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autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-cd62e4-67882145606
2023-10-04T17:26:08.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
null
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2023-10-04T17:25:08
--- type: predictions tags: - autotrain - evaluation datasets: - adversarial_qa eval_info: task: extractive_question_answering model: Akihiro2/bert-finetuned-squad metrics: [] dataset_name: adversarial_qa dataset_config: adversarialQA dataset_split: validation col_mapping: context: context question: question answers-text: answers.text answers-answer_start: answers.answer_start --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Question Answering * Model: Akihiro2/bert-finetuned-squad * Dataset: adversarial_qa * Config: adversarialQA * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@zhouzj](https://huggingface.co/zhouzj) for evaluating this model.
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autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-cd62e4-67882145607
2023-10-04T17:26:15.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
null
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2023-10-04T17:25:11
--- type: predictions tags: - autotrain - evaluation datasets: - adversarial_qa eval_info: task: extractive_question_answering model: Asmit/bert-finetuned-squad metrics: [] dataset_name: adversarial_qa dataset_config: adversarialQA dataset_split: validation col_mapping: context: context question: question answers-text: answers.text answers-answer_start: answers.answer_start --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Question Answering * Model: Asmit/bert-finetuned-squad * Dataset: adversarial_qa * Config: adversarialQA * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@zhouzj](https://huggingface.co/zhouzj) for evaluating this model.
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autoevaluate/autoeval-eval-acronym_identification-default-58eb27-68148145611
2023-10-04T17:25:59.000Z
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autoevaluate
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autoevaluate/autoeval-eval-glue-cola-508e4a-68175145612
2023-10-04T17:26:37.000Z
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2023-10-04T17:26:33
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autoevaluate/autoeval-eval-acronym_identification-default-460442-68463145616
2023-10-04T17:26:40.000Z
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autoevaluate
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2023-10-04T17:26:37
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autoevaluate/autoeval-eval-acronym_identification-default-4e5d8b-68492145617
2023-10-04T17:26:45.000Z
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autoevaluate
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autoevaluate/autoeval-eval-acronym_identification-default-20be5f-68181145613
2023-10-04T17:26:45.000Z
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autoevaluate
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2023-10-04T17:26:42
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autoevaluate/autoeval-eval-acronym_identification-default-9e8f9b-68269145614
2023-10-04T17:26:48.000Z
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autoevaluate
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2023-10-04T17:26:45
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autoevaluate/autoeval-eval-acronym_identification-default-2b4455-68323145615
2023-10-04T17:27:19.000Z
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autoevaluate
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2023-10-04T17:27:15
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autoevaluate/autoeval-eval-acronym_identification-default-31f5c5-68516145618
2023-10-04T17:27:22.000Z
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autoevaluate
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2023-10-04T17:27:18
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autoevaluate/autoeval-eval-go_emotions-raw-c4cfa5-68606145620
2023-10-04T17:27:26.000Z
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autoevaluate
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2023-10-04T17:27:22
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autoevaluate/autoeval-eval-go_emotions-raw-c4cfa5-68606145621
2023-10-04T17:27:27.000Z
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autoevaluate
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2023-10-04T17:27:23
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autoevaluate/autoeval-eval-acronym_identification-default-0f2636-68520145619
2023-10-04T17:27:26.000Z
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autoevaluate
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2023-10-04T17:27:23
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autoevaluate/autoeval-eval-conll2003-conll2003-e68bb2-67908145608
2023-10-04T17:34:15.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
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2023-10-04T17:27:54
--- type: predictions tags: - autotrain - evaluation datasets: - conll2003 eval_info: task: entity_extraction model: 51la5/bert-large-NER metrics: ['bertscore'] dataset_name: conll2003 dataset_config: conll2003 dataset_split: train col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: 51la5/bert-large-NER * Dataset: conll2003 * Config: conll2003 * Split: train To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@theoraclephd](https://huggingface.co/theoraclephd) for evaluating this model.
