, cuke", "944": "artichoke, globe artichoke", "945": "bell pepper", "946": "cardoon", "947": "mushroom", "948": "Granny Smith", "949": "strawberry", "950": "orange", "951": "lemon", "952": "fig", "953": "pineapple, ananas", "954": "banana", "955": "jackfruit, jak, jack", "956": "custard apple", "957": "pomegranate", "958": "hay", "959": "carbonara", "960": "chocolate sauce, chocolate syrup", "961": "dough", "962": "meat loaf, meatloaf", "963": "pizza, pizza pie", "964": "potpie", "965": "burrito", "966": "red wine", "967": "espresso", "968": "cup", "969": "eggnog", "970": "alp", "971": "bubble", "972": "cliff, drop, drop-off", "973": "coral reef", "974": "geyser", "975": "lakeside, lakeshore", "976": "promontory, headland, head, foreland", "977": "sandbar, sand bar", "978": "seashore, coast, seacoast, sea-coast", "979": "valley, vale", "980": "volcano", "981": "ballplayer, baseball player", "982": "groom, bridegroom", "983": "scuba diver", "984": "rapeseed", "985": "daisy", "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum", "987": "corn", "988": "acorn", "989": "hip, rose hip, rosehip", "990": "buckeye, horse chestnut, conker", "991": "coral fungus", "992": "agaric", "993": "gyromitra", "994": "stinkhorn, carrion fungus", "995": "earthstar", "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa", "997": "bolete", "998": "ear, spike, capitulum", "999": "toilet tissue, toilet paper, bathroom tissue"}}}}]
{}
MohdShawezKhan/guanaco-llama2-1k
default
0
36
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-04-12T14:16:06
2024-04-12T14:20:02
[{"name": "text", "dtype": "string"}]
{}
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_066fc4a6-f1f9-4866-90ba-382cc025409e
default
0
38
["region:us"]
null
null
2024-10-31T15:33:27
2024-10-31T15:33:27
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "positive", "1": "negative"}}}}]
{}
davanstrien/cosmochat
default
11
41
["language:en", "license:cc0-1.0", "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "library:distilabel", "arxiv:2306.11644", "region:us", "synthetic", "distilabel", "rlaif"]
["en"]
"cc0-1.0"
2024-05-07T12:26:40
2024-05-10T10:25:50
[{"name": "cosmopedia_text", "dtype": "string"}, {"name": "audience", "dtype": "string"}, {"name": "dialogue", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "final_question_prompt", "dtype": "string"}]
{}
yangyz1230/enhancers
default
0
30
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-04-08T14:25:58
2024-04-15T11:26:30
[{"name": "name", "dtype": "string"}, {"name": "sequence", "dtype": "string"}, {"name": "chrom", "dtype": "string"}, {"name": "start", "dtype": "int64"}, {"name": "end", "dtype": "int64"}, {"name": "strand", "dtype": "string"}, {"name": "label", "dtype": "int64"}]
{}
heyitsys/my-distiset-1e19c7499
default
0
54
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "library:distilabel", "region:us", "synthetic", "distilabel", "rlaif", "datacraft"]
null
null
2024-12-21T08:38:19
2024-12-21T09:19:24
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "legitimate", "1": "suspicious"}}}}]
{}
dmrau/cqudupstack-gis
default
0
33
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-10-09T12:38:25
2023-10-09T12:38:30
[{"name": "_id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}]
{}
mnm373/SFT_dataset_with_hallucination_before_formatted
default
0
39
["size_categories:1M<n<10M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-06-12T11:36:46
2024-06-12T16:08:12
[{"name": "index", "dtype": "int64"}, {"name": "instruction", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}]
{}
Asap7772/llama_base_prm800k_mc_parallel_gsm8k
default
0
37
["size_categories:100K<n<1M", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-22T10:07:15
2024-11-22T10:07:35
[{"name": "trajectory", "dtype": "int64"}, {"name": "completion", "dtype": "int64"}, {"name": "input", "dtype": "string"}, {"name": "solution", "dtype": "string"}, {"name": "is_correct", "dtype": "bool"}, {"name": "solution_steps", "sequence": "string"}, {"name": "rtg", "sequence": "float64"}, {"name": "undiscounted_rtg", "sequence": "float64"}, {"name": "target_answer", "dtype": "string"}]
{}
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_d912814c-28d7-4a9c-b31e-4c23854887c4
default
0
33
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-23T09:56:15
2024-09-23T09:56:16
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "positive", "1": "negative"}}}}]
{}
rkumari/corrosion_segment
default
1
32
["size_categories:n<1K", "format:parquet", "modality:image", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-06-08T22:38:13
2023-06-08T23:12:03
[{"name": "image", "dtype": "image"}, {"name": "label", "dtype": "image"}]
{}
vmathur87/llm-support
default
0
35
["size_categories:n<1K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-02-19T10:23:37
2024-02-19T10:23:40
[{"name": "input_ids", "sequence": "int32"}]
{}
HuggingFaceTB/python-edu-annotations
default
2
58
["size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-31T10:13:43
2024-07-31T10:20:23
[{"name": "max_stars_repo_path", "dtype": "string"}, {"name": "max_stars_repo_name", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "score", "dtype": "int64"}]
{}
Data-Agora/magpie_code_claude3.5_sonnet_10000
default
4
42
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-10-11T16:47:50
2024-10-11T16:47:51
[{"name": "config", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "response", "dtype": "string"}]
{}
adamjweintraut/eli5_precomputed_top_slice
default
0
32
["size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-11-29T01:23:33
2023-12-06T01:34:22
[{"name": "index", "dtype": "int64"}, {"name": "q_id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "best_answer", "dtype": "string"}, {"name": "all_answers", "sequence": "string"}, {"name": "num_answers", "dtype": "int64"}, {"name": "top_answers", "sequence": "string"}, {"name": "num_top_answers", "dtype": "int64"}, {"name": "context", "dtype": "string"}, {"name": "orig", "dtype": "string"}, {"name": "target", "dtype": "string"}]
{}
Henly1/customhkcoode2
default
0
31
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-23T14:07:13
2024-03-23T14:08:43
[{"name": "text", "dtype": "string"}]
{}
SidhaarthMurali/synthetic_math_mri_mini
default
0
52
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-17T14:57:39
2024-12-19T06:15:31
[{"name": "response", "dtype": "string"}, {"name": "conversations", "sequence": "string"}, {"name": "intent", "dtype": "string"}, {"name": "knowledge", "dtype": "string"}, {"name": "difficulty", "dtype": "string"}, {"name": "task_category", "dtype": "string"}, {"name": "input_quality", "dtype": "string"}, {"name": " , ", "sequence": "string"}, {"name": "function calculateTriangleArea(a, b, c) {\n", "dtype": "string"}, {"name": " const s = (a + b + c) / 2;\n", "dtype": "string"}, {"name": " const area = Math.sqrt(s * (s - a) * (s - b) * (s - c));\n", "dtype": "string"}, {"name": "}\n", "dtype": "string"}, {"name": "// Understanding geometry is essential for this task as it involves calculating the area of a triangle, which is a fundamental geometric concept. The calculation is based on the lengths of the triangle's sides, requiring knowledge of both triangle properties and Heron's formula to derive the area accurately. \n", "dtype": "string"}]
{}
ferrazzipietro/unLS_Llama-3.1-8B_diann-sentences-spanish_NoQuant_16_16_0.01_64_BestF1
default
0
39
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-11T14:26:46
2024-12-11T14:26:49
[{"name": "sentence", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "keywords", "dtype": "string"}, {"name": "annotated_text", "dtype": "string"}, {"name": "raw_text", "dtype": "string"}, {"name": "sentence_annotated", "dtype": "string"}, {"name": "entities", "list": [{"name": "offsets", "sequence": "int64"}, {"name": "text", "dtype": "string"}, {"name": "type", "dtype": "string"}]}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": "int64"}, {"name": "ground_truth_word_level", "sequence": "string"}, {"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}, {"name": "labels", "sequence": "int64"}, {"name": "predictions", "sequence": "string"}, {"name": "ground_truth_labels", "sequence": "string"}]
{}
lamhieu/slwiki_dialogue_vi
default
0
49
["task_categories:text-classification", "task_categories:text2text-generation", "language:vi", "license:mit", "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
["vi"]
"mit"
2024-01-16T14:04:24
2024-05-17T10:35:02
[{"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
pbelcak/pmc-train-4200000-to-4300000-GemmaTokens
default
0
33
["size_categories:100K<n<1M", "format:parquet", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-05-08T13:45:57
2024-05-08T13:48:50
[{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}]
{}
jainabh/LLama-2-FT
default
0
31
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-08-07T02:45:38
2023-08-07T02:47:38
[{"name": "Text", "dtype": "string"}]
{}
antonkirk/fz_gpt4o_mini
default
0
31
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-18T21:28:53
2024-09-06T14:40:00
[{"name": "queries", "sequence": "string"}, {"name": "chunk", "dtype": "string"}]
{}
Zeal-Nir/quechua-audioset-4GB
default
1
37
["size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-21T18:37:11
2024-03-21T19:56:51
[{"name": "audios", "dtype": "audio"}, {"name": "texts", "dtype": "string"}]
{}
FlippyDora/REFUEL
default
0
38
["size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-04T01:09:26
2024-11-04T01:09:27
[{"name": "trajectory", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "sampled_len_from_5", "dtype": "int64"}, {"name": "sampled_h_from_sampled_len", "dtype": "int64"}, {"name": "trajectory_sampled_h_from_sampled_len", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
jlbaker361/actstu-ghibli
default
0
29
["size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-02-27T19:08:06
2024-02-27T19:10:56
[{"name": "image", "dtype": "image"}, {"name": "prompt", "dtype": "string"}, {"name": "seed", "dtype": "int64"}, {"name": "steps", "dtype": "int64"}]
{}
alvarobartt/openhermes-preferences-metamath
default
4
45
