Zero-Shot Classification
Transformers
PyTorch
English
deberta-v2
text-classification
deberta-v3-small
deberta-v3
deberta
nli
natural-language-inference
multitask
multi-task
pipeline
extreme-multi-task
extreme-mtl
tasksource
zero-shot
rlhf
Inference Endpoints
sileod commited on
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696
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
+ "head_qa/en",
738
+ "sciq",
739
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740
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741
+ "wiqa",
742
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743
+ "hellaswag",
744
+ "super_glue/copa",
745
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746
+ "e-CARE",
747
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748
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749
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750
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751
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752
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753
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754
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755
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756
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757
+ "utilitarianism",
758
+ "amazon_counterfactual/en",
759
+ "insincere-questions",
760
+ "toxic_conversations",
761
+ "TuringBench",
762
+ "trec",
763
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764
+ "hope_edi/english",
765
+ "rumoureval_2019/RumourEval2019",
766
+ "ethos/binary",
767
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768
+ "tweet_eval/sentiment",
769
+ "tweet_eval/emotion",
770
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771
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772
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773
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774
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775
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776
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777
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778
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779
+ "discovery/discovery",
780
+ "pragmeval/squinky-informativeness",
781
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782
+ "pragmeval/emobank-arousal",
783
+ "pragmeval/squinky-formality",
784
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785
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786
+ "pragmeval/mrda",
787
+ "pragmeval/emobank-valence",
788
+ "pragmeval/verifiability",
789
+ "pragmeval/persuasiveness-strength",
790
+ "pragmeval/sarcasm",
791
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792
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793
+ "pragmeval/pdtb",
794
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795
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796
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797
+ "pragmeval/persuasiveness-claimtype",
798
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799
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800
+ "silicone/iemocap",
801
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802
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803
+ "silicone/meld_e",
804
+ "silicone/meld_s",
805
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806
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807
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808
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809
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810
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811
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812
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813
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814
+ "imdb",
815
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816
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817
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818
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819
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820
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821
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822
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823
+ "hate_speech18",
824
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825
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826
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827
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828
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829
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830
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831
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832
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833
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834
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835
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836
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837
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838
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839
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840
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841
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842
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843
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844
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845
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846
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848
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849
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850
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852
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853
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854
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855
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856
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857
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858
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859
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860
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861
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862
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863
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864
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865
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866
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867
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868
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869
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870
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871
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872
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873
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874
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875
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876
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877
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879
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884
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894
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895
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896
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897
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898
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899
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900
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901
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902
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903
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904
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905
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906
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908
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909
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910
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911
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913
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914
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916
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917
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918
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920
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921
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922
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923
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925
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926
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927
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928
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929
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931
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932
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933
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934
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935
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936
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937
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938
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939
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941
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942
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943
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944
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945
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946
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947
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948
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949
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950
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951
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952
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953
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954
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955
+ "reclor",
956
+ "counterfactually-augmented-imdb",
957
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958
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959
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960
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961
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962
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963
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964
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965
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966
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967
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968
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969
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970
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971
+ "mindgames",
972
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973
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974
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975
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976
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977
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978
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979
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980
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981
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982
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983
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984
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985
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989
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990
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991
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992
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993
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994
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995
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997
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999
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1000
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1001
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1002
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1003
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1004
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1005
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1006
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1007
+ "robustLR",
1008
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1009
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1010
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1011
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1012
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1013
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1014
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1015
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1016
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1017
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1018
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1019
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1020
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1021
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1022
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1023
+ "com2sense",
1024
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1025
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1026
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1027
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1028
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1029
+ "lsat_qa/all",
1030
+ "apt",
1031
+ "twitter-financial-news-sentiment",
1032
+ "icl-symbol-tuning-instruct",
1033
+ "SpaceNLI",
1034
+ "propsegment/nli",
1035
+ "HatemojiBuild",
1036
+ "regset",
1037
+ "esci",
1038
+ "chatbot_arena_conversations",
1039
+ "dnd_style_intents",
1040
+ "FLD.v2",
1041
+ "SDOH-NLI",
1042
+ "scifact_entailment",
1043
+ "feasibilityQA",
1044
+ "simple_pair",
1045
+ "AdjectiveScaleProbe-nli",
1046
+ "resnli",
1047
+ "SpaRTUN",
1048
+ "ReSQ",
1049
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1050
+ "dataset_train_nli",
1051
+ "stepgame",
1052
+ "nlgraph",
1053
+ "oasst2_pairwise_rlhf_reward",
1054
+ "hh-rlhf/helpful-rejection-sampled",
1055
+ "hh-rlhf/helpful-base",
1056
+ "hh-rlhf/helpful-online",
1057
+ "hh-rlhf/harmless-base",
1058
+ "ruletaker",
1059
+ "PARARULE-Plus",
1060
+ "proofwriter",
1061
+ "logical-entailment",
1062
+ "babi_nli",
1063
+ "gen_debiased_nli",
1064
+ "imppres/presupposition",
1065
+ "/prag",
1066
+ "blimp-2",
1067
+ "mmlu-4"
1068
+ ],
1069
+ "torch_dtype": "float32",
1070
+ "transformers_version": "4.34.1",
1071
+ "type_vocab_size": 0,
1072
+ "vocab_size": 128100
1073
+ }
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