datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gsm8k
Dataset Card for GSM8K
Dataset Summary
GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning.
These problems take between 2 and 8 steps to solve.
Solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to… See the full description on the dataset page: https://huggingface.co/datasets/openai/gsm8k.OpenMathInstruct-2
OpenMathInstruct-2
OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs
generated using the Llama3.1-405B-Instruct model.
The training set problems of GSM8K
and MATH are used for constructing the dataset in the following ways:
Solution augmentation: Generating chain-of-thought solutions for training set problems in GSM8K and MATH.
Problem-Solution augmentation: Generating new problems, followed by solutions for these new problems.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-2.Ultra-FineWeb
Ultra-FineWeb
📜 Technical Report |
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM4 Series |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
Ultra-FineWeb is a large-scale, high-quality, and efficiently-filtered dataset. We use the proposed efficient verification-based high-quality filtering pipeline to the FineWeb and Chinese FineWeb datasets (source data from Chinese FineWeb-edu-v2, which includes IndustryCorpus2, MiChao, WuDao, SkyPile… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb.OpenMathReasoning
OpenMathReasoning
OpenMathReasoning is a large-scale math reasoning dataset for training large language models (LLMs).
This dataset contains
306K unique mathematical problems sourced from AoPS forums with:
3.2M long chain-of-thought (CoT) solutions
1.7M long tool-integrated reasoning (TIR) solutions
566K samples that select the most promising solution out of many candidates (GenSelect)
Additional 193K problems sourced from AoPS forums (problems only, no solutions)
We used… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathReasoning.openwebtext
Dataset Card for "openwebtext"
Dataset Summary
An open-source replication of the WebText dataset from OpenAI, that was used to train GPT-2.
This distribution was created by Aaron Gokaslan and Vanya Cohen of Brown University.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data Instances
plain_text
Size of downloaded dataset… See the full description on the dataset page: https://huggingface.co/datasets/Skylion007/openwebtext.hacker-news
Hacker News - Complete Archive
Every Hacker News item since 2006, live-updated every 5 minutes
What is it?
This dataset contains the complete Hacker News archive: every story, comment, Ask HN, Show HN, job posting, and poll ever submitted to the site. Hacker News is one of the longest-running and most influential technology communities on the internet, operated by Y Combinator since 2007. It has become the de facto gathering place for founders, engineers… See the full description on the dataset page: https://huggingface.co/datasets/open-index/hacker-news.OpenCodeInstruct
OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs
Dataset Description
We introduce OpenCodeInstruct, the largest open-access instruction tuning dataset, comprising 5 million diverse samples. OpenCodeInstruct is designed for supervised fine-tuning (SFT).
Technical Report - Discover the methodology and technical details behind OpenCodeInstruct.
Github Repo - Access the complete pipeline used to perform SFT.
This dataset is ready for… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenCodeInstruct.AutoMathText-V2
🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset
🎉 AutoMathText-v2 has surpassed 1.5 million downloads! We'd love to know how you're using it. Please take 1 minute to fill out our use case survey. Your feedback will directly shape the future roadmap of this dataset.👉 Share your use case here
📊 AutoMathText-V2 consists of 2.46 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2.UltraData-Math
UltraData-Math
🤗 Dataset | 💻 Source Code | 🇨🇳 中文 README
UltraData-Math is a large-scale, high-quality mathematical pre-training dataset totaling 290B+ tokens across three progressive tiers—L1 (170.5B tokens web corpus), L2 (33.7B tokens quality-selected), and L3 (88B tokens multi-format refined)—designed to systematically enhance mathematical reasoning in LLMs. It has been applied to the mathematical pre-training of the MiniCPM Series models.
It was introduced in… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-Math.UltraData-Code
UltraData-Code
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series |
📖 Tech Report (Coming Soon) |
🤗 UltraData-Code-L2 Classifier
English | 中文
📚 Introduction
UltraData-Code is a complete implementation of the UltraData L0-L4 tiered data management framework. It covers four code data states from L0 through L3, with each level corresponding to a distinct construction stage. The pipeline starts from approximately 192 million public GitHub… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-Code.Lucie-Training-Dataset
Lucie Training Dataset Card
The Lucie Training Dataset is a curated collection of text data
in English, French, German, Spanish and Italian culled from a variety of sources including: web data, video subtitles, academic papers,
digital books, newspapers, and magazines, some of which were processed by Optical Character Recognition (OCR). It also contains samples of diverse programming languages.
