| { | |
| "_name_or_path": "sileod/deberta-v3-base-tasksource-nli", | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
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| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "AI", | |
| "1": "AI Retail", | |
| "2": "AR", | |
| "3": "Advertising", | |
| "4": "Alcohol", | |
| "5": "Analytics", | |
| "6": "App", | |
| "7": "Automation SaaS", | |
| "8": "B2B", | |
| "9": "Big Data Analytics", | |
| "10": "Big Data Software", | |
| "11": "Biotech", | |
| "12": "Biotechnology Healthcare", | |
| "13": "Cannabis", | |
| "14": "Cannabis Healthcare", | |
| "15": "Cloud", | |
| "16": "Coding", | |
| "17": "Coffee", | |
| "18": "Consumer App", | |
| "19": "Customer Service IT", | |
| "20": "Cybersecurity", | |
| "21": "Data Analytics", | |
| "22": "Data Management", | |
| "23": "E-commerce", | |
| "24": "Education", | |
| "25": "Enterprise", | |
| "26": "Enterprise Software", | |
| "27": "Enterprise Software HR", | |
| "28": "Enterprise Tech VR", | |
| "29": "FinTech", | |
| "30": "FinTech Healthcare InsurTech", | |
| "31": "FinTech Healthcare Payments", | |
| "32": "FinTech Payments", | |
| "33": "Finance", | |
| "34": "Finance Stock Exchanges", | |
| "35": "Food & Beverages Mobile Apps", | |
| "36": "Food Fashion", | |
| "37": "Hardware", | |
| "38": "Healthcare", | |
| "39": "IT", | |
| "40": "Legal Tech", | |
| "41": "Logistics", | |
| "42": "Media", | |
| "43": "Networking", | |
| "44": "Online Learning", | |
| "45": "Payments", | |
| "46": "Productivity Cloud", | |
| "47": "Productivity Collaboration", | |
| "48": "Proptech", | |
| "49": "Real Estate", | |
| "50": "Retail", | |
| "51": "Security", | |
| "52": "Social Media", | |
| "53": "Tech", | |
| "54": "Template", | |
| "55": "Transportation", | |
| "56": "Venture Capital Retail", | |
| "57": "Virtual Reality", | |
| "58": "eCommerce" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "AI": 0, | |
| "AI Retail": 1, | |
| "AR": 2, | |
| "Advertising": 3, | |
| "Alcohol": 4, | |
| "Analytics": 5, | |
| "App": 6, | |
| "Automation SaaS": 7, | |
| "B2B": 8, | |
| "Big Data Analytics": 9, | |
| "Big Data Software": 10, | |
| "Biotech": 11, | |
| "Biotechnology Healthcare": 12, | |
| "Cannabis": 13, | |
| "Cannabis Healthcare": 14, | |
| "Cloud": 15, | |
| "Coding": 16, | |
| "Coffee": 17, | |
| "Consumer App": 18, | |
| "Customer Service IT": 19, | |
| "Cybersecurity": 20, | |
| "Data Analytics": 21, | |
| "Data Management": 22, | |
| "E-commerce": 23, | |
| "Education": 24, | |
| "Enterprise": 25, | |
| "Enterprise Software": 26, | |
| "Enterprise Software HR": 27, | |
| "Enterprise Tech VR": 28, | |
| "FinTech": 29, | |
| "FinTech Healthcare InsurTech": 30, | |
| "FinTech Healthcare Payments": 31, | |
| "FinTech Payments": 32, | |
| "Finance": 33, | |
| "Finance Stock Exchanges": 34, | |
| "Food & Beverages Mobile Apps": 35, | |
| "Food Fashion": 36, | |
| "Hardware": 37, | |
| "Healthcare": 38, | |
| "IT": 39, | |
| "Legal Tech": 40, | |
| "Logistics": 41, | |
| "Media": 42, | |
| "Networking": 43, | |
| "Online Learning": 44, | |
| "Payments": 45, | |
| "Productivity Cloud": 46, | |
| "Productivity Collaboration": 47, | |
| "Proptech": 48, | |
| "Real Estate": 49, | |
| "Retail": 50, | |
| "Security": 51, | |
| "Social Media": 52, | |
| "Tech": 53, | |
| "Template": 54, | |
| "Transportation": 55, | |
| "Venture Capital Retail": 56, | |
| "Virtual Reality": 57, | |