["task_categories:text-generation", "annotations_creators:Argilla", "annotations_creators:HuggingFaceH4", "source_datasets:argilla/OpenHermesPreferences", "language:en", "license:other", "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "dpo", "synthetic", "metamath"]
["en"]
"other"
2024-02-27T08:25:32
2024-02-29T09:14:42
[{"name": "chosen", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "rejected", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
GilbertKrantz/rsna-lumbar-spine-dataset
default
0
48
["size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-26T16:05:18
2024-12-09T13:38:35
[{"name": "image", "dtype": "image"}, {"name": "label", "dtype": "int64"}, {"name": "metadata", "dtype": "string"}, {"name": "condition", "dtype": "string"}]
{}
juny76/dataset-train
default
0
32
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-27T04:44:37
2024-03-27T04:47:57
[{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "data_source", "dtype": "string"}]
{}
tattrongvu/chameleon_1m_unlabeled
default
0
36
["size_categories:1M<n<10M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-30T15:53:55
2024-12-30T16:06:30
[{"name": "image_tokens", "dtype": "string"}, {"name": "caption", "dtype": "string"}]
{}
datacomp/imagenet-1k-random-100.0-frac-1over16
default
0
70
["size_categories:100K<n<1M", "format:parquet", "modality:image", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-06T13:53:01
2025-01-18T00:13:54
[{"name": "image", "dtype": "image"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "tench, Tinca tinca", "1": "goldfish, Carassius auratus", "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias", "3": "tiger shark, Galeocerdo cuvieri", "4": "hammerhead, hammerhead shark", "5": "electric ray, crampfish, numbfish, torpedo", "6": "stingray", "7": "cock", "8": "hen", "9": "ostrich, Struthio camelus", "10": "brambling, Fringilla montifringilla", "11": "goldfinch, Carduelis carduelis", "12": "house finch, linnet, Carpodacus mexicanus", "13": "junco, snowbird", "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea", "15": "robin, American robin, Turdus migratorius", "16": "bulbul", "17": "jay", "18": "magpie", "19": "chickadee", "20": "water ouzel, dipper", "21": "kite", "22": "bald eagle, American eagle, Haliaeetus leucocephalus", "23": "vulture", "24": "great grey owl, great gray owl, Strix nebulosa", "25": "European fire salamander, Salamandra salamandra", "26": "common newt, Triturus vulgaris", "27": "eft", "28": "spotted salamander, Ambystoma maculatum", "29": "axolotl, mud puppy, Ambystoma mexicanum", "30": "bullfrog, Rana catesbeiana", "31": "tree frog, tree-frog", "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui", "33": "loggerhead, loggerhead turtle, Caretta caretta", "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea", "35": "mud turtle", "36": "terrapin", "37": "box turtle, box tortoise", "38": "banded gecko", "39": "common iguana, iguana, Iguana iguana", "40": "American chameleon, anole, Anolis carolinensis", "41": "whiptail, whiptail lizard", "42": "agama", "43": "frilled lizard, Chlamydosaurus kingi", "44": "alligator lizard", "45": "Gila monster, Heloderma suspectum", "46": "green lizard, Lacerta viridis", "47": "African chameleon, Chamaeleo chamaeleon", "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis", "49": "African crocodile, Nile crocodile, Crocodylus niloticus", "50": "American alligator, Alligator mississipiensis", "51": "triceratops", "52": "thunder snake, worm snake, Carphophis amoenus", "53": "ringneck snake, ring-necked snake, ring snake", "54": "hognose snake, puff adder, sand viper", "55": "green snake, grass snake", "56": "king snake, kingsnake", "57": "garter snake, grass snake", "58": "water snake", "59": "vine snake", "60": "night snake, Hypsiglena torquata", "61": "boa constrictor, Constrictor constrictor", "62": "rock python, rock snake, Python sebae", "63": "Indian cobra, Naja naja", "64": "green mamba", "65": "sea snake", "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus", "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus", "68": "sidewinder, horned rattlesnake, Crotalus cerastes", "69": "trilobite", "70": "harvestman, daddy longlegs, Phalangium opilio", "71": "scorpion", "72": "black and gold garden spider, Argiope aurantia", "73": "barn spider, Araneus cavaticus", "74": "garden spider, Aranea diademata", "75": "black widow, Latrodectus mactans", "76": "tarantula", "77": "wolf spider, hunting spider", "78": "tick", "79": "centipede", "80": "black grouse", "81": "ptarmigan", "82": "ruffed grouse, partridge, Bonasa umbellus", "83": "prairie chicken, prairie grouse, prairie fowl", "84": "peacock", "85": "quail", "86": "partridge", "87": "African grey, African gray, Psittacus erithacus", "88": "macaw", "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita", "90": "lorikeet", "91": "coucal", "92": "bee eater", "93": "hornbill", "94": "hummingbird", "95": "jacamar", "96": "toucan", "97": "drake", "98": "red-breasted merganser, Mergus serrator", "99": "goose", "100": "black swan, Cygnus atratus", "101": "tusker", "102": "echidna, spiny anteater, anteater", "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus", "104": "wallaby, brush kangaroo", "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus", "106": "wombat", "107": "jellyfish", "108": "sea anemone, anemone", "109": "brain coral", "110": "flatworm, platyhelminth", "111": "nematode, nematode worm, roundworm", "112": "conch", "113": "snail", "114": "slug", "115": "sea slug, nudibranch", "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore", "117": "chambered nautilus, pearly nautilus, nautilus", "118": "Dungeness crab, Cancer magister", "119": "rock crab, Cancer irroratus", "120": "fiddler crab", "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica", "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus", "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish", "124": "crayfish, crawfish, crawdad, crawdaddy", "125": "hermit crab", "126": "isopod", "127": "white stork, Ciconia ciconia", "128": "black stork, Ciconia nigra", "129": "spoonbill", "130": "flamingo", "131": "little blue heron, Egretta caerulea", "132": "American egret, great white heron, Egretta albus", "133": "bittern", "134": "crane", "135": "limpkin, Aramus pictus", "136": "European gallinule, Porphyrio porphyrio", "137": "American coot, marsh hen, mud hen, water hen, Fulica americana", "138": "bustard", "139": "ruddy turnstone, Arenaria interpres", "140": "red-backed sandpiper, dunlin, Erolia alpina", "141": "redshank, Tringa totanus", "142": "dowitcher", "143": "oystercatcher, oyster catcher", "144": "pelican", "145": "king penguin, Aptenodytes patagonica", "146": "albatross, mollymawk", "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus", "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca", "149": "dugong, Dugong dugon", "150": "sea lion", "151": "Chihuahua", "152": "Japanese spaniel", "153": "Maltese dog, Maltese terrier, Maltese", "154": "Pekinese, Pekingese, Peke", "155": "Shih-Tzu", "156": "Blenheim spaniel", "157": "papillon", "158": "toy terrier", "159": "Rhodesian ridgeback", "160": "Afghan hound, Afghan", "161": "basset, basset hound", "162": "beagle", "163": "bloodhound, sleuthhound", "164": "bluetick", "165": "black-and-tan coonhound", "166": "Walker hound, Walker foxhound", "167": "English foxhound", "168": "redbone", "169": "borzoi, Russian wolfhound", "170": "Irish wolfhound", "171": "Italian greyhound", "172": "whippet", "173": "Ibizan hound, Ibizan Podenco", "174": "Norwegian elkhound, elkhound", "175": "otterhound, otter hound", "176": "Saluki, gazelle hound", "177": "Scottish deerhound, deerhound", "178": "Weimaraner", "179": "Staffordshire bullterrier, Staffordshire bull terrier", "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier", "181": "Bedlington terrier", "182": "Border terrier", "183": "Kerry blue terrier", "184": "Irish terrier", "185": "Norfolk terrier", "186": "Norwich terrier", "187": "Yorkshire terrier", "188": "wire-haired fox terrier", "189": "Lakeland terrier", "190": "Sealyham terrier, Sealyham", "191": "Airedale, Airedale terrier", "192": "cairn, cairn terrier", "193": "Australian terrier", "194": "Dandie Dinmont, Dandie Dinmont terrier", "195": "Boston bull, Boston terrier", "196": "miniature schnauzer", "197": "giant schnauzer", "198": "standard schnauzer", "199": "Scotch terrier, Scottish terrier, Scottie", "200": "Tibetan terrier, chrysanthemum dog", "201": "silky terrier, Sydney silky", "202": "soft-coated wheaten terrier", "203": "West Highland white terrier", "204": "Lhasa, Lhasa apso", "205": "flat-coated retriever", "206": "curly-coated retriever", "207": "golden retriever", "208": "Labrador retriever", "209": "Chesapeake Bay retriever", "210": "German short-haired pointer", "211": "vizsla, Hungarian pointer", "212": "English setter", "213": "Irish setter, red setter", "214": "Gordon setter", "215": "Brittany spaniel", "216": "clumber, clumber spaniel", "217": "English springer, English springer spaniel", "218": "Welsh springer spaniel", "219": "cocker spaniel, English cocker spaniel, cocker", "220": "Sussex spaniel", "221": "Irish water spaniel", "222": "kuvasz", "223": "schipperke", "224": "groenendael", "225": "malinois", "226": "briard", "227": "kelpie", "228": "komondor", "229": "Old English sheepdog, bobtail", "230": "Shetland sheepdog, Shetland sheep dog, Shetland", "231": "collie", "232": "Border collie", "233": "Bouvier des Flandres, Bouviers des Flandres", "234": "Rottweiler", "235": "German shepherd, German shepherd dog, German police dog, alsatian", "236": "Doberman, Doberman pinscher", "237": "miniature pinscher", "238": "Greater Swiss Mountain dog", "239": "Bernese mountain dog", "240": "Appenzeller", "241": "EntleBucher", "242": "boxer", "243": "bull mastiff", "244": "Tibetan mastiff", "245": "French bulldog", "246": "Great Dane", "247": "Saint Bernard, St Bernard", "248": "Eskimo dog, husky", "249": "malamute, malemute, Alaskan malamute", "250": "Siberian husky", "251": "dalmatian, coach dog, carriage dog", "252": "affenpinscher, monkey pinscher, monkey