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autoevaluate/autoeval-eval-acronym_identification-default-0d74fb-68661145622
2023-10-04T17:28:00.000Z
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autoevaluate
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2023-10-04T17:27:56
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autoevaluate/autoeval-eval-acronym_identification-default-5a5ab9-68735145623
2023-10-04T17:28:06.000Z
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autoevaluate
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2023-10-04T17:28:02
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autoevaluate/autoeval-eval-acronym_identification-default-1982e3-68759145624
2023-10-04T17:28:17.000Z
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autoevaluate
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2023-10-04T17:28:13
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autoevaluate/autoeval-eval-acronym_identification-default-b10dc6-68760145625
2023-10-04T17:28:21.000Z
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autoevaluate
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autoevaluate/autoeval-eval-squad_v2-squad_v2-bc82cf-68805145626
2023-10-04T17:28:37.000Z
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autoevaluate
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2023-10-04T17:28:33
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autoevaluate/autoeval-eval-acronym_identification-default-0f8f5a-68821145627
2023-10-04T17:28:45.000Z
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autoevaluate
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autoevaluate/autoeval-eval-samsum-samsum-e12e62-68887145628
2023-10-04T17:28:56.000Z
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autoevaluate
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2023-10-04T17:28:52
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autoevaluate/autoeval-eval-samsum-samsum-e12e62-68887145629
2023-10-04T17:36:22.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
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2023-10-04T17:28:54
--- type: predictions tags: - autotrain - evaluation datasets: - samsum eval_info: task: summarization model: d0rj/rut5-base-summ metrics: [] dataset_name: samsum dataset_config: samsum dataset_split: test col_mapping: text: dialogue target: summary --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: d0rj/rut5-base-summ * Dataset: samsum * Config: samsum * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@d0rj](https://huggingface.co/d0rj) for evaluating this model.
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autoevaluate/autoeval-eval-ade_corpus_v2-Ade_corpus_v2_classification-7bebf7-68056145609
2023-10-04T17:29:24.000Z
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autoevaluate
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2023-10-04T17:29:20
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autoevaluate/autoeval-eval-xsum-default-199117-68890145630
2023-10-04T19:46:09.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
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2023-10-04T17:30:14
--- type: predictions tags: - autotrain - evaluation datasets: - xsum eval_info: task: summarization model: d0rj/rut5-base-summ metrics: [] dataset_name: xsum dataset_config: default dataset_split: test col_mapping: text: document target: summary --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: d0rj/rut5-base-summ * Dataset: xsum * Config: default * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@d0rj](https://huggingface.co/d0rj) for evaluating this model.
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-657a6e-69032145637
2023-10-04T17:30:39.000Z
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autoevaluate/autoeval-eval-ag_news-default-d8388c-69061145638
2023-10-04T17:30:51.000Z
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autoevaluate
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2023-10-04T17:30:43
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autoevaluate/autoeval-eval-squadshifts-nyt-4ac5f8-69195145640
2023-10-04T17:31:25.000Z
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autoevaluate
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2023-10-04T17:31:20
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autoevaluate/autoeval-eval-acronym_identification-default-d4c5a8-69063145639
2023-10-04T17:31:30.000Z
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autoevaluate/autoeval-eval-acronym_identification-default-6b3ddf-68921145634
2023-10-04T17:31:39.000Z
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autoevaluate/autoeval-eval-squadshifts-nyt-4ac5f8-69195145641
2023-10-04T17:32:09.000Z
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2023-10-04T17:32:05
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autoevaluate/autoeval-eval-acronym_identification-default-ab931e-68894145632
2023-10-04T17:32:18.000Z
[ "region:us" ]
autoevaluate
null
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autoevaluate/autoeval-eval-squadshifts-reddit-75a166-69197145645
2023-10-04T17:32:19.000Z
[ "region:us" ]
autoevaluate
null
null
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2023-10-04T17:32:15
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autoevaluate/autoeval-eval-squadshifts-nyt-98ac89-69196145643
2023-10-04T17:32:53.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:32:49
