metadata
language:
- en
pipeline_tag: zero-shot-classification
tags:
- smol
datasets:
- glue
- super_glue
- anli
- metaeval/babi_nli
- sick
- stanfordnlp/snli
- scitail
- hans
- alisawuffles/WANLI
- metaeval/recast
- sileod/probability_words_nli
- joey234/nan-nli
- pietrolesci/nli_fever
- pietrolesci/breaking_nli
- pietrolesci/conj_nli
- pietrolesci/fracas
- pietrolesci/dialogue_nli
- pietrolesci/mpe
- pietrolesci/dnc
- pietrolesci/recast_white
- pietrolesci/joci
- pietrolesci/robust_nli
- pietrolesci/robust_nli_is_sd
- pietrolesci/robust_nli_li_ts
- pietrolesci/gen_debiased_nli
- pietrolesci/add_one_rte
- metaeval/imppres
- hlgd
- paws
- medical_questions_pairs
- conll2003
- Anthropic/model-written-evals
- truthful_qa
- nightingal3/fig-qa
- tasksource/bigbench
- blimp
- cos_e
- cosmos_qa
- dream
- openbookqa
- qasc
- quartz
- quail
- head_qa
- sciq
- social_i_qa
- wiki_hop
- wiqa
- piqa
- hellaswag
- pkavumba/balanced-copa
- 12ml/e-CARE
- art
- tasksource/mmlu
- winogrande
- codah
- ai2_arc
- definite_pronoun_resolution
- swag
- math_qa
- metaeval/utilitarianism
- mteb/amazon_counterfactual
- SetFit/insincere-questions
- SetFit/toxic_conversations
- turingbench/TuringBench
- trec
- tals/vitaminc
- hope_edi
- strombergnlp/rumoureval_2019
- ethos
- tweet_eval
- discovery
- pragmeval
- silicone
- lex_glue
- papluca/language-identification
- imdb
- rotten_tomatoes
- ag_news
- yelp_review_full
- financial_phrasebank
- poem_sentiment
- dbpedia_14
- amazon_polarity
- app_reviews
- hate_speech18
- sms_spam
- humicroedit
- snips_built_in_intents
- hate_speech_offensive
- yahoo_answers_topics
- pacovaldez/stackoverflow-questions
- zapsdcn/hyperpartisan_news
- zapsdcn/sciie
- zapsdcn/citation_intent
- go_emotions
- allenai/scicite
- liar
- relbert/lexical_relation_classification
- tasksource/crowdflower
- metaeval/ethics
- emo
- google_wellformed_query
- tweets_hate_speech_detection
- has_part
- wnut_17
- ncbi_disease
- acronym_identification
- jnlpba
- SpeedOfMagic/ontonotes_english
- blog_authorship_corpus
- launch/open_question_type
- health_fact
- commonsense_qa
- mc_taco
- ade_corpus_v2
- prajjwal1/discosense
- circa
- PiC/phrase_similarity
- copenlu/scientific-exaggeration-detection
- quarel
- mwong/fever-evidence-related
- numer_sense
- dynabench/dynasent
- raquiba/Sarcasm_News_Headline
- sem_eval_2010_task_8
- demo-org/auditor_review
- medmcqa
- RuyuanWan/Dynasent_Disagreement
- RuyuanWan/Politeness_Disagreement
- RuyuanWan/SBIC_Disagreement
- RuyuanWan/SChem_Disagreement
- RuyuanWan/Dilemmas_Disagreement
- lucasmccabe/logiqa
- wiki_qa
- metaeval/cycic_classification
- metaeval/cycic_multiplechoice
- metaeval/sts-companion
- metaeval/commonsense_qa_2.0
- metaeval/lingnli
- metaeval/monotonicity-entailment
- metaeval/arct
- metaeval/scinli
- metaeval/naturallogic
- onestop_qa
- demelin/moral_stories
- corypaik/prost
- aps/dynahate
- metaeval/syntactic-augmentation-nli
- metaeval/autotnli
- lasha-nlp/CONDAQA
- openai/webgpt_comparisons
- Dahoas/synthetic-instruct-gptj-pairwise
- metaeval/scruples
- metaeval/wouldyourather
- metaeval/defeasible-nli
- metaeval/help-nli
- metaeval/nli-veridicality-transitivity
- metaeval/natural-language-satisfiability