dog", "253": "basenji", "254": "pug, pug-dog", "255": "Leonberg", "256": "Newfoundland, Newfoundland dog", "257": "Great Pyrenees", "258": "Samoyed, Samoyede", "259": "Pomeranian", "260": "chow, chow chow", "261": "keeshond", "262": "Brabancon griffon", "263": "Pembroke, Pembroke Welsh corgi", "264": "Cardigan, Cardigan Welsh corgi", "265": "toy poodle", "266": "miniature poodle", "267": "standard poodle", "268": "Mexican hairless", "269": "timber wolf, grey wolf, gray wolf, Canis lupus", "270": "white wolf, Arctic wolf, Canis lupus tundrarum", "271": "red wolf, maned wolf, Canis rufus, Canis niger", "272": "coyote, prairie wolf, brush wolf, Canis latrans", "273": "dingo, warrigal, warragal, Canis dingo", "274": "dhole, Cuon alpinus", "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus", "276": "hyena, hyaena", "277": "red fox, Vulpes vulpes", "278": "kit fox, Vulpes macrotis", "279": "Arctic fox, white fox, Alopex lagopus", "280": "grey fox, gray fox, Urocyon cinereoargenteus", "281": "tabby, tabby cat", "282": "tiger cat", "283": "Persian cat", "284": "Siamese cat, Siamese", "285": "Egyptian cat", "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor", "287": "lynx, catamount", "288": "leopard, Panthera pardus", "289": "snow leopard, ounce, Panthera uncia", "290": "jaguar, panther, Panthera onca, Felis onca", "291": "lion, king of beasts, Panthera leo", "292": "tiger, Panthera tigris", "293": "cheetah, chetah, Acinonyx jubatus", "294": "brown bear, bruin, Ursus arctos", "295": "American black bear, black bear, Ursus americanus, Euarctos americanus", "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus", "297": "sloth bear, Melursus ursinus, Ursus ursinus", "298": "mongoose", "299": "meerkat, mierkat", "300": "tiger beetle", "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle", "302": "ground beetle, carabid beetle", "303": "long-horned beetle, longicorn, longicorn beetle", "304": "leaf beetle, chrysomelid", "305": "dung beetle", "306": "rhinoceros beetle", "307": "weevil", "308": "fly", "309": "bee", "310": "ant, emmet, pismire", "311": "grasshopper, hopper", "312": "cricket", "313": "walking stick, walkingstick, stick insect", "314": "cockroach, roach", "315": "mantis, mantid", "316": "cicada, cicala", "317": "leafhopper", "318": "lacewing, lacewing fly", "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk", "320": "damselfly", "321": "admiral", "322": "ringlet, ringlet butterfly", "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus", "324": "cabbage butterfly", "325": "sulphur butterfly, sulfur butterfly", "326": "lycaenid, lycaenid butterfly", "327": "starfish, sea star", "328": "sea urchin", "329": "sea cucumber, holothurian", "330": "wood rabbit, cottontail, cottontail rabbit", "331": "hare", "332": "Angora, Angora rabbit", "333": "hamster", "334": "porcupine, hedgehog", "335": "fox squirrel, eastern fox squirrel, Sciurus niger", "336": "marmot", "337": "beaver", "338": "guinea pig, Cavia cobaya", "339": "sorrel", "340": "zebra", "341": "hog, pig, grunter, squealer, Sus scrofa", "342": "wild boar, boar, Sus scrofa", "343": "warthog", "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius", "345": "ox", "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis", "347": "bison", "348": "ram, tup", "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis", "350": "ibex, Capra ibex", "351": "hartebeest", "352": "impala, Aepyceros melampus", "353": "gazelle", "354": "Arabian camel, dromedary, Camelus dromedarius", "355": "llama", "356": "weasel", "357": "mink", "358": "polecat, fitch, foulmart, foumart, Mustela putorius", "359": "black-footed ferret, ferret, Mustela nigripes", "360": "otter", "361": "skunk, polecat, wood pussy", "362": "badger", "363": "armadillo", "364": "three-toed sloth, ai, Bradypus tridactylus", "365": "orangutan, orang, orangutang, Pongo pygmaeus", "366": "gorilla, Gorilla gorilla", "367": "chimpanzee, chimp, Pan troglodytes", "368": "gibbon, Hylobates lar", "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus", "370": "guenon, guenon monkey", "371": "patas, hussar monkey, Erythrocebus patas", "372": "baboon", "373": "macaque", "374": "langur", "375": "colobus, colobus monkey", "376": "proboscis monkey, Nasalis larvatus", "377": "marmoset", "378": "capuchin, ringtail, Cebus capucinus", "379": "howler monkey, howler", "380": "titi, titi monkey", "381": "spider monkey, Ateles geoffroyi", "382": "squirrel monkey, Saimiri sciureus", "383": "Madagascar cat, ring-tailed lemur, Lemur catta", "384": "indri, indris, Indri indri, Indri brevicaudatus", "385": "Indian elephant, Elephas maximus", "386": "African elephant, Loxodonta africana", "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens", "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca", "389": "barracouta, snoek", "390": "eel", "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch", "392": "rock beauty, Holocanthus tricolor", "393": "anemone fish", "394": "sturgeon", "395": "gar, garfish, garpike, billfish, Lepisosteus osseus", "396": "lionfish", "397": "puffer, pufferfish, blowfish, globefish", "398": "abacus", "399": "abaya", "400": "academic gown, academic robe, judge's robe", "401": "accordion, piano accordion, squeeze box", "402": "acoustic guitar", "403": "aircraft carrier, carrier, flattop, attack aircraft carrier", "404": "airliner", "405": "airship, dirigible", "406": "altar", "407": "ambulance", "408": "amphibian, amphibious vehicle", "409": "analog clock", "410": "apiary, bee house", "411": "apron", "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin", "413": "assault rifle, assault gun", "414": "backpack, back pack, knapsack, packsack, rucksack, haversack", "415": "bakery, bakeshop, bakehouse", "416": "balance beam, beam", "417": "balloon", "418": "ballpoint, ballpoint pen, ballpen, Biro", "419": "Band Aid", "420": "banjo", "421": "bannister, banister, balustrade, balusters, handrail", "422": "barbell", "423": "barber chair", "424": "barbershop", "425": "barn", "426": "barometer", "427": "barrel, cask", "428": "barrow, garden cart, lawn cart, wheelbarrow", "429": "baseball", "430": "basketball", "431": "bassinet", "432": "bassoon", "433": "bathing cap, swimming cap", "434": "bath towel", "435": "bathtub, bathing tub, bath, tub", "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon", "437": "beacon, lighthouse, beacon light, pharos", "438": "beaker", "439": "bearskin, busby, shako", "440": "beer bottle", "441": "beer glass", "442": "bell cote, bell cot", "443": "bib", "444": "bicycle-built-for-two, tandem bicycle, tandem", "445": "bikini, two-piece", "446": "binder, ring-binder", "447": "binoculars, field glasses, opera glasses", "448": "birdhouse", "449": "boathouse", "450": "bobsled, bobsleigh, bob", "451": "bolo tie, bolo, bola tie, bola", "452": "bonnet, poke bonnet", "453": "bookcase", "454": "bookshop, bookstore, bookstall", "455": "bottlecap", "456": "bow", "457": "bow tie, bow-tie, bowtie", "458": "brass, memorial tablet, plaque", "459": "brassiere, bra, bandeau", "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty", "461": "breastplate, aegis, egis", "462": "broom", "463": "bucket, pail", "464": "buckle", "465": "bulletproof vest", "466": "bullet train, bullet", "467": "butcher shop, meat market", "468": "cab, hack, taxi, taxicab", "469": "caldron, cauldron", "470": "candle, taper, wax light", "471": "cannon", "472": "canoe", "473": "can opener, tin opener", "474": "cardigan", "475": "car mirror", "476": "carousel, carrousel, merry-go-round, roundabout, whirligig", "477": "carpenter's kit, tool kit", "478": "carton", "479": "car wheel", "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM", "481": "cassette", "482": "cassette player", "483": "castle", "484": "catamaran", "485": "CD player", "486": "cello, violoncello", "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone", "488": "chain", "489": "chainlink fence", "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour", "491": "chain saw, chainsaw", "492": "chest", "493": "chiffonier, commode", "494": "chime, bell, gong", "495": "china cabinet, china closet", "496": "Christmas stocking", "497": "church, church building", "498": "cinema, movie theater, movie theatre, movie house, picture palace", "499": "cleaver, meat cleaver, chopper", "500": "cliff dwelling", "501": "cloak", "502": "clog, geta, patten, sabot", "503": "cocktail shaker", "504": "coffee mug", "505": "coffeepot", "506": "coil, spiral, volute, whorl, helix", "507": "combination lock", "508": "computer keyboard, keypad", "509": "confectionery, confectionary, candy store", "510": "container ship, containership, container vessel", "511": "convertible", "512": "corkscrew, bottle screw", "513": "cornet, horn, trumpet, trump", "514": "cowboy boot", "515": "cowboy hat, ten-gallon hat", "516": "cradle", "517": "crane2", "518": "crash helmet", "519": "crate", "520": "crib, cot", "521": "Crock Pot", "522": "croquet ball", "523": "crutch", "524": "cuirass", "525": "dam, dike, dyke", "526": "desk", "527": "desktop computer", "528": "dial telephone, dial phone", "529": "diaper, nappy, napkin", "530": "digital clock", "531": "digital watch", "532": "dining table, board", "533": "dishrag, dishcloth", "534": "dishwasher, dish washer, dishwashing machine", "535": "disk brake, disc brake", "536": "dock, dockage, docking facility", "537": "dogsled, dog sled, dog sleigh", "538": "dome", "539": "doormat, welcome mat", "540": "drilling platform, offshore rig", "541": "drum, membranophone, tympan", "542": "drumstick", "543": "dumbbell", "544": "Dutch oven", "545": "electric fan, blower", "546": "electric guitar", "547": "electric locomotive", "548": "entertainment center", "549": "envelope", "550": "espresso maker", "551": "face powder", "552": "feather boa, boa", "553": "file, file cabinet, filing cabinet", "554": "fireboat", "555": "fire engine, fire truck", "556": "fire screen, fireguard", "557": "flagpole, flagstaff", "558": "flute, transverse flute", "559": "folding chair", "560": "football helmet", "561": "forklift", "562": "fountain", "563": "fountain pen", "564": "four-poster", "565": "freight car", "566": "French