The Lucie Training Dataset was used to pretrain Lucie-7B,
a foundation LLM with… See the full description on the dataset page: https://huggingface.co/datasets/OpenLLM-France/Lucie-Training-Dataset.Ultra-FineWeb-L1
Ultra-FineWeb-L1
📜 Ultra-FineWeb Technical Report |
📦 UltraData Collection |
🌐 UltraData
English |
中文
📚 Introduction
Ultra-FineWeb-L1 is a large-scale English web corpus built from Common Crawl snapshots. Within UltraData's L0-L4 tiered data management framework, it serves as the L1 filtered layer for general web data and provides the foundation for subsequent L2 selection and L3 refinement. Building on the FineWeb processing pipeline, we perform… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb-L1.UltraData-SFT-2605
UltraData-SFT-2605
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-SFT-2605 is the full set of core-domain SFT data used in the post-training of MiniCPM5-1B-SFT within the MiniCPM5-1B series, and a key representative of L3 refined data in the UltraData L0-L4 tiered data management framework. It covers math, code, knowledge, instruction following, and other core domains, containing over 15 million Deep… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-SFT-2605.Ultra-FineWeb-L3
Ultra-FineWeb-L3
📜 Ultra-FineWeb Technical Report |
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
Ultra-FineWeb-L3 is the L3 refined data for general high-quality web data within UltraData's L0-L4 tiered data management framework. Moving beyond L2 quality selection, it transforms high-value web corpora into structured, high-learnability training data with clearer reasoning signals and richer educational… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb-L3.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
Our latest model, the first 7B to score better overall than all… See the full description on the dataset page: https://huggingface.co/datasets/Open-Orca/OpenOrca.OpenThoughts3-1.2M
paper |
dataset |
model
[!NOTE]
We have released a paper for OpenThoughts! See our paper here.
OpenThoughts3-1.2M
Open-source state-of-the-art reasoning dataset with 1.2M rows. 🚀
OpenThoughts3-1.2M is the third iteration in our line of OpenThoughts datasets, building on our previous OpenThoughts-114k and OpenThoughts2-1M.
This time around, we scale even further and generate our dataset in a much more systematic way -- OpenThoughts3-1.2M is the result of a… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts3-1.2M.UltraData-SFT-Agent-2609
UltraData-SFT-Agent-2609
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-SFT-Agent-2609 is the L3 refined data for Agent instruction-tuning within UltraData's L0-L4 tiered data management framework. Built for the post-training of MiniCPM5-2B, it complements UltraData-SFT-2605 (core-domain SFT) with executable Agent trajectories. The release contains approximately 500,000 samples spanning tool use… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-SFT-Agent-2609.open-australian-legal-corpus
Open Australian Legal Corpus ⚖️
The Open Australian Legal Corpus by Isaacus, a foundational legal AI research company, is the first and only multijurisdictional open corpus of Australian legislative and judicial documents.
Comprised of 229,122 texts totalling over 60 million lines and 1.4 billion tokens, the Corpus includes every in force statute and regulation in the Commonwealth, New South Wales, Queensland, Western Australia, South Australia, Tasmania and Norfolk Island, in… See the full description on the dataset page: https://huggingface.co/datasets/isaacus/open-australian-legal-corpus.AICC🔧 🔧 Our New-Gen Html Parser MinerU-HTML Now Realease!
AICC: AI-ready Common Crawl Dataset
Paper | Project page
News
[2025-12-24] 🔥 CC-MinerU-Code Updated! We have updated our specialized high-quality code dataset CC-MinerU-Code, containing 4.58M samples, also extracted from the full Common Crawl corpus.
Download: CC-MinerU-Code
Each record includes language, code_language, and Markdown-formatted content with fenced code blocks. Here is a sample:
{… See the full description on the dataset page: https://huggingface.co/datasets/opendatalab/AICC.chinese-fineweb-edu
This version is deprecated. We recommend you to use the newest version Fineweb-edu-chinese-v2.1 !
Chinese Fineweb Edu Dataset [中文] [English]
[OpenCSG Community] [👾github] [wechat] [Twitter]
📖Technical Report
Chinese Fineweb Edu dataset is a meticulously constructed high-quality Chinese pre-training corpus, specifically designed for natural language processing tasks in the education domain. This dataset undergoes a rigorous selection and… See the full description on the dataset page: https://huggingface.co/datasets/opencsg/chinese-fineweb-edu.UltraX-Preview
UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing
📜 Paper |
💻 Code |
🤖 Models |
📦 UltraData Collection
English |
中文
📚 Introduction
UltraX is a function-calling refinement framework for large-scale pre-training data that adaptively generates and executes editing functions for efficient instance-wise refinement. Unlike rule-based or end-to-end LLM rewriting methods, UltraX trains a lightweight… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraX-Preview.Mixture-of-Thoughts
Dataset summary
Mixture-of-Thoughts is a curated dataset of 350k verified reasoning traces distilled from DeepSeek-R1. The dataset spans tasks in mathematics, coding, and science, and is designed to teach language models to reason step-by-step. It was used in the Open R1 project to train OpenR1-Distill-7B, an SFT model that replicates the reasoning capabilities of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B from the same base model.
