Text Classification
Transformers
PyTorch
English
deberta-v2
Inference Endpoints
ikrysinska commited on
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+ "bigbench/bbq_lite_json",
690
+ "bigbench/epistemic_reasoning",
691
+ "bigbench/phrase_relatedness",
692
+ "bigbench/presuppositions_as_nli",
693
+ "bigbench/hindu_knowledge",
694
+ "bigbench/gre_reading_comprehension",
695
+ "bigbench/disambiguation_qa",
696
+ "bigbench/play_dialog_same_or_different",
697
+ "bigbench/date_understanding",
698
+ "bigbench/implicatures",
699
+ "bigbench/movie_dialog_same_or_different",
700
+ "bigbench/unit_interpretation",
701
+ "bigbench/symbol_interpretation",
702
+ "cos_e/v1.0",
703
+ "cosmos_qa",
704
+ "dream",
705
+ "openbookqa",
706
+ "qasc",
707
+ "quartz",
708
+ "quail",
709
+ "head_qa/en",
710
+ "sciq",
711
+ "social_i_qa",
712
+ "wiki_hop/original",
713
+ "wiqa",
714
+ "piqa",
715
+ "hellaswag",
716
+ "super_glue/copa",
717
+ "balanced-copa",
718
+ "e-CARE",
719
+ "art",
720
+ "winogrande/winogrande_xl",
721
+ "codah/codah",
722
+ "ai2_arc/ARC-Easy/challenge",
723
+ "ai2_arc/ARC-Challenge/challenge",
724
+ "definite_pronoun_resolution",
725
+ "swag/regular",
726
+ "math_qa",
727
+ "glue/cola",
728
+ "glue/sst2",
729
+ "utilitarianism",
730
+ "amazon_counterfactual/en",
731
+ "insincere-questions",
732
+ "toxic_conversations",
733
+ "TuringBench",
734
+ "trec",
735
+ "vitaminc/tals--vitaminc",
736
+ "hope_edi/english",
737
+ "rumoureval_2019/RumourEval2019",
738
+ "ethos/binary",
739
+ "ethos/multilabel",
740
+ "tweet_eval/stance_abortion",
741
+ "tweet_eval/emoji",
742
+ "tweet_eval/irony",
743
+ "tweet_eval/stance_atheism",
744
+ "tweet_eval/stance_hillary",
745
+ "tweet_eval/emotion",
746
+ "tweet_eval/stance_climate",
747
+ "tweet_eval/stance_feminist",
748
+ "tweet_eval/sentiment",
749
+ "tweet_eval/offensive",
750
+ "tweet_eval/hate",
751
+ "discovery/discovery",
752
+ "pragmeval/squinky-formality",
753
+ "pragmeval/emobank-valence",
754
+ "pragmeval/emobank-dominance",
755
+ "pragmeval/verifiability",
756
+ "pragmeval/mrda",
757
+ "pragmeval/emobank-arousal",
758
+ "pragmeval/squinky-informativeness",
759
+ "pragmeval/squinky-implicature",
760
+ "pragmeval/switchboard",
761
+ "pragmeval/gum",
762
+ "pragmeval/persuasiveness-eloquence",
763
+ "pragmeval/stac",
764
+ "pragmeval/pdtb",
765
+ "pragmeval/sarcasm",
766
+ "pragmeval/persuasiveness-strength",
767
+ "pragmeval/emergent",
768
+ "pragmeval/persuasiveness-claimtype",
769
+ "pragmeval/persuasiveness-specificity",
770
+ "pragmeval/persuasiveness-premisetype",
771
+ "pragmeval/persuasiveness-relevance",
772
+ "silicone/meld_e",
773
+ "silicone/meld_s",
774
+ "silicone/iemocap",
775
+ "silicone/oasis",
776
+ "silicone/dyda_e",
777
+ "silicone/dyda_da",
778
+ "silicone/sem",
779
+ "silicone/maptask",
780
+ "lex_glue/eurlex",
781
+ "lex_glue/scotus",
782
+ "lex_glue/ledgar",
783
+ "lex_glue/unfair_tos",
784
+ "lex_glue/case_hold",
785
+ "language-identification",
786
+ "imdb",
787
+ "rotten_tomatoes",
788
+ "ag_news",
789
+ "yelp_review_full/yelp_review_full",
790
+ "financial_phrasebank/sentences_allagree",
791
+ "poem_sentiment",
792
+ "dbpedia_14/dbpedia_14",
793
+ "amazon_polarity/amazon_polarity",