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autoevaluate/autoeval-eval-xsum-default-199117-68890145631
2023-10-04T17:33:15.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:33:10
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autoevaluate/autoeval-eval-squadshifts-reddit-75a166-69197145644
2023-10-04T17:34:06.000Z
[ "region:us" ]
autoevaluate
null
null
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2023-10-04T17:34:02
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autoevaluate/autoeval-eval-squadshifts-nyt-98ac89-69196145642
2023-10-04T17:34:53.000Z
[ "region:us" ]
autoevaluate
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autoevaluate/autoeval-eval-acronym_identification-default-666611-69327145648
2023-10-04T17:35:39.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:35:35
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autoevaluate/autoeval-eval-squad-plain_text-b528f3-69445145652
2023-10-04T17:35:57.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:35:53
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autoevaluate/autoeval-eval-acronym_identification-default-597533-69343145650
2023-10-04T17:36:17.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:36:13
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autoevaluate/autoeval-eval-acronym_identification-default-b738a0-68973145635
2023-10-04T17:36:35.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:36:31
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autoevaluate/autoeval-eval-squad-plain_text-b528f3-69445145654
2023-10-04T17:36:58.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:36:54
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autoevaluate/autoeval-eval-squad-plain_text-b528f3-69445145655
2023-10-04T17:37:09.000Z
[ "region:us" ]
autoevaluate
null
null
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2023-10-04T17:37:06
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autoevaluate/autoeval-eval-ade_corpus_v2-Ade_corpus_v2_classification-3b42eb-69446145656
2023-10-04T17:37:14.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:37:10
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15
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autoevaluate/autoeval-eval-acronym_identification-default-eb9367-69467145657
2023-10-04T17:37:16.000Z
[ "region:us" ]
autoevaluate
null
null
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2023-10-04T17:37:12
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erhwenkuo/clean_passages_80m-chinese-zhtw
2023-10-04T21:53:04.000Z
[ "task_categories:text-generation", "size_categories:10M<n<100M", "language:zh", "region:us" ]
erhwenkuo
null
null
0
0
2023-10-04T17:37:32
--- dataset_info: features: - name: passage dtype: string splits: - name: train num_bytes: 18996999214 num_examples: 88328203 download_size: 13088559046 dataset_size: 18996999214 configs: - config_name: default data_files: - split: train path: data/train-* task_categories: - text-generation language: - zh size_categories: - 10M<n<100M --- # Dataset Card for "clean_passages_80m-chinese-zhtw" 包含**8千萬餘萬**(88328203)個中文段落,不包含任何字母、數字。文字長度大部分介於 50\~200 個字。 原始資料集是用於訓練[GENIUS模型中文版](https://huggingface.co/spaces/beyond/genius)。論文參考引用: ``` @article{guo2022genius, title={GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation}, author={Guo, Biyang and Gong, Yeyun and Shen, Yelong and Han, Songqiao and Huang, Hailiang and Duan, Nan and Chen, Weizhu}, journal={arXiv preprint arXiv:2211.10330}, year={2022} } ``` ## 資料集來源 本資料集是基於[CLUE中文預訓練語料集](https://github.com/CLUEbenchmark/CLUE)進行處理、過濾并進行簡繁轉諲而得到的。 原始資料集引用: ``` @misc{bright_xu_2019_3402023, author = {Bright Xu}, title = {NLP Chinese Corpus: Large Scale Chinese Corpus for NLP }, month = sep, year = 2019, doi = {10.5281/zenodo.3402023}, version = {1.0}, publisher = {Zenodo}, url = {https://doi.org/10.5281/zenodo.3402023} } ```
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autoevaluate/autoeval-eval-acronym_identification-default-d56b8a-69576145658
2023-10-04T17:37:53.000Z
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autoevaluate
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autoevaluate/autoeval-eval-imdb-plain_text-8a4130-69634145659
2023-10-04T17:37:56.000Z
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autoevaluate
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autoevaluate/autoeval-eval-acronym_identification-default-fc8438-69328145649
2023-10-04T17:38:08.000Z
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autoevaluate
null
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2023-10-04T17:38:04
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autoevaluate/autoeval-eval-acronym_identification-default-94a268-69686145661
2023-10-04T17:38:30.000Z
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autoevaluate
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2023-10-04T17:38:27
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autoevaluate/autoeval-eval-acronym_identification-default-185a2c-69702145662
2023-10-04T17:38:33.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:38:29
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autoevaluate/autoeval-eval-acronym_identification-default-d32055-69703145663
2023-10-04T17:38:35.000Z
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autoevaluate
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2023-10-04T17:38:31
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autoevaluate/autoeval-eval-acronym_identification-default-cfaff9-69883145664