horn, horn", "567": "frying pan, frypan, skillet", "568": "fur coat", "569": "garbage truck, dustcart", "570": "gasmask, respirator, gas helmet", "571": "gas pump, gasoline pump, petrol pump, island dispenser", "572": "goblet", "573": "go-kart", "574": "golf ball", "575": "golfcart, golf cart", "576": "gondola", "577": "gong, tam-tam", "578": "gown", "579": "grand piano, grand", "580": "greenhouse, nursery, glasshouse", "581": "grille, radiator grille", "582": "grocery store, grocery, food market, market", "583": "guillotine", "584": "hair slide", "585": "hair spray", "586": "half track", "587": "hammer", "588": "hamper", "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier", "590": "hand-held computer, hand-held microcomputer", "591": "handkerchief, hankie, hanky, hankey", "592": "hard disc, hard disk, fixed disk", "593": "harmonica, mouth organ, harp, mouth harp", "594": "harp", "595": "harvester, reaper", "596": "hatchet", "597": "holster", "598": "home theater, home theatre", "599": "honeycomb", "600": "hook, claw", "601": "hoopskirt, crinoline", "602": "horizontal bar, high bar", "603": "horse cart, horse-cart", "604": "hourglass", "605": "iPod", "606": "iron, smoothing iron", "607": "jack-o'-lantern", "608": "jean, blue jean, denim", "609": "jeep, landrover", "610": "jersey, T-shirt, tee shirt", "611": "jigsaw puzzle", "612": "jinrikisha, ricksha, rickshaw", "613": "joystick", "614": "kimono", "615": "knee pad", "616": "knot", "617": "lab coat, laboratory coat", "618": "ladle", "619": "lampshade, lamp shade", "620": "laptop, laptop computer", "621": "lawn mower, mower", "622": "lens cap, lens cover", "623": "letter opener, paper knife, paperknife", "624": "library", "625": "lifeboat", "626": "lighter, light, igniter, ignitor", "627": "limousine, limo", "628": "liner, ocean liner", "629": "lipstick, lip rouge", "630": "Loafer", "631": "lotion", "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system", "633": "loupe, jeweler's loupe", "634": "lumbermill, sawmill", "635": "magnetic compass", "636": "mailbag, postbag", "637": "mailbox, letter box", "638": "maillot", "639": "maillot, tank suit", "640": "manhole cover", "641": "maraca", "642": "marimba, xylophone", "643": "mask", "644": "matchstick", "645": "maypole", "646": "maze, labyrinth", "647": "measuring cup", "648": "medicine chest, medicine cabinet", "649": "megalith, megalithic structure", "650": "microphone, mike", "651": "microwave, microwave oven", "652": "military uniform", "653": "milk can", "654": "minibus", "655": "miniskirt, mini", "656": "minivan", "657": "missile", "658": "mitten", "659": "mixing bowl", "660": "mobile home, manufactured home", "661": "Model T", "662": "modem", "663": "monastery", "664": "monitor", "665": "moped", "666": "mortar", "667": "mortarboard", "668": "mosque", "669": "mosquito net", "670": "motor scooter, scooter", "671": "mountain bike, all-terrain bike, off-roader", "672": "mountain tent", "673": "mouse, computer mouse", "674": "mousetrap", "675": "moving van", "676": "muzzle", "677": "nail", "678": "neck brace", "679": "necklace", "680": "nipple", "681": "notebook, notebook computer", "682": "obelisk", "683": "oboe, hautboy, hautbois", "684": "ocarina, sweet potato", "685": "odometer, hodometer, mileometer, milometer", "686": "oil filter", "687": "organ, pipe organ", "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO", "689": "overskirt", "690": "oxcart", "691": "oxygen mask", "692": "packet", "693": "paddle, boat paddle", "694": "paddlewheel, paddle wheel", "695": "padlock", "696": "paintbrush", "697": "pajama, pyjama, pj's, jammies", "698": "palace", "699": "panpipe, pandean pipe, syrinx", "700": "paper towel", "701": "parachute, chute", "702": "parallel bars, bars", "703": "park bench", "704": "parking meter", "705": "passenger car, coach, carriage", "706": "patio, terrace", "707": "pay-phone, pay-station", "708": "pedestal, plinth, footstall", "709": "pencil box, pencil case", "710": "pencil sharpener", "711": "perfume, essence", "712": "Petri dish", "713": "photocopier", "714": "pick, plectrum, plectron", "715": "pickelhaube", "716": "picket fence, paling", "717": "pickup, pickup truck", "718": "pier", "719": "piggy bank, penny bank", "720": "pill bottle", "721": "pillow", "722": "ping-pong ball", "723": "pinwheel", "724": "pirate, pirate ship", "725": "pitcher, ewer", "726": "plane, carpenter's plane, woodworking plane", "727": "planetarium", "728": "plastic bag", "729": "plate rack", "730": "plow, plough", "731": "plunger, plumber's helper", "732": "Polaroid camera, Polaroid Land camera", "733": "pole", "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria", "735": "poncho", "736": "pool table, billiard table, snooker table", "737": "pop bottle, soda bottle", "738": "pot, flowerpot", "739": "potter's wheel", "740": "power drill", "741": "prayer rug, prayer mat", "742": "printer", "743": "prison, prison house", "744": "projectile, missile", "745": "projector", "746": "puck, hockey puck", "747": "punching bag, punch bag, punching ball, punchball", "748": "purse", "749": "quill, quill pen", "750": "quilt, comforter, comfort, puff", "751": "racer, race car, racing car", "752": "racket, racquet", "753": "radiator", "754": "radio, wireless", "755": "radio telescope, radio reflector", "756": "rain barrel", "757": "recreational vehicle, RV, R.V.", "758": "reel", "759": "reflex camera", "760": "refrigerator, icebox", "761": "remote control, remote", "762": "restaurant, eating house, eating place, eatery", "763": "revolver, six-gun, six-shooter", "764": "rifle", "765": "rocking chair, rocker", "766": "rotisserie", "767": "rubber eraser, rubber, pencil eraser", "768": "rugby ball", "769": "rule, ruler", "770": "running shoe", "771": "safe", "772": "safety pin", "773": "saltshaker, salt shaker", "774": "sandal", "775": "sarong", "776": "sax, saxophone", "777": "scabbard", "778": "scale, weighing machine", "779": "school bus", "780": "schooner", "781": "scoreboard", "782": "screen, CRT screen", "783": "screw", "784": "screwdriver", "785": "seat belt, seatbelt", "786": "sewing machine", "787": "shield, buckler", "788": "shoe shop, shoe-shop, shoe store", "789": "shoji", "790": "shopping basket", "791": "shopping cart", "792": "shovel", "793": "shower cap", "794": "shower curtain", "795": "ski", "796": "ski mask", "797": "sleeping bag", "798": "slide rule, slipstick", "799": "sliding door", "800": "slot, one-armed bandit", "801": "snorkel", "802": "snowmobile", "803": "snowplow, snowplough", "804": "soap dispenser", "805": "soccer ball", "806": "sock", "807": "solar dish, solar collector, solar furnace", "808": "sombrero", "809": "soup bowl", "810": "space bar", "811": "space heater", "812": "space shuttle", "813": "spatula", "814": "speedboat", "815": "spider web, spider's web", "816": "spindle", "817": "sports car, sport car", "818": "spotlight, spot", "819": "stage", "820": "steam locomotive", "821": "steel arch bridge", "822": "steel drum", "823": "stethoscope", "824": "stole", "825": "stone wall", "826": "stopwatch, stop watch", "827": "stove", "828": "strainer", "829": "streetcar, tram, tramcar, trolley, trolley car", "830": "stretcher", "831": "studio couch, day bed", "832": "stupa, tope", "833": "submarine, pigboat, sub, U-boat", "834": "suit, suit of clothes", "835": "sundial", "836": "sunglass", "837": "sunglasses, dark glasses, shades", "838": "sunscreen, sunblock, sun blocker", "839": "suspension bridge", "840": "swab, swob, mop", "841": "sweatshirt", "842": "swimming trunks, bathing trunks", "843": "swing", "844": "switch, electric switch, electrical switch", "845": "syringe", "846": "table lamp", "847": "tank, army tank, armored combat vehicle, armoured combat vehicle", "848": "tape player", "849": "teapot", "850": "teddy, teddy bear", "851": "television, television system", "852": "tennis ball", "853": "thatch, thatched roof", "854": "theater curtain, theatre curtain", "855": "thimble", "856": "thresher, thrasher, threshing machine", "857": "throne", "858": "tile roof", "859": "toaster", "860": "tobacco shop, tobacconist shop, tobacconist", "861": "toilet seat", "862": "torch", "863": "totem pole", "864": "tow truck, tow car, wrecker", "865": "toyshop", "866": "tractor", "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi", "868": "tray", "869": "trench coat", "870": "tricycle, trike, velocipede", "871": "trimaran", "872": "tripod", "873": "triumphal arch", "874": "trolleybus, trolley coach, trackless trolley", "875": "trombone", "876": "tub, vat", "877": "turnstile", "878": "typewriter keyboard", "879": "umbrella", "880": "unicycle, monocycle", "881": "upright, upright piano", "882": "vacuum, vacuum cleaner", "883": "vase", "884": "vault", "885": "velvet", "886": "vending machine", "887": "vestment", "888": "viaduct", "889": "violin, fiddle", "890": "volleyball", "891": "waffle iron", "892": "wall clock", "893": "wallet, billfold, notecase, pocketbook", "894": "wardrobe, closet, press", "895": "warplane, military plane", "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin", "897": "washer, automatic washer, washing machine", "898": "water bottle", "899": "water jug", "900": "water tower", "901": "whiskey jug", "902": "whistle", "903": "wig", "904": "window screen", "905": "window shade", "906": "Windsor tie", "907": "wine bottle", "908": "wing", "909": "wok", "910": "wooden spoon", "911": "wool, woolen, woollen", "912": "worm fence, snake fence, snake-rail fence, Virginia fence", "913": "wreck", "914": "yawl", "915": "yurt", "916": "web site, website, internet site, site", "917": "comic book", "918": "crossword puzzle, crossword", "919": "street sign", "920": "traffic light, traffic signal, stoplight", "921": "book jacket, dust cover, dust jacket, dust wrapper", "922": "menu", "923": "plate", "924": "guacamole", "925": "consomme", "926": "hot pot, hotpot", "927": "trifle", "928": "ice cream, icecream", "929": "ice lolly, lolly, lollipop, popsicle", "930": "French loaf", "931": "bagel, beigel", "932": "pretzel", "933": "cheeseburger", "934": "hotdog, hot dog, red hot", "935": "mashed potato", "936": "head