794
+ "app_reviews",
795
+ "hate_speech18",
796
+ "sms_spam",
797
+ "humicroedit/subtask-1",
798
+ "humicroedit/subtask-2",
799
+ "snips_built_in_intents",
800
+ "hate_speech_offensive",
801
+ "yahoo_answers_topics",
802
+ "stackoverflow-questions",
803
+ "hyperpartisan_news",
804
+ "sciie",
805
+ "citation_intent",
806
+ "go_emotions/simplified",
807
+ "scicite",
808
+ "liar",
809
+ "lexical_relation_classification/ROOT09",
810
+ "lexical_relation_classification/K&H+N",
811
+ "lexical_relation_classification/EVALution",
812
+ "lexical_relation_classification/CogALexV",
813
+ "lexical_relation_classification/BLESS",
814
+ "linguisticprobing/odd_man_out",
815
+ "linguisticprobing/bigram_shift",
816
+ "linguisticprobing/top_constituents",
817
+ "linguisticprobing/subj_number",
818
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819
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820
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821
+ "linguisticprobing/past_present",
822
+ "linguisticprobing/obj_number",
823
+ "crowdflower/sentiment_nuclear_power",
824
+ "crowdflower/tweet_global_warming",
825
+ "crowdflower/airline-sentiment",
826
+ "crowdflower/corporate-messaging",
827
+ "crowdflower/text_emotion",
828
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829
+ "crowdflower/political-media-audience",
830
+ "crowdflower/economic-news",
831
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832
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833
+ "ethics/deontology",
834
+ "ethics/justice",
835
+ "ethics/virtue",
836
+ "emo/emo2019",
837
+ "google_wellformed_query",
838
+ "tweets_hate_speech_detection",
839
+ "has_part",
840
+ "wnut_17/wnut_17",
841
+ "ncbi_disease/ncbi_disease",
842
+ "acronym_identification",
843
+ "jnlpba/jnlpba",
844
+ "ontonotes_english/SpeedOfMagic--ontonotes_english",
845
+ "blog_authorship_corpus/gender",
846
+ "blog_authorship_corpus/age",
847
+ "blog_authorship_corpus/horoscope",
848
+ "blog_authorship_corpus/job",
849
+ "open_question_type",
850
+ "health_fact",
851
+ "commonsense_qa",
852
+ "mc_taco",
853
+ "ade_corpus_v2/Ade_corpus_v2_classification",
854
+ "discosense",
855
+ "circa",
856
+ "EffectiveFeedbackStudentWriting",
857
+ "phrase_similarity",
858
+ "scientific-exaggeration-detection",
859
+ "quarel",
860
+ "fever-evidence-related/mwong--fever-related",
861
+ "numer_sense",
862
+ "dynasent/dynabench.dynasent.r1.all/r1",
863
+ "dynasent/dynabench.dynasent.r2.all/r2",
864
+ "Sarcasm_News_Headline",
865
+ "sem_eval_2010_task_8",
866
+ "auditor_review/demo-org--auditor_review",
867
+ "medmcqa",
868
+ "Dynasent_Disagreement",
869
+ "Politeness_Disagreement",
870
+ "SBIC_Disagreement",
871
+ "SChem_Disagreement",
872
+ "Dilemmas_Disagreement",
873
+ "logiqa",
874
+ "wiki_qa",
875
+ "cycic_classification",
876
+ "cycic_multiplechoice",
877
+ "sts-companion",
878
+ "commonsense_qa_2.0",
879
+ "lingnli",
880
+ "monotonicity-entailment",
881
+ "arct",
882
+ "scinli",
883
+ "naturallogic",
884
+ "onestop_qa",
885
+ "moral_stories/full",
886
+ "prost",
887
+ "dynahate",
888
+ "syntactic-augmentation-nli",
889
+ "autotnli",
890
+ "CONDAQA",
891
+ "webgpt_comparisons",