2023-10-04T17:38:45.000Z
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autoevaluate
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2023-10-04T17:38:41
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autoevaluate/autoeval-eval-imdb-plain_text-8a4130-69634145660
2023-10-04T17:38:51.000Z
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autoevaluate
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2023-10-04T17:38:47
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autoevaluate/autoeval-eval-squad_v2-squad_v2-c9866e-69898145665
2023-10-04T17:39:08.000Z
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autoevaluate
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2023-10-04T17:39:05
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-0750f3-69912145666
2023-10-04T17:39:16.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:39:12
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-5c6ce1-69913145667
2023-10-04T17:39:18.000Z
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autoevaluate
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-5c6ce1-69913145668
2023-10-04T17:39:30.000Z
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autoevaluate
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2023-10-04T17:39:26
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autoevaluate/autoeval-eval-squadshifts-reddit-e63d81-69198145646
2023-10-04T17:39:31.000Z
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autoevaluate
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2023-10-04T17:39:27
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-5c6ce1-69913145669
2023-10-04T17:39:53.000Z
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autoevaluate
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2023-10-04T17:39:49
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-247a8b-69915145670
2023-10-04T17:39:55.000Z
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autoevaluate
null
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2023-10-04T17:39:51
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-247a8b-69915145671
2023-10-04T17:40:05.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:40:02
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autoevaluate/autoeval-eval-tner__bc5cdr-bc5cdr-247a8b-69915145672
2023-10-04T17:40:21.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:40:17
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autoevaluate/autoeval-eval-yelp_review_full-yelp_review_full-f52961-69920145673
2023-10-04T17:40:31.000Z
[ "region:us" ]
autoevaluate
null
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2023-10-04T17:40:27
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autoevaluate/autoeval-eval-yelp_polarity-plain_text-c254cd-69921145674
2023-10-04T17:40:41.000Z
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autoevaluate
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2023-10-04T17:40:36
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autoevaluate/autoeval-eval-acronym_identification-default-7eb114-70037145675
2023-10-04T17:40:51.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:40:47
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autoevaluate/autoeval-eval-acronym_identification-default-25bbbc-70173145676
2023-10-04T17:40:59.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:40:55
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autoevaluate/autoeval-eval-squad-plain_text-1683b2-69031145636
2023-10-04T17:41:05.000Z
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autoevaluate/autoeval-eval-squad-plain_text-b528f3-69445145651
2023-10-04T17:41:22.000Z
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2023-10-04T17:41:19
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autoevaluate/autoeval-eval-acronym_identification-default-733f7f-70174145677
2023-10-04T17:41:24.000Z
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autoevaluate
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2023-10-04T17:41:21
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autoevaluate/autoeval-eval-acronym_identification-default-c4974c-70206145678
2023-10-04T17:41:30.000Z
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2023-10-04T17:41:26
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autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-0b96f1-70211145679
2023-10-04T17:41:32.000Z
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autoevaluate
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2023-10-04T17:41:29
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autoevaluate/autoeval-eval-squad-plain_text-b528f3-69445145653
2023-10-04T17:41:43.000Z
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autoevaluate
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2023-10-04T17:41:39
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autoevaluate/autoeval-eval-squadshifts-reddit-e63d81-69198145647
2023-10-04T17:41:53.000Z
[ "region:us" ]
autoevaluate
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2023-10-04T17:41:50
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autoevaluate/autoeval-eval-acronym_identification-default-12c3e0-70217145680
2023-10-04T17:42:02.000Z
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autoevaluate/autoeval-eval-acronym_identification-default-f20b7a-70249145681
2023-10-04T17:42:06.000Z
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autoevaluate