To load the dataset, run:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts.OpenCodeReasoning
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding
Data Overview
OpenCodeReasoning is the largest reasoning-based synthetic dataset to date for coding, comprises 735,255 samples in Python across 28,319 unique competitive programming
questions. OpenCodeReasoning is designed for supervised fine-tuning (SFT).
Technical Report - Discover the methodology and technical details behind OpenCodeReasoning.
Github Repo - Access the complete pipeline used to… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenCodeReasoning.UltraFeedback
Introduction
GitHub Repo
UltraRM-13b
UltraCM-13b
UltraFeedback is a large-scale, fine-grained, diverse preference dataset, used for training powerful reward models and critic models. We collect about 64k prompts from diverse resources (including UltraChat, ShareGPT, Evol-Instruct, TruthfulQA, FalseQA, and FLAN). We then use these prompts to query multiple LLMs (see Table for model lists) and generate 4 different responses for each prompt, resulting in a total of 256k samples.
To… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraFeedback.flores_plus
Dataset Card for FLORES+
FLORES+ is an evaluation benchmark dataset for multilingual machine translation.
Dataset Details
Dataset Description
FLORES+ is a multilingual machine translation benchmark released under CC BY-SA 4.0. This dataset was originally released by FAIR researchers at Meta under the name FLORES. Further information about these initial releases can be found in Dataset Sources below. The data is now being managed by OLDI, the Open… See the full description on the dataset page: https://huggingface.co/datasets/openlanguagedata/flores_plus.open-schematics
Open Schematics Dataset
The largest dataset of electronic schematics and PCB layouts on the internet, built as an engineering reference for schematic and PCB layout work. It's a self-growing, autonomous dataset that continuously scans the web for new engineering designs and updates itself accordingly.
Dataset Description
Each record corresponds to one schematic file and includes the raw source, rendered images, structured metadata, and all associated PCB files… See the full description on the dataset page: https://huggingface.co/datasets/bshada/open-schematics.TaskTrove
TaskTrove
v5.1 (current) — independent-review source retirement — moves 15 sources with majority or unanimous REJECT verdicts out of the default config and into deprecated/. Three blinded reviewers each sampled 10 tasks per source from all 50 v5.0 source-drop candidates, read the instructions and packaged tests, and issued independent KEEP or REJECT verdicts. The 15 retired sources received at least two REJECT votes. The active catalog changes from 93 sources and 1,674,033… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/TaskTrove.OpenMathInstruct-1
OpenMathInstruct-1
OpenMathInstruct-1 is a math instruction tuning dataset with 1.8M problem-solution pairs
generated using permissively licensed Mixtral-8x7B model.
The problems are from GSM8K
and MATH training subsets and the solutions
are synthetically generated by allowing Mixtral model to use a mix of text reasoning and
code blocks executed by Python interpreter.
The dataset is split into train and validation subsets that we used in the ablations experiments.
These two subsets… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-1.AgentTrove
AgentTrove
AgentTrove is the largest open-source collection of agentic interaction traces to date, released by the OpenThoughts-Agent team. It contains 1,696,847 rows drawn from 219 source datasets spanning code repair, shell scripting, mathematical problem-solving, competitive programming, and general computer-use tasks.
At 1.7 million rows, AgentTrove is 4× the size of the Nemotron Terminal Corpus (430 K rows), the previous largest open-source agentic trace dataset.… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/AgentTrove.nvidia-OpenCodeInstruct-refined
nvidia-OpenCodeInstruct-refined
A strictly quality-filtered subset of nvidia/OpenCodeInstruct (5M examples). This is a strict subset of EER6/nvidia-OpenCodeInstruct-broad.
Filtering criteria
Both conditions must be satisfied:
Criterion
Threshold
LLM judge min score
= 5 (out of 5)
Unit test pass rate (average_test_score)
= 1.0
LLM judge min score is the minimum across all three dimensions in the llm_judgement field:
requirement_conformance — does the… See the full description on the dataset page: https://huggingface.co/datasets/EER6/nvidia-OpenCodeInstruct-refined.