| "eCommerce": 58 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 768, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "tasks": [ | |
| "glue/mnli", | |
| "glue/qnli", | |
| "glue/rte", | |
| "glue/wnli", | |
| "glue/mrpc", | |
| "glue/qqp", | |
| "glue/stsb", | |
| "super_glue/boolq", | |
| "super_glue/cb", | |
| "super_glue/multirc", | |
| "super_glue/wic", | |
| "super_glue/axg", | |
| "anli/a1", | |
| "anli/a2", | |
| "anli/a3", | |
| "sick/label", | |
| "sick/relatedness", | |
| "sick/entailment_AB", | |
| "snli", | |
| "scitail/snli_format", | |
| "hans", | |
| "WANLI", | |
| "recast/recast_megaveridicality", | |
| "recast/recast_ner", | |
| "recast/recast_kg_relations", | |
| "recast/recast_puns", | |
| "recast/recast_factuality", | |
| "recast/recast_verbnet", | |
| "recast/recast_verbcorner", | |
| "recast/recast_sentiment", | |
| "probability_words_nli/reasoning_2hop", | |
| "probability_words_nli/reasoning_1hop", | |
| "probability_words_nli/usnli", | |
| "nan-nli/joey234--nan-nli", | |
| "nli_fever", | |
| "breaking_nli", | |
| "conj_nli", | |
| "fracas", | |
| "dialogue_nli", | |
| "mpe", | |
| "dnc", | |
| "recast_white/fnplus", | |
| "recast_white/sprl", | |
| "recast_white/dpr", | |
| "joci", | |
| "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", | |
| "add_one_rte", | |
| "imppres/implicature_modals/log", | |
| "imppres/implicature_connectives/log", | |
| "imppres/implicature_quantifiers/log", | |
| "imppres/implicature_gradable_adjective/log", | |
| "imppres/implicature_numerals_2_3/log", | |
| "imppres/implicature_numerals_10_100/log", | |
| "imppres/implicature_gradable_verb/log", | |
| "glue_diagnostics/diagnostics", | |
| "hlgd", | |
| "paws/labeled_final", | |
| "paws/labeled_swap", | |
| "medical_questions_pairs", | |
| "conll2003/pos_tags", | |
| "conll2003/chunk_tags", | |
| "conll2003/ner_tags", | |
| "hh-rlhf", | |
| "model-written-evals", | |
| "truthful_qa/multiple_choice", | |
| "fig-qa", | |
| "bigbench/tracking_shuffled_objects", | |
| "bigbench/movie_recommendation", | |
| "bigbench/key_value_maps", | |
| "bigbench/discourse_marker_prediction", | |
| "bigbench/human_organs_senses", | |
| "bigbench/physical_intuition", | |
| "bigbench/presuppositions_as_nli", | |
| "bigbench/undo_permutation", | |
| "bigbench/analytic_entailment", | |
| "bigbench/abstract_narrative_understanding", | |
| "bigbench/general_knowledge", | |
| "bigbench/dark_humor_detection", | |
| "bigbench/evaluating_information_essentiality", | |
| "bigbench/social_support", | |
| "bigbench/logical_sequence", | |
| "bigbench/understanding_fables", | |
| "bigbench/dyck_languages", | |
| "bigbench/date_understanding", | |
| "bigbench/salient_translation_error_detection", | |
| "bigbench/authorship_verification", | |
| "bigbench/logical_args", | |
| "bigbench/international_phonetic_alphabet_nli", | |
| "bigbench/mathematical_induction", | |
| "bigbench/causal_judgment", | |
| "bigbench/logic_grid_puzzle", | |
| "bigbench/suicide_risk", | |
| "bigbench/symbol_interpretation", | |
| "bigbench/bbq_lite_json", | |
| "bigbench/color", | |
| "bigbench/english_proverbs", | |
| "bigbench/navigate", | |
| "bigbench/unit_interpretation", | |
| "bigbench/logical_fallacy_detection", | |
| "bigbench/metaphor_boolean", | |
| "bigbench/arithmetic", | |
| "bigbench/vitaminc_fact_verification", | |
| "bigbench/strategyqa", | |
| "bigbench/fantasy_reasoning", | |
