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deberta-v3-base-tasksource-nli

Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3-base
deberta-v3
deberta
nli
natural-language-inference
multitask
multi-task
pipeline
extreme-multi-task
extreme-mtl
tasksource
zero-shot
rlhf
Eval Results
Inference Endpoints
Model card Files Community
9
deberta-v3-base-tasksource-nli / config.json
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{
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"architectures": [
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"id2label": {
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"relative_attention": true,
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"tasks": [
"babi_nli/counting",
"babi_nli/indefinite-knowledge",
"babi_nli/simple-negation",
"babi_nli/three-arg-relations",
"babi_nli/basic-induction",
"babi_nli/time-reasoning",
"babi_nli/compound-coreference",
"babi_nli/path-finding",
"babi_nli/positional-reasoning",
"babi_nli/conjunction",
"babi_nli/size-reasoning",
"babi_nli/yes-no-questions",
"babi_nli/basic-coreference",
"babi_nli/two-supporting-facts",
"babi_nli/lists-sets",
"babi_nli/two-arg-relations",
"babi_nli/three-supporting-facts",
"babi_nli/basic-deduction",
"babi_nli/single-supporting-fact",
"anli/a1",
"anli/a2",
"anli/a3",
"sick/label",
"sick/relatedness",
"sick/entailment_AB",
"sick/entailment_BA",
"snli",
"scitail/snli_format",
"hans",
"WANLI",
"recast/recast_kg_relations",
"recast/recast_puns",
"recast/recast_factuality",
"recast/recast_megaveridicality",
"recast/recast_verbcorner",
"recast/recast_verbnet",
"recast/recast_ner",
"recast/recast_sentiment",
"probability_words_nli/usnli",
"probability_words_nli/reasoning_1hop",
"probability_words_nli/reasoning_2hop",
"nan-nli/joey234--nan-nli",
"nli_fever",
"breaking_nli",
"conj_nli",
"fracas",
"dialogue_nli",
"mpe",
"dnc",
"gpt3_nli",
"recast_white/fnplus",
"recast_white/sprl",
"recast_white/dpr",
"joci",
"contrast_nli",
"robust_nli/IS_CS",
"robust_nli/LI_LI",
"robust_nli/ST_WO",
"robust_nli/PI_SP",
"robust_nli/PI_CD",
"robust_nli/ST_SE",
"robust_nli/ST_NE",
"robust_nli/ST_LM",
"robust_nli_is_sd",
"robust_nli_li_ts",
"gen_debiased_nli/snli_seq_z",
"gen_debiased_nli/snli_z_aug",
"gen_debiased_nli/snli_par_z",
"gen_debiased_nli/mnli_par_z",
"gen_debiased_nli/mnli_z_aug",
"gen_debiased_nli/mnli_seq_z",
"add_one_rte",
"imppres/presupposition_cleft_uniqueness/presupposition",
"imppres/presupposition_possessed_definites_uniqueness/presupposition",
"imppres/presupposition_possessed_definites_existence/presupposition",
"imppres/presupposition_only_presupposition/presupposition",
"imppres/presupposition_all_n_presupposition/presupposition",
"imppres/presupposition_both_presupposition/presupposition",
"imppres/presupposition_change_of_state/presupposition",
"imppres/presupposition_cleft_existence/presupposition",
"imppres/presupposition_question_presupposition/presupposition",
"imppres/implicature_modals/prag",
"imppres/implicature_numerals_10_100/prag",
"imppres/implicature_numerals_2_3/prag",
"imppres/implicature_gradable_adjective/prag",
"imppres/implicature_quantifiers/prag",
"imppres/implicature_gradable_verb/prag",
"imppres/implicature_connectives/prag",
"imppres/implicature_gradable_adjective/log",
"imppres/implicature_gradable_verb/log",
"imppres/implicature_numerals_2_3/log",
"imppres/implicature_numerals_10_100/log",