892
+ "synthetic-instruct-gptj-pairwise",
893
+ "scruples",
894
+ "wouldyourather",
895
+ "attempto-nli",
896
+ "defeasible-nli/snli",
897
+ "defeasible-nli/atomic",
898
+ "help-nli",
899
+ "nli-veridicality-transitivity",
900
+ "natural-language-satisfiability",
901
+ "lonli",
902
+ "dadc-limit-nli",
903
+ "FLUTE",
904
+ "strategy-qa",
905
+ "summarize_from_feedback/comparisons",
906
+ "folio",
907
+ "tomi-nli",
908
+ "avicenna",
909
+ "SHP",
910
+ "MedQA-USMLE-4-options-hf",
911
+ "wikimedqa/medwiki",
912
+ "cicero",
913
+ "CREAK",
914
+ "mutual",
915
+ "NeQA",
916
+ "quote-repetition",
917
+ "redefine-math",
918
+ "puzzte",
919
+ "implicatures",
920
+ "race/high",
921
+ "race/middle",
922
+ "race-c",
923
+ "spartqa-yn",
924
+ "spartqa-mchoice",
925
+ "temporal-nli",
926
+ "riddle_sense",
927
+ "clcd-english",
928
+ "twentyquestions",
929
+ "reclor",
930
+ "counterfactually-augmented-imdb",
931
+ "counterfactually-augmented-snli",
932
+ "cnli",
933
+ "boolq-natural-perturbations",
934
+ "acceptability-prediction",
935
+ "equate",
936
+ "ScienceQA_text_only",
937
+ "ekar_english",
938
+ "implicit-hate-stg1",
939
+ "chaos-mnli-ambiguity",
940
+ "headline_cause/en_simple",
941
+ "logiqa-2.0-nli",
942
+ "oasst1_dense_flat/quality",
943
+ "oasst1_dense_flat/toxicity",
944
+ "oasst1_dense_flat/helpfulness",
945
+ "PARARULE-Plus",
946
+ "mindgames",
947
+ "universal_dependencies/en_ewt/deprel",
948
+ "universal_dependencies/en_gum/deprel",
949
+ "universal_dependencies/en_lines/deprel",
950
+ "universal_dependencies/en_partut/deprel",
951
+ "ambient",
952
+ "path-naturalness-prediction",
953
+ "civil_comments/toxicity",
954
+ "civil_comments/severe_toxicity",
955
+ "civil_comments/obscene",
956
+ "civil_comments/threat",
957
+ "civil_comments/insult",
958
+ "civil_comments/identity_attack",
959
+ "civil_comments/sexual_explicit",
960
+ "cloth",
961
+ "dgen",
962
+ "oasst1_pairwise_rlhf_reward",
963
+ "I2D2",
964
+ "args_me",
965
+ "Touche23-ValueEval",
966
+ "starcon",
967
+ "banking77",
968
+ "ruletaker",
969
+ "lsat_qa/all",
970
+ "ConTRoL-nli",
971
+ "tracie",
972
+ "sherliic",
973
+ "sen-making/1",
974
+ "sen-making/2",
975
+ "winowhy",
976
+ "mbib-base/cognitive-bias",
977
+ "mbib-base/fake-news",
978
+ "mbib-base/gender-bias",
979
+ "mbib-base/hate-speech",
980
+ "mbib-base/linguistic-bias",
981
+ "mbib-base/political-bias",
982
+ "mbib-base/racial-bias",
983
+ "mbib-base/text-level-bias",
984
+ "robustLR",
985
+ "v1/gen_train234_test2to10",
986
+ "logical-fallacy",
987
+ "parade",
988
+ "cladder",
989
+ "subjectivity",
990
+ "MOH",
991
+ "VUAC",
992
+ "TroFi",
993
+ "sharc_modified/mod",
994
+ "conceptrules_v2",
995
+ "disrpt/eng.dep.scidtb",
996
+ "conll2000",
997
+ "few-nerd/supervised",
998
+ "zero-shot-label-nli",
999
+ "com2sense",
1000
+ "scone",
1001
+ "winodict",
1002
+ "fool-me-twice",
1003
+ "monli",
1004
+ "babi_nli",
1005
+ "gen_debiased_nli",
1006
+ "imppres/presupposition",
1007
+ "/prag",
1008
+ "blimp-2",
1009
+ "mmlu-4"
1010
+ ],
1011
+ "torch_dtype": "float32",
1012
+ "transformers_version": "4.21.2",
1013
+ "type_vocab_size": 0,
1014
+ "vocab_size": 128100
1015
+ }
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