| "bigbench/ruin_names", | |
| "bigbench/code_line_description", | |
| "bigbench/timedial", | |
| "bigbench/hhh_alignment", | |
| "bigbench/emojis_emotion_prediction", | |
| "bigbench/known_unknowns", | |
| "bigbench/question_selection", | |
| "bigbench/hyperbaton", | |
| "bigbench/analogical_similarity", | |
| "bigbench/temporal_sequences", | |
| "bigbench/irony_identification", | |
| "bigbench/winowhy", | |
| "bigbench/novel_concepts", | |
| "bigbench/cifar10_classification", | |
| "bigbench/logical_deduction", | |
| "bigbench/penguins_in_a_table", | |
| "bigbench/phrase_relatedness", | |
| "bigbench/checkmate_in_one", | |
| "bigbench/crash_blossom", | |
| "bigbench/similarities_abstraction", | |
| "bigbench/implicatures", | |
| "bigbench/fact_checker", | |
| "bigbench/reasoning_about_colored_objects", | |
| "bigbench/physics", | |
| "bigbench/elementary_math_qa", | |
| "bigbench/entailed_polarity", | |
| "bigbench/riddle_sense", | |
| "bigbench/mnist_ascii", | |
| "bigbench/odd_one_out", | |
| "bigbench/movie_dialog_same_or_different", | |
| "bigbench/metaphor_understanding", | |
| "bigbench/play_dialog_same_or_different", | |
| "bigbench/cause_and_effect", | |
| "bigbench/anachronisms", | |
| "bigbench/real_or_fake_text", | |
| "bigbench/conceptual_combinations", | |
| "bigbench/emoji_movie", | |
| "bigbench/cs_algorithms", | |
| "bigbench/social_iqa", | |
| "bigbench/strange_stories", | |
| "bigbench/misconceptions", | |
| "bigbench/crass_ai", | |
| "bigbench/disambiguation_qa", | |
| "bigbench/formal_fallacies_syllogisms_negation", | |
| "bigbench/sports_understanding", | |
| "bigbench/moral_permissibility", | |
| "bigbench/simple_ethical_questions", | |
| "bigbench/snarks", | |
| "bigbench/geometric_shapes", | |
| "bigbench/implicit_relations", | |
| "bigbench/identify_math_theorems", | |
| "bigbench/nonsense_words_grammar", | |
| "bigbench/sentence_ambiguity", | |
| "bigbench/contextual_parametric_knowledge_conflicts", | |
| "bigbench/hindu_knowledge", | |
| "bigbench/empirical_judgments", | |
| "bigbench/identify_odd_metaphor", | |
| "bigbench/goal_step_wikihow", | |
| "bigbench/gre_reading_comprehension", | |
| "bigbench/figure_of_speech_detection", | |
| "bigbench/intent_recognition", | |
| "bigbench/epistemic_reasoning", | |
| "cos_e/v1.0", | |
| "cosmos_qa", | |
| "dream", | |
| "openbookqa", | |
| "qasc", | |
| "quartz", | |
| "quail", | |
| "head_qa/en", | |
| "sciq", | |
| "social_i_qa", | |
| "wiki_hop/original", | |
| "wiqa", | |
| "piqa", | |
| "hellaswag", | |
| "super_glue/copa", | |
| "balanced-copa", | |
| "e-CARE", | |
| "art", | |
| "winogrande/winogrande_xl", | |
| "codah/codah", | |
| "ai2_arc/ARC-Challenge/challenge", | |
| "ai2_arc/ARC-Easy/challenge", | |
| "definite_pronoun_resolution", | |
| "swag/regular", | |
| "math_qa", | |
| "glue/cola", | |
| "glue/sst2", | |
| "utilitarianism", | |
| "amazon_counterfactual/en", | |
| "insincere-questions", | |
| "toxic_conversations", | |
| "TuringBench", | |
| "trec", | |
| "vitaminc/tals--vitaminc", | |
| "hope_edi/english", | |
| "rumoureval_2019/RumourEval2019", | |
| "ethos/binary", | |
| "ethos/multilabel", | |
| "tweet_eval/hate", | |
| "tweet_eval/stance_climate", | |
| "tweet_eval/irony", | |
| "tweet_eval/stance_abortion", | |
| "tweet_eval/sentiment", | |
| "tweet_eval/offensive", | |
| "tweet_eval/stance_feminist", | |
| "tweet_eval/stance_atheism", | |
