datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
r15-ai-search-metamerism
R15: AI Search Metamerism — Cross-Cultural Brand Perception Dataset
Citation: Zharnikov, D. (2026v) | DOI: 10.5281/zenodo.19422427 | Version: v3.2.0
Dataset Summary
This dataset contains the full session logs, aggregated results, and analysis outputs from the R15 large-scale experiment testing whether Large Language Models systematically collapse multi-dimensional brand perception into Economic and Experiential dimensions ("spectral metamerism"). It comprises 21… See the full description on the dataset page: https://huggingface.co/datasets/spectralbranding/r15-ai-search-metamerism.Raiden-DeepSeek-R1Click here to support our open-source dataset and model releases!
Raiden-DeepSeek-R1 is a dataset containing creative-reasoning and analytic-reasoning responses, testing the limits of DeepSeek R1's reasoning skills!
This dataset contains:
63k 'creative_content' and 'analytical_reasoning' prompts from microsoft/orca-agentinstruct-1M-v1, with all responses generated by deepseek-ai/DeepSeek-R1.
Responses demonstrate the reasoning capabilities of DeepSeek's 685b parameter R1 reasoning model.… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Raiden-DeepSeek-R1.Titanium2-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
32.4k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Titanium2-DeepSeek-R1.Celestia3-DeepSeek-R1-0528Click here to support our open-source dataset and model releases!
Celestia3-DeepSeek-R1-0528 is a dataset focused on science, testing the limits of DeepSeek R1 0528's science-reasoning skills!
This dataset contains:
90.9k synthetically generated science prompts, with all responses generated using DeepSeek R1 0528.
Primary subjects are physics, chemistry, biology, and computer science; secondary subjects include Earth science, astronomy, and information theory.
All prompts are synthetic, taken… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Celestia3-DeepSeek-R1-0528.Fast-Math-R1-SFTThis repository contains the First stage SFT dataset as presented in the paper A Practical Two-Stage Recipe for Mathematical LLMs: Maximizing Accuracy with SFT and Efficiency with Reinforcement Learning.
This dataset is used for the intensive Supervised Fine-Tuning (SFT) phase, crucial for pushing the model's mathematical accuracy.
Project GitHub Repository: https://github.com/RabotniKuma/Kaggle-AIMO-Progress-Prize-2-9th-Place-Solution
Dataset Construction
This dataset was… See the full description on the dataset page: https://huggingface.co/datasets/RabotniKuma/Fast-Math-R1-SFT.DAG-Reasoning-DeepSeek-R1-0528Click here to support our open-source dataset and model releases!
DAG-Reasoning-DeepSeek-R1-0528 is a dataset focused on analysis and reasoning, creating directed acyclic graphs testing the limits of DeepSeek R1 0528's graph-reasoning skills!
This dataset contains:
4.08k synthetically generated prompts to create directed acyclic graphs in response to user input, with all responses generated using DeepSeek R1 0528.
All responses contain a multi-step thinking process to perform effective… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/DAG-Reasoning-DeepSeek-R1-0528.Titanium2.1-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2.1-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
31.7k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Titanium2.1-DeepSeek-R1.Fast-Math-R1-GRPOThis repository contains the second-stage GRPO dataset for the paper A Practical Two-Stage Recipe for Mathematical LLMs: Maximizing Accuracy with SFT and Efficiency with Reinforcement Learning.
This dataset is crucial for the second stage of the training recipe, aiming to improve token efficiency while preserving peak mathematical reasoning performance in Large Language Models (LLMs) through Reinforcement Learning from online inference (GRPO).
We extracted the answers from the 2nd stage SFT… See the full description on the dataset page: https://huggingface.co/datasets/RabotniKuma/Fast-Math-R1-GRPO.Mitakihara-DeepSeek-R1-0528Click here to support our open-source dataset and model releases!
Mitakihara-DeepSeek-R1-0528 is a dataset focused on artificial intelligence, testing the limits of DeepSeek R1 0528's AI-reasoning skills!
This dataset contains:
16.9k synthetically generated prompts about AI, with all responses generated using DeepSeek R1 0528.
Subjects include computer science, artificial intelligence, MLOps, LLMs and diffusion models, math and CUDA, cutting-edge and future technologies, complex adaptive and… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Mitakihara-DeepSeek-R1-0528.Titanium2-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
32.4k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/gravermistakes/Titanium2-DeepSeek-R1.Tachibana2-DeepSeek-R1Click here to support our open-source dataset and model releases!
Tachibana2-DeepSeek-R1 is a code-reasoning dataset, testing the limits of DeepSeek R1's coding skills!
This dataset contains:
27.2k synthetically generated code-reasoning prompts. All responses are generated using DeepSeek R1.
Synthetic prompts are generated using Llama 3.1 405b Instruct, based on the original sequelbox/Tachibana dataset with increased task complexity.
Responses demonstrate the code-reasoning capabilities of… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Tachibana2-DeepSeek-R1.Celestia3-DeepSeek-R1-0528-PREVIEWClick here to support our open-source dataset and model releases!
This is an early sneak preview of Celestia3-DeepSeek-R1-0528, containing the first 13.4k rows!
Celestia3-DeepSeek-R1-0528 is a dataset focused on science, testing the limits of DeepSeek R1's science-reasoning skills!
This early preview release contains:
13.4k synthetically generated science prompts. All responses are generated using DeepSeek R1 0528.
Primary subjects are physics, chemistry, biology, and computer science;… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Celestia3-DeepSeek-R1-0528-PREVIEW.dumy-zno-ukrainian-math-history-geo-r1-o1
DUMY («Думи»): Ukrainian Multidomain Reasoning Dataset (Part 1: ZNO/NMT tasks with DeepSeek R1 and OpenAI o1 answers)
DUMY is an open benchmark and dataset designed for training, distillation, and evaluation of language models focused on Ukrainian reasoning tasks.
The word “Dumy” comes from Taras Shevchenko’s famous poem and literally means “thoughts” in Ukrainian:
Думи мої, думи мої,
Лихо мені з вами!
Нащо стали на папері
Сумними рядами?..
Work in progress. Stay tuned.… See the full description on the dataset page: https://huggingface.co/datasets/NLPForUA/dumy-zno-ukrainian-math-history-geo-r1-o1.ua-codeforces-cots-open-r1
Dataset Summary
ua-codeforces-cots-open-r1 is a Ukrainian-focused derivative of open-r1/codeforces-cots that:
includes 1550 Python solutions from original dataset generated by DeepSeek-R1;
adds Ukrainian translations of Codeforces task statements, I/O formats, notes, and editorials;
provides Ukrainian translation of original ("high") reasoning obtained with DeepSeek-V3;
adds “low” reasoning in Ukrainian by DeepSeek-R1 based on original reasoning and task statements;
ships… See the full description on the dataset page: https://huggingface.co/datasets/anon-researcher-ua/ua-codeforces-cots-open-r1.