- metaeval/lonli
- metaeval/dadc-limit-nli
- ColumbiaNLP/FLUTE
- metaeval/strategy-qa
- openai/summarize_from_feedback
- tasksource/folio
- metaeval/tomi-nli
- metaeval/avicenna
- stanfordnlp/SHP
- GBaker/MedQA-USMLE-4-options-hf
- sileod/wikimedqa
- declare-lab/cicero
- amydeng2000/CREAK
- metaeval/mutual
- inverse-scaling/NeQA
- inverse-scaling/quote-repetition
- inverse-scaling/redefine-math
- metaeval/puzzte
- metaeval/implicatures
- race
- metaeval/race-c
- metaeval/spartqa-yn
- metaeval/spartqa-mchoice
- metaeval/temporal-nli
- riddle_sense
- metaeval/clcd-english
- maximedb/twentyquestions
- metaeval/reclor
- metaeval/counterfactually-augmented-imdb
- metaeval/counterfactually-augmented-snli
- metaeval/cnli
- metaeval/boolq-natural-perturbations
- metaeval/acceptability-prediction
- metaeval/equate
- metaeval/ScienceQA_text_only
- Jiangjie/ekar_english
- metaeval/implicit-hate-stg1
- metaeval/chaos-mnli-ambiguity
- IlyaGusev/headline_cause
- metaeval/logiqa-2.0-nli
- tasksource/oasst2_dense_flat
- sileod/mindgames
- universal_dependencies
- metaeval/ambient
- metaeval/path-naturalness-prediction
- civil_comments
- AndyChiang/cloth
- AndyChiang/dgen
- tasksource/I2D2
- webis/args_me
- webis/Touche23-ValueEval
- tasksource/starcon
- PolyAI/banking77
- tasksource/ConTRoL-nli
- tasksource/tracie
- tasksource/sherliic
- tasksource/sen-making
- tasksource/winowhy
- mediabiasgroup/mbib-base
- tasksource/robustLR
- CLUTRR/v1
- tasksource/logical-fallacy
- tasksource/parade
- tasksource/cladder
- tasksource/subjectivity
- tasksource/MOH
- tasksource/VUAC
- tasksource/TroFi
- sharc_modified
- tasksource/conceptrules_v2
- metaeval/disrpt
- conll2000
- DFKI-SLT/few-nerd
- nlpaueb/finer-139
- tasksource/zero-shot-label-nli
- tasksource/com2sense
- tasksource/scone
- tasksource/winodict
- tasksource/fool-me-twice
- tasksource/monli
- tasksource/corr2cause
- lighteval/lsat_qa
- tasksource/apt
- zeroshot/twitter-financial-news-sentiment
- tasksource/icl-symbol-tuning-instruct
- tasksource/SpaceNLI
- sihaochen/propsegment
- HannahRoseKirk/HatemojiBuild
- tasksource/regset
- tasksource/esci
- lmsys/chatbot_arena_conversations
- neurae/dnd_style_intents
- hitachi-nlp/FLD.v2
- tasksource/SDOH-NLI
- allenai/scifact_entailment
- tasksource/feasibilityQA
- tasksource/simple_pair
- tasksource/AdjectiveScaleProbe-nli
- tasksource/resnli
- tasksource/SpaRTUN
- tasksource/ReSQ
- tasksource/semantic_fragments_nli
- MoritzLaurer/dataset_train_nli
- tasksource/stepgame
- tasksource/nlgraph
- tasksource/oasst2_pairwise_rlhf_reward
- tasksource/hh-rlhf
- tasksource/ruletaker
- qbao775/PARARULE-Plus
- tasksource/proofwriter
- tasksource/logical-entailment
- tasksource/nope
- tasksource/LogicNLI
- kiddothe2b/contract-nli
- AshtonIsNotHere/nli4ct_semeval2024
- tasksource/lsat-ar
- tasksource/lsat-rc
- AshtonIsNotHere/biosift-nli
- tasksource/brainteasers
- Anthropic/persuasion
- erbacher/AmbigNQ-clarifying-question
- tasksource/SIGA-nli
deberta-v3-xsmall fine-tuned for 100k steps on the tasksource collection
Model size: 22M backbone + 48M vocabulary parameters
Refer to the this page for documentation :[https://huggingface.co/sileod/deberta-v3-base-tasksource-nli]