| "tweet_eval/stance_hillary", | |
| "tweet_eval/emoji", | |
| "tweet_eval/emotion", | |
| "discovery/discovery", | |
| "pragmeval/emobank-dominance", | |
| "pragmeval/emobank-arousal", | |
| "pragmeval/emobank-valence", | |
| "pragmeval/squinky-formality", | |
| "pragmeval/squinky-implicature", | |
| "pragmeval/squinky-informativeness", | |
| "pragmeval/switchboard", | |
| "pragmeval/mrda", | |
| "pragmeval/verifiability", | |
| "pragmeval/emergent", | |
| "pragmeval/pdtb", | |
| "pragmeval/gum", | |
| "pragmeval/persuasiveness-premisetype", | |
| "pragmeval/persuasiveness-eloquence", | |
| "pragmeval/persuasiveness-relevance", | |
| "pragmeval/persuasiveness-specificity", | |
| "pragmeval/persuasiveness-strength", | |
| "pragmeval/sarcasm", | |
| "pragmeval/stac", | |
| "pragmeval/persuasiveness-claimtype", | |
| "silicone/dyda_da", | |
| "silicone/dyda_e", | |
| "silicone/sem", | |
| "silicone/meld_s", | |
| "silicone/meld_e", | |
| "silicone/maptask", | |
| "silicone/iemocap", | |
| "silicone/oasis", | |
| "lex_glue/eurlex", | |
| "lex_glue/scotus", | |
| "lex_glue/ledgar", | |
| "lex_glue/unfair_tos", | |
| "lex_glue/case_hold", | |
| "language-identification", | |
| "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", | |
| "hate_speech_offensive", | |
| "yahoo_answers_topics", | |
| "stackoverflow-questions", | |
| "hyperpartisan_news", | |
| "sciie", | |
| "citation_intent", | |
| "go_emotions/simplified", | |
| "scicite", | |
| "liar", | |
| "lexical_relation_classification/BLESS", | |
| "lexical_relation_classification/EVALution", | |
| "lexical_relation_classification/K&H+N", | |
| "lexical_relation_classification/ROOT09", | |
| "lexical_relation_classification/CogALexV", | |
| "linguisticprobing/bigram_shift", | |
| "linguisticprobing/odd_man_out", | |
| "linguisticprobing/coordination_inversion", | |
| "linguisticprobing/tree_depth", | |
| "linguisticprobing/top_constituents", | |
| "linguisticprobing/sentence_length", | |
| "linguisticprobing/past_present", | |
| "linguisticprobing/obj_number", | |
| "linguisticprobing/subj_number", | |
| "crowdflower/sentiment_nuclear_power", | |
| "crowdflower/political-media-bias", | |
| "crowdflower/text_emotion", | |
| "crowdflower/political-media-message", | |
| "crowdflower/political-media-audience", | |
| "crowdflower/economic-news", | |
| "crowdflower/corporate-messaging", | |
| "crowdflower/airline-sentiment", | |
| "crowdflower/tweet_global_warming", | |
| "ethics/commonsense", | |
| "ethics/deontology", | |
| "ethics/justice", | |
| "ethics/virtue", | |
| "emo/emo2019", | |
| "google_wellformed_query", | |
| "tweets_hate_speech_detection", | |
| "has_part", | |
| "wnut_17/wnut_17", | |
| "ncbi_disease/ncbi_disease", | |
| "acronym_identification", | |
| "jnlpba/jnlpba", | |
| "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", | |
| "EffectiveFeedbackStudentWriting", | |
| "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", | |
| "auditor_review/demo-org--auditor_review", | |
| "medmcqa", | |
| "Dynasent_Disagreement", | |
| "Politeness_Disagreement", | |
| "SBIC_Disagreement", | |
| "SChem_Disagreement", | |
| "Dilemmas_Disagreement", | |
| "logiqa", | |
| "wiki_qa", | |
| "cycic_classification", | |
| "cycic_multiplechoice", | |
| "sts-companion", | |
| "commonsense_qa_2.0", | |
| "lingnli", | |
| "monotonicity-entailment", | |
| "arct", | |
| "scinli", | |
| "naturallogic", | |
| "onestop_qa", | |
