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}Hugging Face Datasets2026 · Table · Parquet
FineEnvs/SmolDataEnvs📈 SmolDataEnvs 5.5K+ RL tasks for hill-climbing small models in code and data science. A 2B model on these tasks. Left: what it optimises. Right: 144 held-out tasks it never trains on. Two runs over the same 5,000 tasks: shuffled against a curriculum ordered easiest to hardest. Data-analysis tasks as a plain, load-and-go dataset: no runtime, no framework required. Each row is one self-contained ta
Hugging Face Datasets2026 · Image
China Universities DatasetChina Universities Dataset 🎓 582 Chinese universities — names (English + 中文), city, province, category, 985/211/双一流 tags, logos, and ShanghaiRanking (软科中国大学排名) 2026 national ranks, scores, and institution-page links. Shipped as ready-to-use JSON · CSV · SQL, no scraping needed. One import and you have a structured Chinese university database: searchable slugs, province→city geography, prestige tag
Hugging Face Datasets2026 · Image
DAREBench: Deployment-Aware and Reliable Evaluation of Models as AgentsDAREBench DAREBench (Deployment-Aware and Reliable Evaluation of Models as Agents) is a workload- and deployment-aware benchmark for evaluating models as agents. Built on a shared OpenClaw execution environment, it organizes 233 tasks selected and adapted from 22 source benchmarks into a 2×3 workload matrix defined by input modality and execution form, and evaluates them under a unified contract-b
Hugging Face Datasets2026 · Table · Parquet
datalab-to/omni_extract_benchOmni Extract Bench We weren’t satisfied with the current benchmarking options for extraction. They were biased, didn’t use realistic data and were hard to audit. Our view is that an extraction benchmark should do two things: Help customers choose the right vendor; and Give engineers a way to diagnose what’s actually going wrong in a given model. That’s why we built OmniExtractBench. OmniExtractBen
Hugging Face Datasets2026 · Image
Ledgerthe LEDGER Long-Context Multi-KPI extraction datasets and benchmarks. OCR'd annual reports with ground-truth KPI values for financial information extraction benchmarking. Dataset Description This dataset pairs OCR-extracted annual report text (from DeepSeek OCR) with structured KPI ground-truth values. It is designed for evaluating LLM-based financial information extraction, retrieval, and needle-
Hugging Face Datasets2026 · dataset
DartLab 전자공시 데이터DartLab 데이터 종목코드 하나로 읽는 한국 DART + 미국 SEC EDGAR 공시 데이터 Structured Korean (DART) and US (SEC EDGAR) disclosure data, ready as Parquet. 무엇인가요? DartLab이 한국 DART 전자공시와 미국 SEC EDGAR 공시를 종목코드 하나로 비교 가능한 표로 가공해 Parquet으로 올려둔 데이터셋입니다. 한국 전 상장사(약 2,700사)와 미국 주요 상장사(약 1,000사)의 재무제표, 사업보고서 본문, 정형 공시, 주가, 거시지표가 들어 있습니다. 이 데이터셋은 DartLab의 데이터 층입니다. dartlab.Company("005930")을 호출하면 라이브러리가 필요한 parquet을 여기서 자동으로 내려받
Hugging Face Datasets2026 · Image
ibm-granite/ChartNetChartNet: A Million-Scale Multimodal Dataset for Chart Understanding 🌐 Homepage | 📖 arXiv 📝 Changelog June 3, 2026 — Release of grounded_qa subset and completed reasoning subset (both subject to Notice Regarding Data Availability) May 15, 2026 — Added link to 30K real-world charts and detailed captions dataset released by our collaborators Abaka AI/2077AI. April 29, 2026 — Release of an additional
Hugging Face Datasets2026 · Table · CSV
ChameleonHugging Face Datasets2025 · Text
birdsql/bird_mini_devBIRD-SQL Mini-Dev Update 2025-07-04 We are grateful for the valuable feedback from the community over the past year regarding BIRD Mini-Dev. Based on your suggestions, we have made significant updates to the BIRD Mini-Dev dataset. For New Users If you are new to BIRD Mini-Dev, you can download the complete databases and datasets using the following link: Download BIRD Mini-Dev Complete Package For
Hugging Face Datasets2025 · Table · Parquet
philschmid/gretel-synthetic-text-to-sqlFork of gretelai/synthetic_text_to_sql The gretelai/synthetic_text_to_sql dataset is a large, Apache 2.0 licensed, synthetic Text-to-SQL dataset consisting of 105,851 high-quality records across 100 diverse domains, designed for training language models. It includes comprehensive SQL tasks with varying complexities, database contexts, natural language explanations, and contextual tags, outperformi