cabbage", "937": "broccoli", "938": "cauliflower", "939": "zucchini, courgette", "940": "spaghetti squash", "941": "acorn squash", "942": "butternut squash", "943": "cucumber, cuke", "944": "artichoke, globe artichoke", "945": "bell pepper", "946": "cardoon", "947": "mushroom", "948": "Granny Smith", "949": "strawberry", "950": "orange", "951": "lemon", "952": "fig", "953": "pineapple, ananas", "954": "banana", "955": "jackfruit, jak, jack", "956": "custard apple", "957": "pomegranate", "958": "hay", "959": "carbonara", "960": "chocolate sauce, chocolate syrup", "961": "dough", "962": "meat loaf, meatloaf", "963": "pizza, pizza pie", "964": "potpie", "965": "burrito", "966": "red wine", "967": "espresso", "968": "cup", "969": "eggnog", "970": "alp", "971": "bubble", "972": "cliff, drop, drop-off", "973": "coral reef", "974": "geyser", "975": "lakeside, lakeshore", "976": "promontory, headland, head, foreland", "977": "sandbar, sand bar", "978": "seashore, coast, seacoast, sea-coast", "979": "valley, vale", "980": "volcano", "981": "ballplayer, baseball player", "982": "groom, bridegroom", "983": "scuba diver", "984": "rapeseed", "985": "daisy", "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum", "987": "corn", "988": "acorn", "989": "hip, rose hip, rosehip", "990": "buckeye, horse chestnut, conker", "991": "coral fungus", "992": "agaric", "993": "gyromitra", "994": "stinkhorn, carrion fungus", "995": "earthstar", "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa", "997": "bolete", "998": "ear, spike, capitulum", "999": "toilet tissue, toilet paper, bathroom tissue"}}}}]
{}
tomc43841/public_smash_little_dataset
default
0
32
["size_categories:1K<n<10K", "format:parquet", "modality:image", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-12-05T23:49:47
2023-12-05T23:50:22
[{"name": "image", "dtype": "image"}, {"name": "Start", "dtype": "bool"}, {"name": "A", "dtype": "bool"}, {"name": "B", "dtype": "bool"}, {"name": "X", "dtype": "bool"}, {"name": "Y", "dtype": "bool"}, {"name": "Z", "dtype": "bool"}, {"name": "DPadUp", "dtype": "bool"}, {"name": "DPadDown", "dtype": "bool"}, {"name": "DPadLeft", "dtype": "bool"}, {"name": "DPadRight", "dtype": "bool"}, {"name": "L", "dtype": "bool"}, {"name": "R", "dtype": "bool"}, {"name": "LPressure", "dtype": "int64"}, {"name": "RPressure", "dtype": "int64"}, {"name": "XAxis", "dtype": "int64"}, {"name": "YAxis", "dtype": "int64"}, {"name": "CXAxis", "dtype": "int64"}, {"name": "CYAxis", "dtype": "int64"}]
{}
selfcorrexp2/llama3_morewrong_rr60k_3ep_dpo_gen_mix_type1
default
0
31
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-13T18:21:18
2025-01-15T09:24:22
[{"name": "chosen_txt", "dtype": "string"}, {"name": "rejected_txt", "dtype": "string"}, {"name": "gt", "dtype": "string"}, {"name": "chosen", "dtype": "string"}, {"name": "rejected", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "margin", "dtype": "float64"}]
{}
andrewsiah/personalization_prompt_response_ziya_llama_7b
default
0
29
["size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-05-31T14:58:44
2024-05-31T15:15:39
[{"name": "reward_1", "dtype": "float64"}, {"name": "reward_2", "dtype": "float64"}, {"name": "reward_3", "dtype": "float64"}, {"name": "reward_4", "dtype": "float64"}, {"name": "reward_5", "dtype": "float64"}, {"name": "reward_6", "dtype": "float64"}, {"name": "reward_7", "dtype": "float64"}, {"name": "reward_8", "dtype": "float64"}, {"name": "prompt", "dtype": "string"}, {"name": "subset", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "response_1", "dtype": "string"}, {"name": "response_1_model", "dtype": "string"}, {"name": "response_2", "dtype": "string"}, {"name": "response_2_model", "dtype": "string"}, {"name": "response_3", "dtype": "string"}, {"name": "response_3_model", "dtype": "string"}, {"name": "response_4", "dtype": "string"}, {"name": "response_4_model", "dtype": "string"}, {"name": "response_5", "dtype": "string"}, {"name": "response_5_model", "dtype": "string"}, {"name": "response_6", "dtype": "string"}, {"name": "response_6_model", "dtype": "string"}, {"name": "response_7", "dtype": "string"}, {"name": "response_7_model", "dtype": "string"}, {"name": "response_8", "dtype": "string"}, {"name": "response_8_model", "dtype": "string"}, {"name": "rformatted_promptresponse_1", "dtype": "string"}, {"name": "rformatted_promptresponse_2", "dtype": "string"}, {"name": "rformatted_promptresponse_3", "dtype": "string"}, {"name": "rformatted_promptresponse_4", "dtype": "string"}, {"name": "rformatted_promptresponse_5", "dtype": "string"}, {"name": "rformatted_promptresponse_6", "dtype": "string"}, {"name": "rformatted_promptresponse_7", "dtype": "string"}, {"name": "rformatted_promptresponse_8", "dtype": "string"}]
{}
kristmh/clean_Qt_balanced
default
0
31
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-17T14:27:13
2024-03-17T14:27:16
[{"name": "text_clean", "dtype": "string"}, {"name": "label", "dtype": "int64"}]
{}
Itsunori/slake_jap
default
0
29
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-23T05:47:58
2024-07-23T05:48:00
[{"name": "img_name", "dtype": "string"}, {"name": "location", "dtype": "string"}, {"name": "modality", "dtype": "string"}, {"name": "base_type", "dtype": "string"}, {"name": "answer_type", "dtype": "string"}, {"name": "qid", "dtype": "int64"}, {"name": "content_type", "dtype": "string"}, {"name": "triple", "sequence": "string"}, {"name": "img_id", "dtype": "int64"}, {"name": "q_lang", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}]
{}
1231czx/REFUEL_sampled_h_from_sampled_len_ckp_3
default
0
39
["size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-05T23:48:45
2024-11-05T23:48:46
[{"name": "trajectory_sampled_h_from_sampled_len", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "sampled_len_from_5", "dtype": "int64"}, {"name": "sampled_h_from_sampled_len", "dtype": "int64"}]
{}
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_b3a5db6c-89c3-4742-9624-fdf54a41409a
default
0
36
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-10-28T15:43:38
2024-10-28T15:43:39
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "positive", "1": "negative"}}}}]
{}
Codec-SUPERB/vocal_imitation_extract_unit
default
0
36
["size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-12-21T03:54:15
2023-12-21T03:56:04
[{"name": "id", "dtype": "string"}, {"name": "unit", "sequence": {"sequence": "int64"}}]
{}
Korsholm22/go-emotion-dk-autotranlated-10k
default
0
34
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-02-27T13:00:01
2023-02-27T13:00:14
[{"name": "text_en", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "labels", "dtype": {"class_label": {"names": {"0": "admiration", "1": "amusement", "2": "anger", "3": "annoyance", "4": "approval", "5": "caring", "6": "confusion", "7": "curiosity", "8": "desire", "9": "disappointment", "10": "disapproval", "11": "disgust", "12": "embarrassment", "13": "excitement", "14": "fear", "15": "gratitude", "16": "grief", "17": "joy", "18": "love", "19": "nervousness", "20": "neutral", "21": "optimism", "22": "pride", "23": "realization", "24": "relief", "25": "remorse", "26": "sadness", "27": "surprise"}}}}, {"name": "__index_level_0__", "dtype": "int64"}, {"name": "input_ids", "sequence": "int32"}, {"name": "token_type_ids", "sequence": "int8"}, {"name": "attention_mask", "sequence": "int8"}]
{}
Joooorrit/twitter_dataset_1718768841
default
0
32
["format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-06-19T03:47:22
2024-06-19T03:47:58
[{"name": "id", "dtype": "null"}, {"name": "tweet_content", "dtype": "null"}, {"name": "user_name", "dtype": "null"}, {"name": "user_id", "dtype": "null"}, {"name": "created_at", "dtype": "null"}, {"name": "url", "dtype": "null"}, {"name": "favourite_count", "dtype": "null"}, {"name": "scraped_at", "dtype": "null"}, {"name": "image_urls", "dtype": "null"}]
{}
EgilKarlsen/BGL_GPT2_Baseline
default
0
30
["size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-08-18T14:55:35
2023-08-18T15:27:40
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"float32"}, {"name": "732", "dtype": "float32"}, {"name": "733", "dtype": "float32"}, {"name": "734", "dtype": "float32"}, {"name": "735", "dtype": "float32"}, {"name": "736", "dtype": "float32"}, {"name": "737", "dtype": "float32"}, {"name": "738", "dtype": "float32"}, {"name": "739", "dtype": "float32"}, {"name": "740", "dtype": "float32"}, {"name": "741", "dtype": "float32"}, {"name": "742", "dtype": "float32"}, {"name": "743", "dtype": "float32"}, {"name": "744", "dtype": "float32"}, {"name": "745", "dtype": "float32"}, {"name": "746", "dtype": "float32"}, {"name": "747", "dtype": "float32"}, {"name": "748", "dtype": "float32"}, {"name": "749", "dtype": "float32"}, {"name": "750", "dtype": "float32"}, {"name": "751", "dtype": "float32"}, {"name": "752", "dtype": "float32"}, {"name": "753", "dtype": "float32"}, {"name": "754", "dtype": "float32"}, {"name": "755", "dtype": "float32"}, {"name": "756", "dtype": "float32"}, {"name": "757", "dtype": "float32"}, {"name": "758", "dtype": "float32"}, {"name": "759", "dtype": "float32"}, {"name": "760", "dtype": "float32"}, {"name": "761", "dtype": "float32"}, {"name": "762", "dtype": "float32"}, {"name": "763", "dtype": "float32"}, {"name": "764", "dtype": "float32"}, {"name": "765", "dtype": "float32"}, {"name": "766", "dtype": "float32"}, {"name": "767", "dtype": "float32"}, {"name": "label", "dtype": "string"}]
{}
griffin/iclr-synthetic
default
0
34
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-10T19:05:54
2024-09-10T19:06:00
[{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "meta", "dtype": "string"}, {"name": "question_type", "dtype": "string"}, {"name": "fact", "dtype": "string"}, {"name": "rationale", "dtype": "string"}]
{}
Cartinoe5930/stock_debate_49_sent
default
0
36
["size_categories:100K<n<1M", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-23T00:54:05
2024-07-23T00:54:13