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2023-10-04T17:42:03
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autoevaluate/autoeval-eval-ejschwartz__oo-method-test-bylibrary-test-ejschwartz__o-703054-70259145682
2023-10-04T17:42:10.000Z
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autoevaluate
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2023-10-04T17:42:06
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autoevaluate/autoeval-eval-amazon_polarity-amazon_polarity-322a2a-70310145683
2023-10-04T17:42:17.000Z
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autoevaluate
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2023-10-04T17:42:13
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autoevaluate/autoeval-eval-amazon_polarity-amazon_polarity-e891a6-70311145684
2023-10-04T17:42:26.000Z
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autoevaluate
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2023-10-04T17:42:22
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autoevaluate/autoeval-eval-amazon_polarity-amazon_polarity-976ed0-70312145685
2023-10-04T17:42:41.000Z
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autoevaluate
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2023-10-04T17:42:37
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autoevaluate/autoeval-eval-yelp_polarity-plain_text-2ac130-70653145686
2023-10-04T17:42:48.000Z
[ "region:us" ]
autoevaluate
null
null
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2023-10-04T17:42:44
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autoevaluate/autoeval-eval-yelp_polarity-plain_text-5c1435-70656145687
2023-10-04T17:42:58.000Z
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autoevaluate
null
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2023-10-04T17:42:54
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autoevaluate/autoeval-eval-OxAISH-AL-LLM__wiki_toxic-default-8c726c-70747145688
2023-10-04T18:17:23.000Z
[ "autotrain", "evaluation", "region:us" ]
autoevaluate
null
null
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2023-10-04T17:43:05
--- type: predictions tags: - autotrain - evaluation datasets: - OxAISH-AL-LLM/wiki_toxic eval_info: task: summarization model: MurkatG/bart-reviews metrics: ['precision'] dataset_name: OxAISH-AL-LLM/wiki_toxic dataset_config: default dataset_split: test col_mapping: text: comment_text target: label --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: MurkatG/bart-reviews * Dataset: OxAISH-AL-LLM/wiki_toxic * Config: default * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@Krzys](https://huggingface.co/Krzys) for evaluating this model.
859
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open-llm-leaderboard/details_beomi__KoRWKV-6B
2023-10-26T04:59:57.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
0
0
2023-10-04T17:43:15
--- pretty_name: Evaluation run of beomi/KoRWKV-6B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [beomi/KoRWKV-6B](https://huggingface.co/beomi/KoRWKV-6B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_beomi__KoRWKV-6B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-26T04:59:46.486302](https://huggingface.co/datasets/open-llm-leaderboard/details_beomi__KoRWKV-6B/blob/main/results_2023-10-26T04-59-46.486302.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.018246644295302015,\n\ \ \"em_stderr\": 0.001370668245281319,\n \"f1\": 0.05829278523489933,\n\ \ \"f1_stderr\": 0.0018688501996275634,\n \"acc\": 0.2557221783741121,\n\ \ \"acc_stderr\": 0.007024402099929661\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.018246644295302015,\n \"em_stderr\": 0.001370668245281319,\n\ \ \"f1\": 0.05829278523489933,\n \"f1_stderr\": 0.0018688501996275634\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5114443567482242,\n\ \ \"acc_stderr\": 0.014048804199859322\n }\n}\n```" repo_url: https://huggingface.co/beomi/KoRWKV-6B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|arc:challenge|25_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-10-04T17-42-58.699001.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_26T04_59_46.486302 path: - '**/details_harness|drop|3_2023-10-26T04-59-46.486302.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-26T04-59-46.486302.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_26T04_59_46.486302 path: - '**/details_harness|gsm8k|5_2023-10-26T04-59-46.486302.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-26T04-59-46.486302.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hellaswag|10_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T17-42-58.699001.parquet' - 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'**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-04T17-42-58.699001.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-management|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-virology|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T17-42-58.699001.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_04T17_42_58.699001 path: - '**/details_harness|truthfulqa:mc|0_2023-10-04T17-42-58.699001.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-10-04T17-42-58.699001.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_26T04_59_46.486302 path: - '**/details_harness|winogrande|5_2023-10-26T04-59-46.486302.