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

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01bench-llm /or-bench OR-Bench: An Over-Refusal Benchmark for Large Language Models Please see our demo at HuggingFace Spaces. Overall Plots of Model Performances Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic prompts and least number of safe prompts. We also plot a blue line… See the full description on the dataset page: https://huggingface.co/datasets/bench-llm/or-bench.imagetext-generation10K<n<100K22 likes9.4k downloads2y agoHugging Face02bitext /Bitext-customer-support-llm-chatbot-training-dataset Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.textquestion-answering10K<n<100K195 likes8.2k downloads2y agoHugging Face03bitext /Bitext-retail-ecommerce-llm-chatbot-training-dataset Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset.textquestion-answering10K<n<100K19 likes1.6k downloads2y agoHugging Face04bitext /Bitext-events-ticketing-llm-chatbot-training-dataset Bitext - Events and Ticketing Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [events and ticketing] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-events-ticketing-llm-chatbot-training-dataset.textquestion-answering10K<n<100K1 likes1.1k downloads2y agoHugging Face05bench-llms /or-bench OR-Bench: An Over-Refusal Benchmark for Large Language Models Please see our demo at HuggingFace Spaces. Overall Plots of Model Performances Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic prompts and least number of safe prompts. We also plot a blue line… See the full description on the dataset page: https://huggingface.co/datasets/bench-llms/or-bench.imagetext-generation10K<n<100K1 likes742 downloads2y agoHugging Face06orbench-llm /or-bench OR-Bench: An Over-Refusal Benchmark for Large Language Models Please see our leaderboard at HuggingFace Spaces. Overall Plots of Model Performances Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic prompts and least number of safe prompts. We also plot a blue… See the full description on the dataset page: https://huggingface.co/datasets/orbench-llm/or-bench.imagetext-generation10K<n<100K0 likes615 downloads2y agoHugging Face07bench-llms /or-bench-toxic-all OR-Bench: An Over-Refusal Benchmark for Large Language Models This dataset constains highly toxic prompts, use with caution!!! Please see our demo at HuggingFace Spaces. Overall Plots of Model Performances Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic… See the full description on the dataset page: https://huggingface.co/datasets/bench-llms/or-bench-toxic-all.imagetext-generation10K<n<100K1 likes357 downloads2y agoHugging Face08bitext /Bitext-telco-llm-chatbot-training-dataset Bitext - Telco Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [telco] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An overview of… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-telco-llm-chatbot-training-dataset.textquestion-answering10K<n<100K2 likes259 downloads2y agoHugging Face09bitext /Bitext-insurance-llm-chatbot-training-dataset Bitext - Insurance Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [insurance] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-insurance-llm-chatbot-training-dataset.textquestion-answering10K<n<100K8 likes221 downloads2y agoHugging Face10llm-jp /llm-jp-longbench-JEMHop llm-jp-longbench-JEMHopQA llm-jp LongBench ベンチマークについて このデータセットは，GitHub リポジトリhttps://github.com/llm-jp/llm-jp-longbenchで公開されているllm-jp LongBenchベンチマークの評価対象データセットの一部として構築されています。 llm-jp LongBench ベンチマークは，日本語大型言語モデル（LLM）のロングコンテキスト処理能力を体系的に評価することを目的としており，複数の長文コンテキスト QA データセットを含んでいます。 本データセットはその一つです。 データセット概要 本データセットは、日本語の説明可能マルチホップ質問応答データセットJEMHopQA （Ishii et al., 2024）を基に、Wikipedia記事を付与することで構築したロングコンテキストQA評価用データセットです。 最大65… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/llm-jp-longbench-JEMHop.textquestion-answeringn<1K1 likes211 downloads7mo agoHugging Face11llm-jp /llm-jp-longbench-NIILC llm-jp-longbench-NIILC llm-jp LongBench ベンチマークについて このデータセットは，GitHub リポジトリhttps://github.com/llm-jp/llm-jp-longbenchで公開されているllm-jp LongBenchベンチマークの評価対象データセットの一部として構築されています。 llm-jp LongBench ベンチマークは，日本語大型言語モデル（LLM）のロングコンテキスト処理能力を体系的に評価することを目的としており，複数の長文コンテキスト QA データセットを含んでいます。 本データセットはその一つです。 データセット概要 本データセットは，日本語質問応答データセット NIILC （Sekine, 2003）を基に， 回答が一意に定まり，かつ時間によって正解が変化しない質問のみを選別し， それらに対応する Wikipedia 記事をコンテキストとして付与することで構築した， ロングコンテキスト QA 評価用データセットです。… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/llm-jp-longbench-NIILC.textquestion-answeringn<1K1 likes202 downloads7mo agoHugging Face12bitext /Bitext-travel-llm-chatbot-training-dataset Bitext - Travel Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Travel] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An overview of… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-travel-llm-chatbot-training-dataset.textquestion-answering10K<n<100K4 likes181 downloads2y agoHugging Face13SIP-med-LLM /JMedQA JMedQA: Benchmarking Large Language Models and Vision-Language Models on the Japanese Medical Licensing Examination JMedQA is a Japanese medical question-answering benchmark derived from Japan's National Medical Examination materials publicly released by the Ministry of Health, Labour and Welfare (MHLW). The dataset supports both text-only large language model (LLM) evaluation and vision-language model (VLM) evaluation using associated examination images. Its image-dependency… See the full description on the dataset page: https://huggingface.co/datasets/SIP-med-LLM/JMedQA.imagequestion-answering1K<n<10K0 likes155 downloads1mo agoHugging Face14llm-jp /jgpqagated JGPQA This repository provides GPQA dataset translated from English into Japanese by LLM-jp, a collaborative project launched in Japan. The dataset was translated from English to Japanese using machine translation, then checked and corrected by external experts. The links of the original GPQA dataset are here(HuggingFace). Send Questions to llm-jp(at)nii.ac.jp Model Card Authors Yuji Tamakoshi, Kouta Nakayama, Yusuke Miyao. textquestion-answering1K<n<10K3 likes146 downloads1y agoHugging Face15chrislimbe /pubmedqa-recursive-llm-degradation-qwen2.5-0.5b PubMedQA Recursive LLM Degradation — Qwen2.5-3B This repository contains synthetic biomedical question-answering data and model predictions generated as part of a study of recursive fine-tuning and model degradation. Base Model Qwen/Qwen2.5-3B Source Dataset The experiments use the PubMedQA dataset: qiaoxin/PubMedQA This repository contains generated/derived research artifacts and does not redistribute the original PubMedQA dataset in its entirety.… See the full description on the dataset page: https://huggingface.co/datasets/chrislimbe/pubmedqa-recursive-llm-degradation-qwen2.5-0.5b.tabularquestion-answering10K<n<100K0 likes135 downloads1d agoHugging Face16chrislimbe /pubmedqa-recursive-llm-degradation-qwen2.5-3b PubMedQA Recursive LLM Degradation — Qwen2.5-3B This repository contains synthetic biomedical question-answering data and model predictions generated as part of a study of recursive fine-tuning and model degradation. Base Model Qwen/Qwen2.5-3B Source Dataset The experiments use the PubMedQA dataset: qiaoxin/PubMedQA This repository contains generated/derived research artifacts and does not redistribute the original PubMedQA dataset in its entirety.… See the full description on the dataset page: https://huggingface.co/datasets/chrislimbe/pubmedqa-recursive-llm-degradation-qwen2.5-3b.tabularquestion-answering10K<n<100K0 likes129 downloads1d agoHugging Face17gretelai /synthetic_multilingual_llm_prompts Image generated by DALL-E. See prompt for more details 📝🌐 Synthetic Multilingual LLM Prompts Welcome to the "Synthetic Multilingual LLM Prompts" dataset! This comprehensive collection features 1,250 synthetic LLM prompts generated using Gretel Navigator, available in seven different languages. To ensure accuracy and diversity in prompts, and translation quality and consistency across the different languages, we employed Gretel Navigator both as a generation tool and as an… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/synthetic_multilingual_llm_prompts.tabulartext-generation1K<n<10K11 likes128 downloads2y agoHugging Face18rubricreward /llm-metric-mmlutextquestion-answering10K<n<100K0 likes110 downloads1y agoHugging Face19bitext /Bitext-mortgage-loans-llm-chatbot-training-dataset Bitext - Mortgage and Loans Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Mortgage and Loans] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-mortgage-loans-llm-chatbot-training-dataset.textquestion-answering10K<n<100K5 likes102 downloads2y agoHugging Face20bitext /Bitext-wealth-management-llm-chatbot-training-dataset Bitext - Wealth Management Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Wealth Management] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-wealth-management-llm-chatbot-training-dataset.textquestion-answering10K<n<100K2 likes90 downloads2y agoHugging Face21emre /TARA_Turkish_LLM_Benchmark TARA: Turkish Advanced Reasoning Assessment Veri Seti *Img Credit: Open AI ChatGPT **English version is given below.