Hugging Face Datasets2024 · Table · Parquet · gated
Turkish MMLU: Yapay Zeka ve Akademik Uygulamalar İçin En Kapsamlı ve Özgün Türkçe Veri SetiTurkish MMLU: Yapay Zeka ve Akademik Uygulamalar İçin En Kapsamlı ve Özgün Türkçe Veri Seti Önemli Not: Bu veri setini kullananların, özellikle Zenodo üzerinden alıntı yapmaları büyük önem taşımaktadır. Zenodo üzerinden yapılan alıntılar, veri setimizin bilimsel olarak daha geniş bir çevrede tanınmasını ve indekslenmesini sağlayacaktır. Lütfen aşağıdaki Zenodo DOI numarasını kullanarak veri setine
Hugging Face Datasets2024 · Table · CSV
Bitext - Telco Tagged Training Dataset for LLM-based Virtual AssistantsBitext - 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 easil
Hugging Face Datasets2024 · Table · CSV
Bitext - Insurance Tagged Training Dataset for LLM-based Virtual AssistantsBitext - 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
Hugging Face Datasets2024 · Text
proj-persona/PersonaHubScaling Synthetic Data Creation with 1,000,000,000 Personas This repo releases data introduced in our paper Scaling Synthetic Data Creation with 1,000,000,000 Personas: We propose a novel persona-driven data synthesis methodology that leverages various perspectives within a large language model (LLM) to create diverse synthetic data. To fully exploit this methodology at scale, we introduce PERSONA
Hugging Face Datasets2024 · Table · Parquet
Code général des impôtsCode général des impôts, non-instruct (2025-09-20) The objective of this project is to provide researchers, professionals and law students with simplified, up-to-date access to all French legal texts, enriched with a wealth of data to facilitate their integration into Community and European projects. Normally, the data is refreshed daily on all legal codes, and aims to simplify the production of t
Hugging Face Datasets2023 · Table · Parquet
Code civilCode civil, non-instruct (2025-09-20) The objective of this project is to provide researchers, professionals and law students with simplified, up-to-date access to all French legal texts, enriched with a wealth of data to facilitate their integration into Community and European projects. Normally, the data is refreshed daily on all legal codes, and aims to simplify the production of training sets
Hugging Face Datasets2023 · Table · CSV
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual AssistantsBitext - 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
Hugging Face Datasets2023 · dataset · gated
Dialog StudioDialogStudio: Unified Dialog Datasets and Instruction-Aware Models for Conversational AI Author: Jianguo Zhang, Kun Qian Paper|Github|[GDrive] 🎉 March 18, 2024: Update for AI Agent. Check xLAM for the latest data and models relevant to AI Agent! 🎉 March 10 2024: Update for dataset viewer issues: Please refer to https://github.com/salesforce/DialogStudio for view of each dataset, where we provide 5
Hugging Face Datasets2023 · Table · Parquet
OpenOrca🐋 The OpenOrca Dataset! 🐋 We are thrilled to announce the release of the OpenOrca dataset! This rich collection of augmented FLAN data aligns, as best as possible, with the distributions outlined in the Orca paper. It has been instrumental in generating high-performing model checkpoints and serves as a valuable resource for all NLP researchers and developers! Official Models Mistral-7B-OpenOrca Ou
Hugging Face Datasets2023 · Table · CSV
ChatGPT Jailbreak PromptsDataset Card for Dataset Name Name ChatGPT Jailbreak Prompts Dataset Summary ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT. Languages [English]
Hugging Face Datasets2022 · Text
UnpredicTable-support-google-comThe UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
Hugging Face Datasets2022 · Text
UnpredicTable-5kThe UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
Hugging Face Datasets2022 · Text
UnpredicTable-uniqueThe UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
Hugging Face Datasets2022 · Text
UnpredicTable-fullThe UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
Hugging Face Datasets2022 · Text
UnpredicTable-rated-mediumThe UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.