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-26T04-59-46.486302.parquet' - config_name: results data_files: - split: 2023_10_04T17_42_58.699001 path: - results_2023-10-04T17-42-58.699001.parquet - split: 2023_10_26T04_59_46.486302 path: - results_2023-10-26T04-59-46.486302.parquet - split: latest path: - results_2023-10-26T04-59-46.486302.parquet --- # Dataset Card for Evaluation run of beomi/KoRWKV-6B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/beomi/KoRWKV-6B - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [beomi/KoRWKV-6B](https://huggingface.co/beomi/KoRWKV-6B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_beomi__KoRWKV-6B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-26T04:59:46.486302](https://huggingface.co/datasets/open-llm-leaderboard/details_beomi__KoRWKV-6B/blob/main/results_2023-10-26T04-59-46.486302.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.018246644295302015, "em_stderr": 0.001370668245281319, "f1": 0.05829278523489933, "f1_stderr": 0.0018688501996275634, "acc": 0.2557221783741121, "acc_stderr": 0.007024402099929661 }, "harness|drop|3": { "em": 0.018246644295302015, "em_stderr": 0.001370668245281319, "f1": 0.05829278523489933, "f1_stderr": 0.0018688501996275634 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness|winogrande|5": { "acc": 0.5114443567482242, "acc_stderr": 0.014048804199859322 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
38,424
[ [ -0.0278167724609375, -0.048126220703125, 0.006031036376953125, 0.016265869140625, -0.01531219482421875, 0.007266998291015625, -0.0287933349609375, -0.01482391357421875, 0.0221405029296875, 0.038482666015625, -0.053375244140625, -0.06500244140625, -0.056243896484...
BangumiBase/isekaidecheatskill
2023-10-04T18:51:26.000Z
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
BangumiBase
null
null
0
0
2023-10-04T17:44:11
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Isekai De Cheat Skill This is the image base of bangumi Isekai de Cheat Skill, we detected 22 characters, 1032 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 309 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 23 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 17 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 10 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 24 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 9 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 29 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 8 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 59 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 76 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 19 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 9 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 7 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | N/A | | 13 | 16 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 6 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | N/A | N/A | | 15 | 10 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 15 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 11 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 73 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 10 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 52 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | noise | 240 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
8,131
[ [ -0.04425048828125, -0.0115814208984375, 0.00936126708984375, 0.0162200927734375, -0.017913818359375, -0.0036067962646484375, -0.0013322830200195312, -0.0258636474609375, 0.041656494140625, 0.03387451171875, -0.059600830078125, -0.053466796875, -0.04278564453125,...
BangumiBase/mawarupenguindrum
2023-10-04T19:21:03.000Z
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
BangumiBase
null
null
0
0
2023-10-04T17:50:55
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Mawaru Penguindrum This is the image base of bangumi Mawaru Penguindrum, we detected 23 characters, 1725 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 19 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 177 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 81 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 18 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 76 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 206 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 19 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 14 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 64 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 11 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 313 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 24 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 11 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 306 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 19 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 19 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 13 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 16 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 37 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 17 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 17 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 8 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | noise | 240 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
8,439
[ [ -0.0455322265625, -0.01042938232421875, 0.00725555419921875, 0.01361846923828125, -0.017578125, -0.005619049072265625, -0.002735137939453125, -0.0234222412109375, 0.0401611328125, 0.032440185546875, -0.05914306640625, -0.05059814453125, -0.04364013671875, 0....