"imppres/implicature_modals/log",
"imppres/implicature_quantifiers/log",
"imppres/implicature_connectives/log",
"glue_diagnostics/diagnostics",
"hlgd",
"paws/labeled_final",
"paws/labeled_swap",
"quora",
"medical_questions_pairs",
"conll2003/pos_tags",
"conll2003/chunk_tags",
"conll2003/ner_tags",
"hh-rlhf",
"model-written-evals",
"truthful_qa/multiple_choice",
"fig-qa",
"bigbench/fantasy_reasoning",
"bigbench/nonsense_words_grammar",
"bigbench/analytic_entailment",
"bigbench/logic_grid_puzzle",
"bigbench/geometric_shapes",
"bigbench/key_value_maps",
"bigbench/analogical_similarity",
"bigbench/metaphor_understanding",
"bigbench/metaphor_boolean",
"bigbench/ruin_names",
"bigbench/cs_algorithms",
"bigbench/physical_intuition",
"bigbench/mnist_ascii",
"bigbench/moral_permissibility",
"bigbench/emoji_movie",
"bigbench/snarks",
"bigbench/timedial",
"bigbench/dark_humor_detection",
"bigbench/gre_reading_comprehension",
"bigbench/empirical_judgments",
"bigbench/causal_judgment",
"bigbench/fact_checker",
"bigbench/logical_fallacy_detection",
"bigbench/identify_math_theorems",
"bigbench/dyck_languages",
"bigbench/winowhy",
"bigbench/logical_sequence",
"bigbench/strategyqa",
"bigbench/unit_interpretation",
"bigbench/authorship_verification",
"bigbench/undo_permutation",
"bigbench/epistemic_reasoning",
"bigbench/human_organs_senses",
"bigbench/misconceptions",
"bigbench/international_phonetic_alphabet_nli",
"bigbench/identify_odd_metaphor",
"bigbench/mathematical_induction",
"bigbench/odd_one_out",
"bigbench/reasoning_about_colored_objects",
"bigbench/strange_stories",
"bigbench/evaluating_information_essentiality",
"bigbench/figure_of_speech_detection",
"bigbench/english_proverbs",
"bigbench/general_knowledge",
"bigbench/tracking_shuffled_objects",
"bigbench/physics",
"bigbench/anachronisms",
"bigbench/simple_ethical_questions",
"bigbench/logical_args",
"bigbench/suicide_risk",
"bigbench/sentence_ambiguity",
"bigbench/temporal_sequences",
"bigbench/penguins_in_a_table",
"bigbench/sports_understanding",
"bigbench/hyperbaton",
"bigbench/code_line_description",
"bigbench/question_selection",
"bigbench/disambiguation_qa",
"bigbench/date_understanding",
"bigbench/play_dialog_same_or_different",
"bigbench/salient_translation_error_detection",
"bigbench/irony_identification",
"bigbench/emojis_emotion_prediction",
"bigbench/hindu_knowledge",
"bigbench/conceptual_combinations",
"bigbench/implicatures",
"bigbench/movie_dialog_same_or_different",
"bigbench/social_support",
"bigbench/presuppositions_as_nli",
"bigbench/vitaminc_fact_verification",
"bigbench/hhh_alignment",
"bigbench/implicit_relations",
"bigbench/bbq_lite_json",
"bigbench/phrase_relatedness",
"bigbench/logical_deduction",
"bigbench/discourse_marker_prediction",
"bigbench/movie_recommendation",
"bigbench/real_or_fake_text",
"bigbench/formal_fallacies_syllogisms_negation",
"bigbench/crass_ai",
"blimp/inchoative",
"blimp/principle_A_c_command",
"blimp/matrix_question_npi_licensor_present",
"blimp/wh_questions_subject_gap_long_distance",
"blimp/sentential_subject_island",
"blimp/existential_there_quantifiers_2",
"blimp/sentential_negation_npi_scope",
"blimp/complex_NP_island",
"blimp/principle_A_reconstruction",
"blimp/animate_subject_passive",
"blimp/tough_vs_raising_1",
"blimp/wh_vs_that_with_gap",
"blimp/principle_A_domain_2",
"blimp/npi_present_1",
"blimp/wh_vs_that_with_gap_long_distance",