[{"name": "\ub0a0\uc9dc", "dtype": "string"}, {"name": "\uc81c\ubaa9", "dtype": "string"}, {"name": "\ub313\uae00 \uac1c\uc218", "dtype": "float64"}, {"name": "\uae00\uc4f4\uc774", "dtype": "string"}, {"name": "\uc870\ud68c", "dtype": "float64"}, {"name": "\uacf5\uac10", "dtype": "float64"}, {"name": "\ube44\uacf5\uac10", "dtype": "float64"}, {"name": "\uae00 ID", "dtype": "float64"}, {"name": "\ub0b4\uc6a9", "dtype": "string"}, {"name": "\uc885\ubaa9\uba85", "dtype": "string"}, {"name": "\uc885\ubaa9\ucf54\ub4dc", "dtype": "int64"}, {"name": "KorFinASC_XLM_RoBERTa", "dtype": "string"}, {"name": "KR_FinBert_SC", "dtype": "string"}, {"name": "distilbert_base_multilingual_cased_sentiment_sent_result", "dtype": "string"}, {"name": "distilbert_base_multilingual_cased_sentiments_student_sent_result", "dtype": "string"}, {"name": "twitter_xlm_roberta_base_sentiment_multilingual_sent_result", "dtype": "string"}]
{}
HuangJordan/Whisper_Dataset
default
0
39
["language:zh", "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
["zh"]
null
2024-05-10T03:54:20
2024-05-14T03:34:45
[{"name": "audio_feature", "struct": [{"name": "array", "sequence": "float64"}, {"name": "path", "dtype": "string"}, {"name": "sampling_rate", "dtype": "int64"}]}, {"name": "sentences", "dtype": "string"}]
{}
jxie/language_table-first_100_samples-100_points-mwt0.5
default
0
44
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-04T21:33:38
2025-01-05T08:21:56
[{"name": "video", "dtype": "video"}, {"name": "tracks", "sequence": {"sequence": {"sequence": "float64"}}}, {"name": "query_points", "sequence": {"sequence": "float64"}}, {"name": "visibles", "sequence": {"sequence": "bool"}}, {"name": "text", "dtype": "string"}]
{}
twright8/testdata2
default
0
34
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-18T08:46:56
2024-07-18T08:46:59
[{"name": "conversations", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "text", "dtype": "string"}]
{}
arjunashok/climate-5day-zeroshot-freshexps-test-llama3370binstructcache2
default
0
26
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-09T20:25:55
2025-01-09T20:26:00
[{"name": "input_text", "dtype": "string"}, {"name": "output_text", "dtype": "string"}, {"name": "input_text_time", "dtype": "string"}, {"name": "output_text_time", "dtype": "string"}, {"name": "output_time", "dtype": "string"}, {"name": "input_num", "sequence": {"sequence": "float64"}}, {"name": "output_num", "sequence": {"sequence": "float64"}}, {"name": "instruction-1", "dtype": "string"}, {"name": "instruction-2", "dtype": "string"}, {"name": "instruction-3", "dtype": "string"}, {"name": "instruction-4", "dtype": "string"}, {"name": "pred_output_case1", "dtype": "string"}, {"name": "pred_output_case2", "dtype": "string"}, {"name": "pred_output_case3", "dtype": "string"}, {"name": "pred_output_case4", "dtype": "string"}]
{}
tmpmodelsave/fixed_beta01_llama3_sft_math_type12_8ktype4_and_8ktype3_no_sft_loss200tmp10
default
0
13
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-15T18:57:49
2025-01-15T18:57:51
[{"name": "idx", "dtype": "int64"}, {"name": "gt", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "level", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "solution", "dtype": "string"}, {"name": "my_solu", "sequence": "string"}, {"name": "pred", "sequence": "string"}, {"name": "rewards", "sequence": "bool"}]
{}
andrewsiah/PersonaPromptPersonalLLM_791
default
0
32
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-07T05:41:25
2024-08-07T05:41:27
[{"name": "personaid_791_response_1_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_2_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_3_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_4_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_5_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_6_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_7_llama3_sfairx", "dtype": "float64"}, {"name": "personaid_791_response_8_llama3_sfairx", "dtype": "float64"}, {"name": "prompt", "dtype": "string"}, {"name": "subset", "dtype": "string"}, {"name": "prompt_id", "dtype": "int64"}, {"name": "response_1", "dtype": "string"}, {"name": "response_1_model", "dtype": "string"}, {"name": "response_2", "dtype": "string"}, {"name": "response_2_model", "dtype": "string"}, {"name": "response_3", "dtype": "string"}, {"name": "response_3_model", "dtype": "string"}, {"name": "response_4", 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"dtype": "float64"}, {"name": "response_4_gemma_7b", "dtype": "float64"}, {"name": "response_5_gemma_7b", "dtype": "float64"}, {"name": "response_6_gemma_7b", "dtype": "float64"}, {"name": "response_7_gemma_7b", "dtype": "float64"}, {"name": "response_8_gemma_7b", "dtype": "float64"}, {"name": "response_1_mistral_raft", "dtype": "float64"}, {"name": "response_2_mistral_raft", "dtype": "float64"}, {"name": "response_3_mistral_raft", "dtype": "float64"}, {"name": "response_4_mistral_raft", "dtype": "float64"}, {"name": "response_5_mistral_raft", "dtype": "float64"}, {"name": "response_6_mistral_raft", "dtype": "float64"}, {"name": "response_7_mistral_raft", "dtype": "float64"}, {"name": "response_8_mistral_raft", "dtype": "float64"}, {"name": "response_1_mistral_ray", "dtype": "float64"}, {"name": "response_2_mistral_ray", "dtype": "float64"}, {"name": "response_3_mistral_ray", "dtype": "float64"}, {"name": "response_4_mistral_ray", "dtype": "float64"}, {"name": "response_5_mistral_ray", "dtype": "float64"}, {"name": "response_6_mistral_ray", "dtype": "float64"}, {"name": "response_7_mistral_ray", "dtype": "float64"}, {"name": "response_8_mistral_ray", "dtype": "float64"}, {"name": "response_1_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_2_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_3_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_4_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_5_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_6_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_7_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_8_mistral_weqweasdas", "dtype": "float64"}, {"name": "response_1_llama3_sfairx", "dtype": "float64"}, {"name": "response_2_llama3_sfairx", "dtype": "float64"}, {"name": "response_3_llama3_sfairx", "dtype": "float64"}, {"name": "response_4_llama3_sfairx", "dtype": "float64"}, {"name": "response_5_llama3_sfairx", "dtype": "float64"}, {"name": "response_6_llama3_sfairx", "dtype": "float64"}, {"name": "response_7_llama3_sfairx", "dtype": "float64"}, {"name": "response_8_llama3_sfairx", "dtype": "float64"}, {"name": "response_1_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_2_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_3_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_4_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_5_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_6_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_7_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_8_oasst_deberta_v3", "dtype": "float64"}, {"name": "response_1_beaver_7b", "dtype": "float64"}, {"name": "response_2_beaver_7b", "dtype": "float64"}, {"name": "response_3_beaver_7b", "dtype": "float64"}, {"name": "response_4_beaver_7b", "dtype": "float64"}, {"name": "response_5_beaver_7b", "dtype": "float64"}, {"name": "response_6_beaver_7b", "dtype": "float64"}, {"name": "response_7_beaver_7b", "dtype": "float64"}, {"name": "response_8_beaver_7b", "dtype": "float64"}, {"name": "response_1_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_2_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_3_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_4_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_5_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_6_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_7_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_8_oasst_pythia_7b", "dtype": "float64"}, {"name": "response_1_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_2_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_3_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_4_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_5_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_6_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_7_oasst_pythia_1b", "dtype": "float64"}, {"name": "response_8_oasst_pythia_1b", "dtype": "float64"}, {"name": "id", "dtype": "int64"}, {"name": "rformatted_promptresponse_1", "dtype": "string"}, {"name": "rformatted_promptresponse_2", "dtype": "string"}, {"name": "rformatted_promptresponse_3", "dtype": "string"}, {"name": "rformatted_promptresponse_4", "dtype": "string"}, {"name": "rformatted_promptresponse_5", "dtype": "string"}, {"name": "rformatted_promptresponse_6", "dtype": "string"}, {"name": "rformatted_promptresponse_7", "dtype": "string"}, {"name": "rformatted_promptresponse_8", "dtype": "string"}]
{}
stroopc/emoji_therapist
default
3
33
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-04-26T19:52:53
2023-04-26T20:19:11
[{"name": "sentence", "dtype": "string"}, {"name": "emoji_therapist", "dtype": "string"}]
{}
yijunshengjax/duankou
default
0
34
["size_categories:n<1K", "format:parquet", "modality:image", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-09T08:36:29
2024-08-09T08:51:35
[{"name": "pixel_values", "dtype": "image"}, {"name": "label", "dtype": "image"}]
{}
Data-Agora/general_llama3.1_70b_instruct_50000
default
0
32
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-25T21:00:03
2024-09-25T21:00:06
[{"name": "config", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "response", "dtype": "string"}]
{}
pysentimiento/emociones_colombia
default
0
43
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-12T13:55:41
2024-08-12T14:51:09
[{"name": "text", "dtype": "string"}, {"name": "tweet_id", "dtype": "int64"}, {"name": "alegria", "dtype": {"class_label": {"names": {"0": "no_alegria", "1": "alegria"}}}}, {"name": "miedo", "dtype": {"class_label": {"names": {"0": "no_miedo", "1": "miedo"}}}}, {"name": "asco", "dtype": {"class_label": {"names": {"0": "no_asco", "1": "asco"}}}}, {"name": "tristeza", "dtype": {"class_label": {"names": {"0": "no_tristeza", "1": "tristeza"}}}}, {"name": "gpt-3.5_cot", "dtype": "string"}]
{}
joey234/mmlu-high_school_biology-neg-prepend-verbal
default
1
62
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-01-10T05:52:56
