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datasets

Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

modalityAllTextImageAudioTabularVideo
taskAllText generationQuestion answeringImage classificationSpeech
sizeAllUnder 1K1K – 10K100K – 1M1M – 10M
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01LLMDH /marianne_pdf_7text10K<n<100K0 likes3.1k downloads2y agoHugging Face02LLMDH /marianne_pdf_9text100K<n<1M0 likes2.6k downloads2y agoHugging Face03LLMDH /marianne_pdf_5text100K<n<1M0 likes2.2k downloads2y agoHugging Face04LLMDH /marianne_pdf_3text100K<n<1M0 likes2.2k downloads2y agoHugging Face05LLMDH /marianne_pdf_8text100K<n<1M0 likes1.7k downloads2y agoHugging Face06LLMDH /marianne_pdf_4text10K<n<100K0 likes1.6k downloads2y agoHugging Face07LLMDH /marianne_pdf_10text100K<n<1M0 likes617 downloads2y agoHugging Face08LLMDH /hal_pdf_extratext10K<n<100K0 likes421 downloads2y agoHugging Face09mispeech /xares_llm_dataaudioaudio-classification1M<n<10M4 likes354 downloads11mo agoHugging Face10tdro-llm /finetune_data tdro-llm/finetune_data tDRO: Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval. Guangyuan Ma, Yongliang Ma, Xing Wu, Zhenpeng Su, Ming Zhou and Songlin Hu. This repo contains all fine-tuning data for Large Language Model-based Dense Retrieval. Please refer to this repo for details to reproduce. A total of 25 heterogeneous retrieval fine-tuning datasets with Hard Negatives and Deduplication (with test sets) are listed as belows.… See the full description on the dataset page: https://huggingface.co/datasets/tdro-llm/finetune_data.textn<1K0 likes250 downloads1y agoHugging Face11matsuo-lab /JP-LLM-Corpus-PII-Filtered-10B CommonCrawl Japanese (Filtered PPI) Dataset 本データセットは、CommonCrawlより抽出した約100億（10B）トークン規模の日本語テキストデータから、特に配慮が必要な「要配慮個人情報」をフィルタリング処理したものです。 データセットの概要 元データソース: CommonCrawl（https://commoncrawl.org/） トークン数: 約10Bトークン 言語: 日本語 処理内容: 要配慮個人情報をルールベースおよび機械学習分類器を用いてフィルタリング フィルタリングには以下のコードを使用しております。https://github.com/matsuolab/jp-llm-corpus-pii-filter/ 注意事項 本データセットは、非常に大規模なテキストから自動的に要配慮個人情報を除去したものであり、完全な排除を保証するものではありません。そのため、二次的な活用に際しては、目的に応じた適切な管理・配慮が必要です。… See the full description on the dataset page: https://huggingface.co/datasets/matsuo-lab/JP-LLM-Corpus-PII-Filtered-10B.text10K<n<100K1 likes143 downloads1y agoHugging Face12DaYuDaYu /LLMMultiLabelimage100K<n<1M0 likes94 downloads2y agoHugging Face13transZ /efficient_llm Data V4 for NeurIPS LLM Challenge Contains 70949 samples collected from Huggingface: Math: 1273 gsm8k math_qa math-eval/TAL-SCQ5K TAL-SCQ5K-EN meta-math/MetaMathQA TIGER-Lab/MathInstruct Science: 42513 lighteval/mmlu - 'all', "split": 'auxiliary_train' lighteval/bbq_helm - 'all' openbookqa - 'main' ComplexQA: 2940 ARC-Challenge ARC-Easy piqa social_i_qa Muennighoff/babi Rowan/hellaswag ComplexQA1: 2060 medmcqa winogrande_xl, winogrande_debiased boolq sciq CNN: 2787… See the full description on the dataset page: https://huggingface.co/datasets/transZ/efficient_llm.texttext-generationn<1K0 likes17 downloads3y agoHugging Face14nishadsinghi /LCB128_Llama3.1-8B-Inst_LLM-as-judge_256_32text10K<n<100K0 likes9 downloads2y agoHugging Face15angadsinghh /create_llm_from_scratchtextn<1K0 likes7 downloads2y agoHugging Face16FreDERicia /LLM_SAFETY_CHECK_OODgatedtext10M<n<100M0 likes1 downloads5mo agoHugging Face

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