"blimp/superlative_quantifiers_1",
"blimp/npi_present_2",
"blimp/wh_questions_object_gap",
"blimp/coordinate_structure_constraint_complex_left_branch",
"blimp/coordinate_structure_constraint_object_extraction",
"blimp/left_branch_island_echo_question",
"blimp/drop_argument",
"cos_e/v1.0",
"cosmos_qa",
"dream",
"openbookqa",
"qasc",
"quartz",
"quail",
"head_qa/en",
"sciq",
"social_i_qa",
"wiki_hop",
"wiqa",
"piqa",
"hellaswag",
"super_glue/copa",
"art",
"hendrycks_test/moral_disputes",
"hendrycks_test/moral_scenarios",
"hendrycks_test/nutrition",
"hendrycks_test/philosophy",
"hendrycks_test/prehistory",
"hendrycks_test/professional_accounting",
"hendrycks_test/professional_law",
"hendrycks_test/world_religions",
"hendrycks_test/professional_psychology",
"hendrycks_test/public_relations",
"hendrycks_test/security_studies",
"hendrycks_test/sociology",
"hendrycks_test/us_foreign_policy",
"hendrycks_test/virology",
"hendrycks_test/miscellaneous",
"hendrycks_test/professional_medicine",
"hendrycks_test/medical_genetics",
"hendrycks_test/college_mathematics",
"hendrycks_test/management",
"hendrycks_test/high_school_computer_science",
"hendrycks_test/astronomy",
"hendrycks_test/high_school_chemistry",
"hendrycks_test/high_school_biology",
"hendrycks_test/global_facts",
"hendrycks_test/formal_logic",
"hendrycks_test/elementary_mathematics",
"hendrycks_test/high_school_european_history",
"hendrycks_test/electrical_engineering",
"hendrycks_test/conceptual_physics",
"hendrycks_test/computer_security",
"hendrycks_test/college_physics",
"hendrycks_test/college_medicine",
"hendrycks_test/college_computer_science",
"hendrycks_test/college_chemistry",
"hendrycks_test/college_biology",
"hendrycks_test/econometrics",
"hendrycks_test/clinical_knowledge",
"hendrycks_test/anatomy",
"hendrycks_test/marketing",
"hendrycks_test/machine_learning",
"hendrycks_test/logical_fallacies",
"hendrycks_test/jurisprudence",
"hendrycks_test/international_law",
"hendrycks_test/human_sexuality",
"hendrycks_test/human_aging",
"hendrycks_test/high_school_world_history",
"hendrycks_test/abstract_algebra",
"hendrycks_test/high_school_us_history",
"hendrycks_test/high_school_psychology",
"hendrycks_test/high_school_physics",
"hendrycks_test/high_school_microeconomics",
"hendrycks_test/high_school_mathematics",
"hendrycks_test/high_school_macroeconomics",
"hendrycks_test/high_school_government_and_politics",
"hendrycks_test/high_school_geography",
"hendrycks_test/high_school_statistics",
"hendrycks_test/business_ethics",
"winogrande/winogrande_xl",
"codah/codah",
"ai2_arc/ARC-Challenge/challenge",
"ai2_arc/ARC-Easy/challenge",
"definite_pronoun_resolution",
"swag",
"math_qa",
"utilitarianism",
"TuringBench",
"trec",
"vitaminc/tals--vitaminc",
"hope_edi/english",
"rumoureval_2019/RumourEval2019",
"ethos/binary",
"ethos/multilabel",
"glue/cola",
"glue/sst2",
"glue/mrpc",
"glue/qqp",
"glue/stsb",
"glue/mnli",
"glue/qnli",
"glue/rte",
"glue/wnli",
"super_glue/boolq",
"super_glue/cb",
"super_glue/multirc",
"super_glue/wic",
"super_glue/axg",
"tweet_eval/stance_feminist",
"tweet_eval/stance_atheism",
"tweet_eval/stance_hillary",
"tweet_eval/stance_abortion",
"tweet_eval/sentiment",
"tweet_eval/offensive",
"tweet_eval/stance_climate",
"tweet_eval/irony",
"tweet_eval/emotion",
"tweet_eval/emoji",
"tweet_eval/hate",
"discovery/discovery",
"pragmeval/switchboard",