| "moral_stories/full", | |
| "prost", | |
| "dynahate", | |
| "syntactic-augmentation-nli", | |
| "autotnli", | |
| "CONDAQA", | |
| "webgpt_comparisons", | |
| "synthetic-instruct-gptj-pairwise", | |
| "scruples", | |
| "wouldyourather", | |
| "attempto-nli", | |
| "defeasible-nli/atomic", | |
| "defeasible-nli/snli", | |
| "help-nli", | |
| "nli-veridicality-transitivity", | |
| "natural-language-satisfiability", | |
| "lonli", | |
| "dadc-limit-nli", | |
| "FLUTE", | |
| "strategy-qa", | |
| "summarize_from_feedback/comparisons", | |
| "folio", | |
| "tomi-nli", | |
| "avicenna", | |
| "SHP", | |
| "MedQA-USMLE-4-options-hf", | |
| "wikimedqa/medwiki", | |
| "cicero", | |
| "CREAK", | |
| "mutual", | |
| "NeQA", | |
| "quote-repetition", | |
| "redefine-math", | |
| "puzzte", | |
| "implicatures", | |
| "race/high", | |
| "race/middle", | |
| "race-c", | |
| "spartqa-yn", | |
| "spartqa-mchoice", | |
| "temporal-nli", | |
| "riddle_sense", | |
| "clcd-english", | |
| "twentyquestions", | |
| "reclor", | |
| "counterfactually-augmented-imdb", | |
| "counterfactually-augmented-snli", | |
| "cnli", | |
| "boolq-natural-perturbations", | |
| "acceptability-prediction", | |
| "equate", | |
| "ScienceQA_text_only", | |
| "ekar_english", | |
| "implicit-hate-stg1", | |
| "chaos-mnli-ambiguity", | |
| "headline_cause/en_simple", | |
| "logiqa-2.0-nli", | |
| "oasst1_dense_flat/quality", | |
| "oasst1_dense_flat/toxicity", | |
| "oasst1_dense_flat/helpfulness", | |
| "PARARULE-Plus", | |
| "mindgames", | |
| "universal_dependencies/en_partut/deprel", | |
| "universal_dependencies/en_lines/deprel", | |
| "universal_dependencies/en_gum/deprel", | |
| "universal_dependencies/en_ewt/deprel", | |
| "ambient", | |
| "path-naturalness-prediction", | |
| "civil_comments/toxicity", | |
| "civil_comments/severe_toxicity", | |
| "civil_comments/obscene", | |
| "civil_comments/threat", | |
| "civil_comments/insult", | |
| "civil_comments/identity_attack", | |
| "civil_comments/sexual_explicit", | |
| "cloth", | |
| "dgen", | |
| "oasst1_pairwise_rlhf_reward", | |
| "I2D2", | |
| "args_me", | |
| "Touche23-ValueEval", | |
| "starcon", | |
| "banking77", | |
| "ruletaker", | |
| "lsat_qa/all", | |
| "ConTRoL-nli", | |
| "tracie", | |
| "sherliic", | |
| "sen-making/1", | |
| "sen-making/2", | |
| "winowhy", | |
| "mbib-base/cognitive-bias", | |
| "mbib-base/fake-news", | |
| "mbib-base/gender-bias", | |
| "mbib-base/hate-speech", | |
| "mbib-base/linguistic-bias", | |
| "mbib-base/political-bias", | |
| "mbib-base/racial-bias", | |
| "mbib-base/text-level-bias", | |
| "robustLR", | |
| "v1/gen_train234_test2to10", | |
| "logical-fallacy", | |
| "parade", | |
| "cladder", | |
| "subjectivity", | |
| "MOH", | |
| "VUAC", | |
| "TroFi", | |
| "sharc_modified/mod", | |
| "conceptrules_v2", | |
| "disrpt/eng.dep.scidtb", | |
| "conll2000", | |
| "few-nerd/supervised", | |
| "finer-139", | |
| "zero-shot-label-nli", | |
| "com2sense", | |
| "scone", | |
| "winodict", | |
| "fool-me-twice", | |
| "monli", | |
| "corr2cause", | |
| "lsat_qa/all", | |
| "apt", | |
| "twitter-financial-news-sentiment", | |
| "icl-symbol-tuning-instruct", | |
| "babi_nli", | |
| "gen_debiased_nli", | |
| "imppres/presupposition", | |
| "/prag", | |
| "blimp-2", | |
| "mmlu-4" | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.30.2", | |
| "type_vocab_size": 0, | |
| "vocab_size": 128100 | |
| } | |