2024-01-11T07:02:38
[{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}]
{}
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_66747397-bfe8-464c-b9c6-63f7f44246a2
default
0
34
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-23T10:30:41
2024-09-23T10:30:42
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "positive", "1": "negative"}}}}]
{}
YYYYYYibo/ultrafeedback_binarized_simple_online_train_part_1_mini_2
default
0
32
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-05-20T03:10:39
2024-05-20T03:10:41
[{"name": "prompt", "dtype": "string"}, {"name": "prompt_id", "dtype": "string"}, {"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "score_chosen", "dtype": "float64"}, {"name": "score_rejected", "dtype": "float64"}, {"name": "reference_response", "dtype": "string"}, {"name": "chosen", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "rejected", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
Hack90/ncbi_genbank_part_0
default
0
32
["size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-10-04T18:59:55
2023-10-04T19:45:14
[{"name": "id", "dtype": "string"}, {"name": "sequence", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "features", "dtype": "int64"}, {"name": "seq_length", "dtype": "int64"}]
{}
math-extraction-comp/cognitivecomputations__dolphin-2.9.4-gemma2-2b
default
0
27
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-11T10:39:13
2025-01-12T10:14:07
[{"name": "question", "dtype": "string"}, {"name": "gold", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "prediction", "dtype": "string"}, {"name": "subset", "dtype": "string"}, {"name": "lighteval-c24870ea_extracted_answer", "dtype": "string"}, {"name": "lighteval-c24870ea_score", "dtype": "float64"}, {"name": "harness_score", "dtype": "float64"}, {"name": "qwen_extracted_answer", "dtype": "string"}, {"name": "lighteval-0f21c935_score", "dtype": "float64"}, {"name": "qwen_score", "dtype": "float64"}, {"name": "lighteval-0f21c935_extracted_answer", "dtype": "string"}, {"name": "harness_extracted_answer", "dtype": "string"}]
{}
deepak-newzera/spectrogram_data_Upbeat-4s
default
0
29
["size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-03-09T05:34:56
2023-03-09T05:36:06
[{"name": "image", "dtype": "image"}, {"name": "audio_file", "dtype": "string"}, {"name": "slice", "dtype": "int16"}]
{}
Paoloc99/random_dataset_gold_at_0
default
0
45
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-20T17:45:43
2024-09-20T17:46:05
[{"name": "prompt", "dtype": "string"}, {"name": "completion", "dtype": "string"}]
{}
RyanYr/reflect_mmlupromath-test_nonGenCritic_t1_crtc
default
0
8
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-17T03:52:58
2025-01-17T04:49:42
[{"name": "question_id", "dtype": "int64"}, {"name": "original_question", "dtype": "string"}, {"name": "options", "sequence": "string"}, {"name": "answer", "dtype": "string"}, {"name": "answer_index", "dtype": "int64"}, {"name": "cot_content", "dtype": "string"}, {"name": "category", "dtype": "string"}, {"name": "src", "dtype": "string"}, {"name": "problem", "dtype": "string"}, {"name": "alt_answer", "dtype": "string"}, {"name": "response@0", "sequence": "string"}, {"name": "response@1", "dtype": "float64"}]
{}
Zappu/Pub-Chem-actIn-70M
default
0
30
["license:apache-2.0", "size_categories:10M<n<100M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
"apache-2.0"
2024-09-03T03:59:47
2024-09-03T04:41:10
[{"name": "cmpdname", "dtype": "string"}, {"name": "cmpdsynonym", "dtype": "string"}, {"name": "mf", "dtype": "string"}]
{}
gregorgabrovsek/imdb1m-top-100-users
default
0
35
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-04-15T08:53:48
2023-04-15T08:53:58
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}]
{}
vira-chatbot/vira-intents-mod
default
0
32
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-10-26T18:04:54
2023-10-31T03:54:15
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}]
{}
Daksh1/finetuningForInstruct
default
0
20
["size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-13T14:43:02
2025-01-13T14:43:18
[{"name": "conversations", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
gsstein/75-percent-human-dataset-llama-mistake
default
0
31
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-28T23:09:13
2024-03-28T23:09:32
[{"name": "id", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "summary", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "generated", "dtype": "bool"}, {"name": "raw_summary", "dtype": "string"}]
{}
math-extraction-comp/vicgalle__CarbonBeagle-11B-truthy
default
0
21
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-11T17:39:39
2025-01-11T17:39:41
[{"name": "question", "dtype": "string"}, {"name": "gold", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "prediction", "dtype": "string"}, {"name": "subset", "dtype": "string"}, {"name": "qwen_extracted_answer", "dtype": "string"}, {"name": "qwen_score", "dtype": "float64"}, {"name": "lighteval-0f21c935_extracted_answer", "dtype": "string"}, {"name": "lighteval-0f21c935_score", "dtype": "float64"}, {"name": "harness_extracted_answer", "dtype": "string"}, {"name": "harness_score", "dtype": "float64"}]
{}
Vasanth/squad-demo-preference-dataset
default
0
34
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-07-31T00:45:18
2024-07-31T00:45:24
[{"name": "id", "dtype": "string"}, {"name": "chosen", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "rejected", "dtype": "string"}, {"name": "answers", "struct": [{"name": "answer_start", "sequence": "int64"}, {"name": "text", "sequence": "string"}]}]
{}
sunnyday910/fractal_flame
default
0
22
["size_categories:n<1K", "format:parquet", "modality:image", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-08T03:34:16
2025-01-08T03:34:24
[{"name": "image", "dtype": "image"}]
{}
winglian/slimorca-i18n
default
1
45
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-10-28T06:26:33
2023-11-03T08:40:31
[{"name": "old_conversation", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}, {"name": "weight", "dtype": "float64"}]}, {"name": "conversation", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "target_language", "dtype": "string"}]
{}
MayAlsofyani/OneBugMixCot4
default
0
36
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-11T23:38:33
2024-11-11T23:44:03
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "response", "dtype": "string"}]
{}
rishitunu/ecc_crackdetector_dataset_main
default
0
33
["size_categories:n<1K", "format:parquet", "modality:image", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-08-27T17:37:16
2023-08-27T17:42:46
[{"name": "image", "dtype": "image"}, {"name": "label", "dtype": "image"}]
{}
lewtun/custom-splits-test
default
0
30
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-04-04T21:08:30
2023-04-04T21:09:06
[{"name": "text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "sadness", "1": "joy", "2": "love", "3": "anger", "4": "fear", "5": "surprise"}}}}]
{}
mask-distilled-one-sec-cv12/chunk_262
default
0
38
["size_categories:100K<n<1M", "format:parquet", "modality:timeseries", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-05-22T20:05:51
2023-05-22T20:06:31
[{"name": "logits", "sequence": "float32"}, {"name": "mfcc", "sequence": {"sequence": "float64"}}]
{}
Kushtrim/sst2-norwegian-bokmaal
default
0
29
["task_categories:text-classification", "language:no", "language:en", "size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
["no", "en"]
null
2024-01-13T15:45:40
2024-01-13T22:09:38
[{"name": "idx", "dtype": "int64"}, {"name": "sentence", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "sentence_nob", "dtype": "string"}]
{}
jganzabalseenka/Tweet_2024-08-27T20_24hs
default
0
31
["size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-28T23:40:27
2024-08-28T23:40:29
[{"name": "asset_id", "dtype": "int64"}, {"name": "title_ch", "dtype": "string"}, {"name": "Asset Destination", "dtype": "string"}, {"name": "media", "dtype": "string"}, {"name": "impact", "dtype": "int64"}, {"name": "start_time_utc", "dtype": "timestamp[ns]"}, {"name": "start_time_local", "dtype": "timestamp[ns]"}, {"name": "entities_curated", "sequence": "string"}, {"name": "entities", "sequence": "string"}, {"name": "predicted_at_entities", "dtype": "timestamp[ns]"}, {"name": "entities_raw_transformers", "list": [{"name": "entities", "list": [{"name": "end", "dtype": "int64"}, {"name": "entity_group", "dtype": "string"}, {"name": "score", "dtype": "float64"}, {"name": "start", "dtype": "int64"}, {"name": "word", "dtype": "string"}]}, {"name": "text", "dtype": "string"}]}, {"name": "entities_transformers", "sequence": "string"}, {"name": "keywords", "sequence": "string"}, {"name": "predicted_at_keywords", "dtype": "timestamp[ns]"}, {"name": "title", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "predicted_at_text", "dtype": "timestamp[us, tz=UTC]"}, {"name": "truncated_text", "dtype": "string"}, {"name": "title_and_text", "dtype": "string"}, {"name": "prediction_delay_predictions", "dtype": "float64"}, {"name": "prediction_delay", "dtype": "float64"}]
{}
EleutherAI/profiles_dataset_25000
default
0
40
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-05T01:03:24
2024-11-05T01:03:25
[{"name": "name", "dtype": "string"}, {"name": "index", "dtype": "int32"}, {"name": "birth_date", "dtype": "timestamp[s]"}, {"name": "birth_city", "dtype": "string"}, {"name": "university", "dtype": "string"}, {"name": "employer", "dtype": "string"}, {"name": "parent", "struct": [{"name": "name", "dtype": "string"}, {"name": "index", "dtype": "int32"}]}, {"name": "child", "struct": [{"name": "name", "dtype": "string"}, {"name": "index", "dtype": "int32"}]}, {"name": "best_friend", "struct": [{"name": "name", "dtype": "string"}, {"name": "index", "dtype": "int32"}]}, {"name": "worst_enemy", "struct": [{"name": "name", "dtype": "string"}, {"name": "index", "dtype": "int32"}]}, {"name": "bio", "dtype": "string"}]
{}
juliadollis/stf_regex_ner_pierre_79
default
0
39
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-30T19:37:58
2024-11-30T19:38:02