BangumiBase/striketheblood
2023-10-04T20:43:50.000Z
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
BangumiBase
null
null
0
0
2023-10-04T17:58:32
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Strike The Blood This is the image base of bangumi Strike the Blood, we detected 66 characters, 5038 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 781 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 24 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 144 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 60 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 16 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 49 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 149 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 40 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 44 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 1115 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 70 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 55 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 128 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 121 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 14 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 31 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 48 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 26 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 31 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 53 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 124 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 51 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 89 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 21 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 24 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 54 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 28 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 31 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 26 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 36 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 14 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 19 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 13 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 60 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 19 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 8 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 9 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 178 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 18 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 32 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 105 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 210 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 77 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 49 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 11 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 23 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 34 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | ![preview 7](46/preview_7.png) | ![preview 8](46/preview_8.png) | | 47 | 13 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 14 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | 49 | 18 | [Download](49/dataset.zip) | ![preview 1](49/preview_1.png) | ![preview 2](49/preview_2.png) | ![preview 3](49/preview_3.png) | ![preview 4](49/preview_4.png) | ![preview 5](49/preview_5.png) | ![preview 6](49/preview_6.png) | ![preview 7](49/preview_7.png) | ![preview 8](49/preview_8.png) | | 50 | 8 | [Download](50/dataset.zip) | ![preview 1](50/preview_1.png) | ![preview 2](50/preview_2.png) | ![preview 3](50/preview_3.png) | ![preview 4](50/preview_4.png) | ![preview 5](50/preview_5.png) | ![preview 6](50/preview_6.png) | ![preview 7](50/preview_7.png) | ![preview 8](50/preview_8.png) | | 51 | 14 | [Download](51/dataset.zip) | ![preview 1](51/preview_1.png) | ![preview 2](51/preview_2.png) | ![preview 3](51/preview_3.png) | ![preview 4](51/preview_4.png) | ![preview 5](51/preview_5.png) | ![preview 6](51/preview_6.png) | ![preview 7](51/preview_7.png) | ![preview 8](51/preview_8.png) | | 52 | 86 | [Download](52/dataset.zip) | ![preview 1](52/preview_1.png) | ![preview 2](52/preview_2.png) | ![preview 3](52/preview_3.png) | ![preview 4](52/preview_4.png) | ![preview 5](52/preview_5.png) | ![preview 6](52/preview_6.png) | ![preview 7](52/preview_7.png) | ![preview 8](52/preview_8.png) | | 53 | 27 | [Download](53/dataset.zip) | ![preview 