"pragmeval/squinky-informativeness",
"pragmeval/emobank-arousal",
"pragmeval/emobank-dominance",
"pragmeval/emobank-valence",
"pragmeval/mrda",
"pragmeval/verifiability",
"pragmeval/squinky-implicature",
"pragmeval/squinky-formality",
"pragmeval/gum",
"pragmeval/emergent",
"pragmeval/persuasiveness-premisetype",
"pragmeval/pdtb",
"pragmeval/persuasiveness-eloquence",
"pragmeval/persuasiveness-specificity",
"pragmeval/persuasiveness-strength",
"pragmeval/sarcasm",
"pragmeval/stac",
"pragmeval/persuasiveness-claimtype",
"pragmeval/persuasiveness-relevance",
"lex_glue/eurlex",
"lex_glue/scotus",
"lex_glue/ledgar",
"lex_glue/unfair_tos",
"lex_glue/case_hold",
"imdb",
"rotten_tomatoes",
"ag_news",
"yelp_review_full/yelp_review_full",
"financial_phrasebank/sentences_allagree",
"poem_sentiment",
"dbpedia_14/dbpedia_14",
"amazon_polarity/amazon_polarity",
"app_reviews",
"hate_speech18",
"sms_spam",
"humicroedit/subtask-1",
"humicroedit/subtask-2",
"snips_built_in_intents",
"banking77",
"hate_speech_offensive",
"hyperpartisan_news_detection/byarticle",
"hyperpartisan_news_detection/bypublisher",
"go_emotions/simplified",
"scicite",
"liar",
"lexical_relation_classification/ROOT09",
"lexical_relation_classification/EVALution",
"lexical_relation_classification/CogALexV",
"lexical_relation_classification/BLESS",
"lexical_relation_classification/K&H+N",
"linguisticprobing/coordination_inversion",
"linguisticprobing/odd_man_out",
"linguisticprobing/word_content",
"linguisticprobing/obj_number",
"linguisticprobing/past_present",
"linguisticprobing/tree_depth",
"linguisticprobing/sentence_length",
"linguisticprobing/top_constituents",
"linguisticprobing/bigram_shift",
"linguisticprobing/subj_number",
"crowdflower/sentiment_nuclear_power",
"crowdflower/tweet_global_warming",
"crowdflower/airline-sentiment",
"crowdflower/economic-news",
"crowdflower/political-media-audience",
"crowdflower/political-media-bias",
"crowdflower/political-media-message",
"crowdflower/text_emotion",
"crowdflower/corporate-messaging",
"ethics/commonsense",
"ethics/deontology",
"ethics/justice",
"ethics/virtue",
"emo/emo2019",
"google_wellformed_query",
"tweets_hate_speech_detection",
"adv_glue/adv_sst2",
"adv_glue/adv_qqp",
"adv_glue/adv_mnli",
"adv_glue/adv_mnli_mismatched",
"adv_glue/adv_qnli",
"adv_glue/adv_rte",
"has_part",
"wnut_17/wnut_17",
"ncbi_disease/ncbi_disease",
"acronym_identification",
"jnlpba/jnlpba",
"species_800/species_800",
"ontonotes_english/SpeedOfMagic--ontonotes_english",
"blog_authorship_corpus/gender",
"blog_authorship_corpus/age",
"blog_authorship_corpus/horoscope",
"blog_authorship_corpus/job",
"open_question_type",
"health_fact",
"commonsense_qa",
"mc_taco",
"ade_corpus_v2/Ade_corpus_v2_classification",
"discosense",
"circa",
"code_x_glue_cc_defect_detection",
"code_x_glue_cc_clone_detection_big_clone_bench",
"code_x_glue_cc_code_refinement/medium",
"EffectiveFeedbackStudentWriting",
"promptSentiment",
"promptNLI",
"promptSpoke",
"promptProficiency",
"promptGrammar",
"promptCoherence",
"phrase_similarity",
"scientific-exaggeration-detection",
"quarel",
"fever-evidence-related/mwong--fever-related",
"numer_sense",
"dynasent/dynabench.dynasent.r1.all/r1",
"dynasent/dynabench.dynasent.r2.all/r2",
"Sarcasm_News_Headline",
"sem_eval_2010_task_8"
],
"torch_dtype": "float32",
"transformers_version": "4.25.1",
"type_vocab_size": 0,
"vocab_size": 128100
}