[{"name": "inteiro_teor", "dtype": "string"}, {"name": "url_download", "dtype": "string"}, {"name": "dataDecisao", "dtype": "timestamp[ns]"}, {"name": "dataPublicacao", "dtype": "timestamp[ns]"}, {"name": "decisao", "dtype": "string"}, {"name": "descricaoClasse", "dtype": "string"}, {"name": "ementa", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "jurisprudenciaCitada", "dtype": "string"}, {"name": "ministroRelator", "dtype": "string"}, {"name": "nomeOrgaoJulgador", "dtype": "string"}, {"name": "numeroProcesso", "dtype": "string"}, {"name": "referenciasLegislativas", "sequence": "string"}, {"name": "siglaClasse", "dtype": "string"}, {"name": "tipoDeDecisao", "dtype": "string"}, {"name": "titulo", "dtype": "string"}, {"name": "acordaosSimilares", "sequence": "string"}, {"name": "partes_lista_texto", "dtype": "string"}, {"name": "temaProcs", "sequence": "string"}, {"name": "inteiro_teor_regex", "dtype": "string"}, {"name": "NER", "struct": [{"name": "JURISPRUDENCIA", "sequence": "string"}, {"name": "LEGISLACAO", "sequence": "string"}, {"name": "LOCAL", "sequence": "string"}, {"name": "ORGANIZACAO", "sequence": "string"}, {"name": "PESSOA", "sequence": "string"}, {"name": "TEMPO", "sequence": "string"}]}]
{}
rookiewxy/test
default
0
39
["size_categories:10K<n<100K", "format:parquet", "modality:image", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-26T09:56:39
2024-11-26T10:36:15
[{"name": "image", "dtype": "image"}]
{}
NobodyExistsOnTheInternet/ConvoOrca3000Random
default
0
32
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-01-01T10:58:08
2024-01-01T10:58:12
[{"name": "conversations", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "evolutions", "sequence": "string"}]
{}
kingsleykim/habitat_videos_10_12_24_15_58_26
default
0
52
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-10T20:58:26
2024-12-10T20:59:12
[{"name": "video", "dtype": {"video": {"decode": false}}}, {"name": "model_output", "dtype": "string"}, {"name": "input_ids", "sequence": {"sequence": "int32"}}, {"name": "attention_mask", "sequence": {"sequence": "int8"}}, {"name": "pixel_values_videos", "sequence": {"sequence": "float32"}}, {"name": "video_grid_thw", "sequence": {"sequence": "int64"}}]
{}
LangAGI-Lab/Mind2Web-axtree-cleaned
default
0
6
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-09-10T07:39:40
2024-09-10T07:41:57
[{"name": "action_uid", "dtype": "string"}, {"name": "raw_html", "dtype": "string"}, {"name": "cleaned_html", "dtype": "string"}, {"name": "operation", "dtype": "string"}, {"name": "pos_candidates", "sequence": "string"}, {"name": "neg_candidates", "sequence": "string"}, {"name": "website", "dtype": "string"}, {"name": "domain", "dtype": "string"}, {"name": "subdomain", "dtype": "string"}, {"name": "annotation_id", "dtype": "string"}, {"name": "confirmed_task", "dtype": "string"}, {"name": "action_reprs", "sequence": "string"}, {"name": "target_action_index", "dtype": "string"}, {"name": "target_action_reprs", "dtype": "string"}, {"name": "accessibility_tree", "dtype": "string"}, {"name": "action", "dtype": "string"}, {"name": "original_action_repr", "dtype": "string"}, {"name": "original_pos_candidate", "struct": [{"name": "attributes", "struct": [{"name": "alt", "dtype": "string"}, {"name": "aria_description", "dtype": "string"}, {"name": "aria_label", "dtype": "string"}, {"name": "backend_node_id", "dtype": "string"}, {"name": "bounding_box_rect", "dtype": "string"}, {"name": "class", "dtype": "string"}, {"name": "data_pw_testid_buckeye_candidate", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "input_checked", "dtype": "string"}, {"name": "input_value", "dtype": "string"}, {"name": "is_clickable", "dtype": "string"}, {"name": "label", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "placeholder", "dtype": "string"}, {"name": "role", "dtype": "string"}, {"name": "text_value", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "backend_node_id", "dtype": "string"}, {"name": "is_original_target", "dtype": "bool"}, {"name": "is_top_level_target", "dtype": "bool"}, {"name": "tag", "dtype": "string"}]}, {"name": "match_type", "dtype": "string"}, {"name": "cleaned_accessibility_tree", "dtype": "string"}]
{}
kejian/sciriff-tulu-none-1000-template-1-summratio-0.75
default
0
47
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-12T04:50:32
2024-12-12T04:50:35
[{"name": "dataset", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}]
{}
fursov/gec_ner_val3
default
0
39
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-01-20T20:44:58
2024-01-20T20:45:03
[{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": "string"}]
{}
Nutanix/cpp_unit_tests_mistral7b_vs_mistral7b_finetuned_judge_gpt
default
0
32
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-09T22:11:56
2024-08-21T19:53:00
[{"name": "Code", "dtype": "string"}, {"name": "Unit Test_mistralv0.2-7b", "dtype": "string"}, {"name": "Unit Test_mistralv0.2-7b-finetuned", "dtype": "string"}, {"name": "Unit Test", "dtype": "string"}, {"name": "Winning Model", "dtype": "string"}, {"name": "Judgement", "dtype": "string"}]
{}
alihmaou/bdnb_2023-11.a_batiment_groupe_adresse_39
default
0
32
["size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-08-14T19:29:15
2024-08-14T19:29:16
[{"name": "batiment_groupe_id", "dtype": "string"}, {"name": "code_departement_insee", "dtype": "string"}, {"name": "cle_interop_adr_principale_ban", "dtype": "string"}, {"name": "libelle_adr_principale_ban", "dtype": "string"}, {"name": "nb_adresse_valid_ban", "dtype": "int64"}, {"name": "fiabilite_cr_adr_niv_1", "dtype": "string"}, {"name": "fiabilite_cr_adr_niv_2", "dtype": "string"}]
{}
ds-claudia/artificial_text_classification
default
0
82
["task_categories:text-classification", "language:en", "license:cc-by-4.0", "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "text-classification", "machine-generated-text", "human-generated-text"]
["en"]
"cc-by-4.0"
2024-12-17T22:02:57
2024-12-17T23:40:48
[{"name": "ID", "dtype": "int64"}, {"name": "Text", "dtype": "string"}, {"name": "label", "dtype": "int64"}]
{}
alvations/c4p0-x1-ja-en
default
0
33
["size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-23T10:22:35
2024-03-24T03:52:43
[{"name": "source", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "target_backto_source", "dtype": "string"}, {"name": "raw_target", "list": [{"name": "generated_text", "dtype": "string"}]}, {"name": "raw_target_backto_source", "list": [{"name": "generated_text", "dtype": "string"}]}, {"name": "prompt", "dtype": "string"}, {"name": "reverse_prompt", "dtype": "string"}, {"name": "source_langid", "dtype": "string"}, {"name": "target_langid", "dtype": "string"}, {"name": "target_backto_source_langid", "dtype": "string"}, {"name": "doc_id", "dtype": "int64"}, {"name": "sent_id", "dtype": "int64"}, {"name": "timestamp", "dtype": "timestamp[us]"}, {"name": "url", "dtype": "string"}, {"name": "doc_hash", "dtype": "string"}]
{}
Mihir1108/LLM4
default
0
33
["size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-10-09T07:08:58
2023-10-09T07:09:00
[{"name": "formate_data", "dtype": "string"}]
{}
gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
default
0
39
["size_categories:100K<n<1M", "format:parquet", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-11-12T17:46:58
2024-11-12T17:47:20
[{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}, {"name": "special_tokens_mask", "sequence": "int8"}, {"name": "lda_lables", "sequence": "float64"}]
{}
AhmedBadawy11/UAE17000
default
0
268
["size_categories:10K<n<100K", "modality:audio", "modality:text", "region:us"]
null
null
2024-12-04T19:33:52
2024-12-04T20:50:30
[{"name": "audio", "dtype": "audio"}, {"name": "text", "dtype": "string"}]
{}
jpalgo/libri-tts-tags-v1
default
0
15
["size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us"]
null
null
2025-01-16T09:49:39
2025-01-16T09:51:13
[{"name": "file", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "chapter_id", "dtype": "int64"}, {"name": "id", "dtype": "string"}, {"name": "input_features", "sequence": {"sequence": "float32"}}, {"name": "labels", "sequence": "int64"}, {"name": "gender", "dtype": "string"}, {"name": "speaker_id", "dtype": "string"}, {"name": "utterance_pitch_mean", "dtype": "float32"}, {"name": "utterance_pitch_std", "dtype": "float32"}, {"name": "snr", "dtype": "float64"}, {"name": "c50", "dtype": "float64"}, {"name": "speaking_rate", "dtype": "float64"}, {"name": "phonemes", "dtype": "string"}, {"name": "stoi", "dtype": "float64"}, {"name": "si-sdr", "dtype": "float64"}, {"name": "pesq", "dtype": "float64"}]
{}
selfcorrexp2/llama31_14w_wrong_10w_corr_20k_test
default
0
34
["size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-12-26T18:29:10
2024-12-26T18:29:15
[{"name": "idx", "dtype": "int64"}, {"name": "first_round", "dtype": "bool"}, {"name": "gt", "dtype": "string"}, {"name": "rewards", "sequence": "bool"}, {"name": "my_solu", "sequence": "string"}, {"name": "flag", "dtype": "bool"}, {"name": "turn", "dtype": "int64"}, {"name": "conversations", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "question", "dtype": "string"}, {"name": "gt_cot", "dtype": "string"}, {"name": "level", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "solution", "dtype": "string"}, {"name": "pred", "sequence": "string"}, {"name": "code", "sequence": "string"}]
{}
dewithsan/secop_corpus_clean
default
0
29
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-03-03T18:20:23
2024-03-03T18:20:29
[{"name": "id_doc", "dtype": "string"}, {"name": "doc_text", "dtype": "string"}]
{}
JetBrains-Research/ts_files
default
0
35
["size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2024-02-23T15:08:56
2024-02-23T15:09:07
[{"name": "text", "dtype": "string"}]
{}
dmayhem93/self-critiquing-base-test
default
0
30
["size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us"]
null
null
2023-04-07T17:29:30
2023-04-07T23:48:49
[{"name": "id", "dtype": "string"}, {"name": "split", "dtype": "string"}, {"name": "time", "dtype": "float64"}, {"name": "labeler", "dtype": "string"}, {"name": "is_topic_based_summarization", "dtype": "bool"}, {"name": "prompt", "dtype": "string"}, {"name": "response", "dtype": "string"}]
{}