** Evaluation Notebook / Değerlendirme Not Defteri Dataset Summary TARA (Turkish Advanced Reasoning Assessment), Türkçe dilindeki Büyük Dil Modellerinin (LLM'ler) gelişmiş akıl yürütme yeteneklerini çoklu alanlarda ölçmek için tasarlanmış, zorluk derecesine göre sınıflandırılmış bir benchmark veri setidir. Bu veri seti, LLM'lerin sadece bilgi… See the full description on the dataset page: https://huggingface.co/datasets/emre/TARA_Turkish_LLM_Benchmark.textquestion-answeringn<1K28 likes90 downloads1y agoHugging Face22bitext /Bitext-hospitality-llm-chatbot-training-dataset Bitext - Hospitality Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [hospitality] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-hospitality-llm-chatbot-training-dataset.textquestion-answering10K<n<100K1 likes83 downloads2y agoHugging Face23bitext /Bitext-media-llm-chatbot-training-dataset Bitext - Media Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [media] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An overview of… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-media-llm-chatbot-training-dataset.textquestion-answering10K<n<100K0 likes76 downloads2y agoHugging Face24bitext /Bitext-restaurants-llm-chatbot-training-dataset Bitext - Restaurants Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [restaurants] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-restaurants-llm-chatbot-training-dataset.textquestion-answering10K<n<100K2 likes62 downloads2y agoHugging Face25barathanasln /turkish_llm_finetune_dataset_4_topics Turkish LLM Finetune Dataset - 4 Topics This dataset is designed to fine-tune the T3 AI Turkish LLM. It was created by Barathan Aslan, Ömer Faruk Çelik, and Batuhan Kalem for the T3 AI Hackathon. The dataset focuses on four distinct topics: Agriculture, Sustainability, Turkish Education Sytem, and Turkish Law System. Contributors Barathan Aslan (https://huggingface.co/barathanasln) Batuhan Kalem(https://huggingface.co/Pancarsuyu) Ömer Faruk Çelik… See the full description on the dataset page: https://huggingface.co/datasets/barathanasln/turkish_llm_finetune_dataset_4_topics.texttable-question-answering10K<n<100K11 likes60 downloads2y agoHugging Face26buildwithdmytro /llm-misinformation-resistance-index LLM Misinformation Resistance Index (LMRI) Formal name: LLM Misinformation Resistance Index (LMRI). Public alias: the Gaslighting Index — the two headline scores keep their code names GI-basic and GI-strict, where "GI" comes from the benchmark's public alias. LMRI measures whether a language model will stand up to its own misinformation. Each benchmark item is a fabricated conversation in which the assistant's own prior turn contains a planted false claim (or, for controls, a… See the full description on the dataset page: https://huggingface.co/datasets/buildwithdmytro/llm-misinformation-resistance-index.tabulartext-generation10K<n<100K0 likes55 downloads1mo agoHugging Face27somosnlp /LLM_SQL_BaseDatosEspanol Usos Usos directos El objetivo principal de este dataset es proporcionar ejemplos simples para el fine-tuning de modelos de procesamiento de lenguaje natural (NLP) en el contexto de consultas SQL. Usos fuera de mira Podria usarse para el entrenamiento de una IA que sirva como creadora de base de datos artificiales Estructura del conjunto de datos Question: Es la pegunta que el usuario le dara al chatbot Answer: La respuesta el que chatbot le… See the full description on the dataset page: https://huggingface.co/datasets/somosnlp/LLM_SQL_BaseDatosEspanol.textquestion-answeringn<1K10 likes51 downloads2y agoHugging Face28abhi23457 /Bitext-customer-support-llm-chatbot-training-dataset Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants Overview This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/abhi23457/Bitext-customer-support-llm-chatbot-training-dataset.textquestion-answering10K<n<100K0 likes50 downloads22d agoHugging Face29noepsl /H-LLMC2 Human Large Language Model Comparison Corpus (H-LLMC2) H-LLMC2 presents a sample of HC3 [1], extended to seven open-weight medium-sized LLMs. Description H-LLMC2 is based on a sample of HC3, balanced over the 5 data sources (reddit_eli5, finance, medicine, open_qa, and wiki_csai). 842 questions are sampled from each source (i.e, the full set of wiki_csai, and random samples for the other source), yielding a parallel dataset of 4210 question-answers sets. In addition to… See the full description on the dataset page: https://huggingface.co/datasets/noepsl/H-LLMC2.textquestion-answering1K<n<10K0 likes44 downloads10mo agoHugging Face30BCCard /bc-finance-llm-benchmark BC Card Finance LLM Benchmark 한국 금융 도메인 특화 LLM 성능 평가를 위한 벤치마크 데이터셋입니다.BC카드-연세대 DSL 산학협력(S2026 LLMOps 프로젝트)의 산출물입니다. 데이터셋 개요 항목 내용 총 문항 수 800 언어 한국어 도메인 금융 (BC카드 FAQ, 금융 일반) 형식 Question / Ground Truth 컬럼 설명 컬럼 설명 no 순번 id 문항 ID 대분류 데이터 출처 대분류 (BC카드FAQ, general 등) 금융토픽 세부 금융 토픽 문제유형 문제 유형 (단일추론, 다중추론 등) question 평가 질문 ground_truth 정답 (참조 답변) source_tag 원본 출처 문서 태그 활용 방법 LLM-as-Judge… See the full description on the dataset page: https://huggingface.co/datasets/BCCard/bc-finance-llm-benchmark.textquestion-answeringn<1K2 likes32 downloads3mo agoHugging Face

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