Datasets:
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HuggingBench-Classification

Dataset card Data Studio Files
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model:lgris/sew-tiny-portuguese-cv8 [4]
model:lgris/wav2vec2-large-xlsr-coraa-portuguese-cv7 [4]
model:lgris/wav2vec2-large-xlsr-coraa-portuguese-cv8 [4]
model:lgris/wav2vec2-xls-r-1b-cv8 [4]
model:lgris/wav2vec2-xls-r-300m-gn-cv8-3 [4]
model:lgris/wav2vec2-xls-r-300m-gn-cv8-4 [4]
model:lgris/wav2vec2-xls-r-300m-gn-cv8 [4]
model:lgris/wav2vec2-xls-r-gn-cv7 [4]
model:lgris/wav2vec2-xls-r-pt-cv7-from-bp400h [4]
model:lgris/wav2vec2_base_10k_8khz_pt_cv7_2 [4]
model:lgris/wavlm-large-CORAA-pt-cv7 [4]
model:lidiya/bart-large-xsum-samsum [26, 40]
model:lighteternal/gpt2-finetuned-greek [33]
model:lighteternal/stsb-xlm-r-greek-transfer [25, 7]
model:linydub/bart-large-samsum [26, 40]
model:lucasresck/bert-base-cased-ag-news [32]
model:lucio/xls-r-kyrgiz-cv8 [4]
model:lucio/xls-r-uyghur-cv8 [4]
model:lucio/xls-r-uzbek-cv8 [4]
model:luheng/bert-finetuned-ner [42]
model:codeparrot/codeparrot [33]
model:lvwerra/gpt2-imdb [33]
model:m3hrdadfi/albert-zwnj-wnli-mean-tokens [7, 25]
model:m3hrdadfi/bert-zwnj-wnli-mean-tokens [7, 25]
model:m3hrdadfi/distilbert-zwnj-wnli-mean-tokens [25, 7]
model:m3hrdadfi/roberta-zwnj-wnli-mean-tokens [7, 25]
model:macedonizer/al-roberta-base [8]
model:malduwais/distilbert-base-uncased-finetuned-ner [42]
model:marcelcastrobr/sagemaker-distilbert-emotion [32]
model:mariagrandury/roberta-base-finetuned-sms-spam-detection [32]
model:marinone94/xls-r-300m-sv-robust [4]
model:masapasa/xls-r-300m-it-cv8-ds13 [4]
model:masapasa/xls-r-300m-sv-cv8 [4]
model:masoudmzb/wav2vec2-xlsr-multilingual-53-fa [4]
model:matthewburke/korean_sentiment [32]
model:mbartolo/electra-large-synqa [22]
model:mbartolo/roberta-large-synqa-ext [22]
model:mbartolo/roberta-large-synqa [22]
model:mdhugol/indonesia-bert-sentiment-classification [32]
model:mdraw/german-news-sentiment-bert [32]
model:mental/mental-bert-base-uncased [8]
model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract [8]
model:microsoft/CodeGPT-small-py [33]
model:microsoft/DialogRPT-updown [32]
model:microsoft/beit-base-finetuned-ade-640-640 [12]
model:microsoft/beit-base-patch16-224-pt22k [10]
model:microsoft/beit-base-patch16-224 [10]
model:microsoft/beit-base-patch16-384 [10]
model:microsoft/beit-large-patch16-224-pt22k-ft22k [10]
model:microsoft/beit-large-patch16-224-pt22k [10]
model:microsoft/beit-large-patch16-224 [10]
model:microsoft/beit-large-patch16-384 [10]
model:microsoft/beit-large-patch16-512 [10]
model:microsoft/deberta-large [8]
model:microsoft/deberta-v2-xxlarge [8]
model:microsoft/deberta-v3-small [8]
model:microsoft/deberta-xlarge-mnli [32]
model:microsoft/infoxlm-base [8]
model:microsoft/prophetnet-large-uncased [40]
model:microsoft/swin-base-patch4-window12-384-in22k [10]
model:microsoft/swin-base-patch4-window12-384 [10]
model:microsoft/swin-base-patch4-window7-224-in22k [10]
model:microsoft/swin-base-patch4-window7-224 [10]
model:microsoft/swin-large-patch4-window12-384-in22k [10]
model:microsoft/swin-large-patch4-window12-384 [10]
model:microsoft/swin-large-patch4-window7-224-in22k [10]
model:microsoft/swin-large-patch4-window7-224 [10]
model:microsoft/swin-small-patch4-window7-224 [10]
model:microsoft/trocr-small-stage1 [16, 13]
model:microsoft/unispeech-sat-base-100h-libri-ft [4]
model:microsoft/wavlm-base [7]
model:microsoft/xlm-align-base [8]
model:microsoft/xtremedistil-l6-h384-uncased [32, 7]
model:mideind/IceBERT [8]
model:milyiyo/selectra-small-finetuned-amazon-review [32]
model:ml6team/bert-base-uncased-city-country-ner [42]
model:ml6team/gpt2-small-german-finetune-oscar [33]
model:ml6team/mt5-small-german-finetune-mlsum [26, 40]
model:monologg/biobert_v1.1_pubmed [8]
model:monologg/kobigbird-bert-base [8]
model:monsoon-nlp/gpt-nyc-small [33]
model:monsoon-nlp/gpt-nyc [33]
model:monsoon-nlp/muril-adapted-local [8]
model:morenolq/SumTO_FNS2020 [32]
model:morenolq/distilbart-bbc [40]
model:moussaKam/barthez-orangesum-abstract [26, 40]
model:mpoyraz/wav2vec2-xls-r-300m-cv8-turkish [4]
model:mrm8488/bert-base-portuguese-cased-finetuned-squad-v1-pt [22]
model:mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization [26, 40]
model:mrm8488/bert-multi-cased-finetuned-xquadv1 [22]
model:mrm8488/bert-small-finetuned-squadv2 [22]
model:mrm8488/camembert2camembert_shared-finetuned-french-summarization [26, 40]
model:mrm8488/deberta-v3-small-finetuned-sst2 [32]
model:mrm8488/distilbert-finetuned-sarcasm-classification [8]
model:mrm8488/distilroberta-finetuned-tweets-hate-speech [32]
model:mrm8488/electra-small-finetuned-squadv2 [22]
model:mrm8488/electricidad-base-finetuned-pawsx-es [32]
model:mrm8488/longformer-base-4096-finetuned-squadv2 [22]
model:mrm8488/mobilebert-uncased-finetuned-squadv1 [22]
model:mse30/bart-base-finetuned-pubmed [40]