1](53/preview_1.png) | ![preview 2](53/preview_2.png) | ![preview 3](53/preview_3.png) | ![preview 4](53/preview_4.png) | ![preview 5](53/preview_5.png) | ![preview 6](53/preview_6.png) | ![preview 7](53/preview_7.png) | ![preview 8](53/preview_8.png) | | 54 | 12 | [Download](54/dataset.zip) | ![preview 1](54/preview_1.png) | ![preview 2](54/preview_2.png) | ![preview 3](54/preview_3.png) | ![preview 4](54/preview_4.png) | ![preview 5](54/preview_5.png) | ![preview 6](54/preview_6.png) | ![preview 7](54/preview_7.png) | ![preview 8](54/preview_8.png) | | 55 | 16 | [Download](55/dataset.zip) | ![preview 1](55/preview_1.png) | ![preview 2](55/preview_2.png) | ![preview 3](55/preview_3.png) | ![preview 4](55/preview_4.png) | ![preview 5](55/preview_5.png) | ![preview 6](55/preview_6.png) | ![preview 7](55/preview_7.png) | ![preview 8](55/preview_8.png) | | 56 | 7 | [Download](56/dataset.zip) | ![preview 1](56/preview_1.png) | ![preview 2](56/preview_2.png) | ![preview 3](56/preview_3.png) | ![preview 4](56/preview_4.png) | ![preview 5](56/preview_5.png) | ![preview 6](56/preview_6.png) | ![preview 7](56/preview_7.png) | N/A | | 57 | 16 | [Download](57/dataset.zip) | ![preview 1](57/preview_1.png) | ![preview 2](57/preview_2.png) | ![preview 3](57/preview_3.png) | ![preview 4](57/preview_4.png) | ![preview 5](57/preview_5.png) | ![preview 6](57/preview_6.png) | ![preview 7](57/preview_7.png) | ![preview 8](57/preview_8.png) | | 58 | 19 | [Download](58/dataset.zip) | ![preview 1](58/preview_1.png) | ![preview 2](58/preview_2.png) | ![preview 3](58/preview_3.png) | ![preview 4](58/preview_4.png) | ![preview 5](58/preview_5.png) | ![preview 6](58/preview_6.png) | ![preview 7](58/preview_7.png) | ![preview 8](58/preview_8.png) | | 59 | 6 | [Download](59/dataset.zip) | ![preview 1](59/preview_1.png) | ![preview 2](59/preview_2.png) | ![preview 3](59/preview_3.png) | ![preview 4](59/preview_4.png) | ![preview 5](59/preview_5.png) | ![preview 6](59/preview_6.png) | N/A | N/A | | 60 | 22 | [Download](60/dataset.zip) | ![preview 1](60/preview_1.png) | ![preview 2](60/preview_2.png) | ![preview 3](60/preview_3.png) | ![preview 4](60/preview_4.png) | ![preview 5](60/preview_5.png) | ![preview 6](60/preview_6.png) | ![preview 7](60/preview_7.png) | ![preview 8](60/preview_8.png) | | 61 | 6 | [Download](61/dataset.zip) | ![preview 1](61/preview_1.png) | ![preview 2](61/preview_2.png) | ![preview 3](61/preview_3.png) | ![preview 4](61/preview_4.png) | ![preview 5](61/preview_5.png) | ![preview 6](61/preview_6.png) | N/A | N/A | | 62 | 6 | [Download](62/dataset.zip) | ![preview 1](62/preview_1.png) | ![preview 2](62/preview_2.png) | ![preview 3](62/preview_3.png) | ![preview 4](62/preview_4.png) | ![preview 5](62/preview_5.png) | ![preview 6](62/preview_6.png) | N/A | N/A | | 63 | 16 | [Download](63/dataset.zip) | ![preview 1](63/preview_1.png) | ![preview 2](63/preview_2.png) | ![preview 3](63/preview_3.png) | ![preview 4](63/preview_4.png) | ![preview 5](63/preview_5.png) | ![preview 6](63/preview_6.png) | ![preview 7](63/preview_7.png) | ![preview 8](63/preview_8.png) | | 64 | 56 | [Download](64/dataset.zip) | ![preview 1](64/preview_1.png) | ![preview 2](64/preview_2.png) | ![preview 3](64/preview_3.png) | ![preview 4](64/preview_4.png) | ![preview 5](64/preview_5.png) | ![preview 6](64/preview_6.png) | ![preview 7](64/preview_7.png) | ![preview 8](64/preview_8.png) | | noise | 314 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
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sleepyboyeyes/Bella
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JoSw-14/chem-0-5000
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JoSw-14/chem-2-5002
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JoSw-14/chem-3-5003
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JoSw-14/chem-5-5005
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JoSw-14/chem-4-5004
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JoSw-14/chem-7-5007
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JoSw-14/chem-9-5009
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JoSw-14/chem-8-5008
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JoSw-14/chem-11-5011
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JoSw-14/chem-10-5010
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JoSw-14/chem-14-5014
2023-10-04T18:29:04.000Z
[ "region:us" ]
JoSw-14
null
null
0
0
2023-10-04T18:29:04
Entry not found
15
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