datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
met-office-uk-deterministic-solar
Met Office UK Deterministic Dataset (Zarr Format)
Description
This dataset is a subset of the Met Office UK Deterministic Dataset, converted from the original NetCDF format into Zarr format for modern data analysis. The Zarr files are packaged as .zarr.zip archives for efficient storage and transfer.
The subset focuses on specific variables and configurations, which are detailed below. Researchers and developers can use this subset for applications in climate science… See the full description on the dataset page: https://huggingface.co/datasets/openclimatefix/met-office-uk-deterministic-solar.poly-sol-orderbookSolarWM-Data
SolarWM-Data
SolarWM-Data is a reusable video-data foundation for camera-conditioned
world-model research. The main Hugging Face repository publishes portable
release controls, licenses, deterministic test indexes, and directly readable
format examples. It also contains the SolarWM-Data-Annotation/
reconstruction package. The full raw video and preencoded latent payloads are
distributed separately because of their size and upstream terms.
Project Page: SolarWM
SolarWM-Data/… See the full description on the dataset page: https://huggingface.co/datasets/junchaoh-cs/SolarWM-Data.SOL-ExecBench
Dataset Description
SOL (Speed Of Light) ExecBench is a real-world CUDA kernel benchmarking dataset of 235 kernel-level computational workload specifications derived from open-source HuggingFace model architectures. The problems span a wide range of AI model workloads — covering text, vision, and speech models' forward and backward passes — and include core algorithms such as matrix multiplications, convolutions, attention variants, mixture-of-experts, and norms across FP32, BF16… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/SOL-ExecBench.distill_r1_qwen_math_1.5b_128_solns_math_verificationsmath-dataset-measuring-mathematical-problem-solvingTo cite the dataset please reference it as
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt},
journal={NeurIPS},
year={2021}
}
autoresearch-solo-vs-forum
Solo vs forum: long-horizon coding-agent runs on 12 research-engineering tasks
1334 runs (186 solo, 1148 forum), 9841 agent trials, 8975 transcripts, 209088 forum posts; 29772 files, 36.7 GB. Models: deepseek-v4.1-flash, glm-5.2, gpt-5.6-sol, qwen3.8-27b. Tasks: actlearn, adplace, borden, carleson, dabic, exploit, graph, kda, mega, moe, swinmlp, topopt.
What the experiment is
Each agent is a coding-agent CLI (Claude Code for Qwen3.8-27B / DeepSeek-V4.1-Flash /… See the full description on the dataset page: https://huggingface.co/datasets/junlinw/autoresearch-solo-vs-forum.SOLE
Segment Any 3D Object with Language
Seungjun Lee* ·
Yuyang Zhao* ·
Gim Hee Lee
National University of Singapore
*equal contribution
ICLR 2025
Code | Paper | Project Page
SOLE is highly generalizable and can segment corresponding instances with various language instructions, including but not limited to visual questions, attributes description, and functional description.
In this repository, we provide the preprocessed data and official… See the full description on the dataset page: https://huggingface.co/datasets/onandon/SOLE.solfunmeme
SOLFUNMEME DAO — Join the Federal Model
Token: BwUTq7fS6sfUmHDwAiCQZ3asSiPEapW5zDrsbwtapump
Supply: 999,791,488.86 tokens (mint renounced, no freeze)
Status
Metric
Value
TX signatures indexed
2,668,036
TX details cached
135,563 (5.1%)
Unique actors
5,119
Active wallets
659
Liquidity pools
2 (Meteora DLMM + Raydium CLMM)
Lean4 proofs
5 modules, all verified
Governance — US Federal Model
Chamber
Holders
Threshold
Role… See the full description on the dataset page: https://huggingface.co/datasets/introspector/solfunmeme.leetcode-problem-solutions
LeetCode Solution Dataset
This dataset contains community-contributed LeetCode solutions scraped from public discussions and solution pages, enriched with metadata such as vote counts, author info, tags, and full code content. The goal is to make high-quality, peer-reviewed coding solutions programmatically accessible for research, analysis, educational use, or developer tooling.
Column Descriptions
Column Name
Type
Description
question_slug
string
The unique… See the full description on the dataset page: https://huggingface.co/datasets/kaysss/leetcode-problem-solutions.basic-math-problems-with-step-by-step-solutionssolarchive
solarchive.org: Solana Blockchain Datasets
A clean, long-term, public archive of Solana blockchain data.
This dataset contains a complete historical archive of Solana blockchain transactions, accounts, and tokens, sourced from Google BigQuery's public Solana dataset and optimized for analysis.
🎯 What is this?
Solarchive is a free, public archive of the entire Solana blockchain, designed for:
🔬 Researchers analyzing blockchain behavior and patterns
📊 Data scientists… See the full description on the dataset page: https://huggingface.co/datasets/solarchive/solarchive.AIME-solutionsappworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4046875
Action score: 0.4703125
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.40546875
Action score: 0.475
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.39921875
Action score: 0.44375
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-t01
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-t01
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38359375
Action score: 0.4703125
Valid samples: 320/320
openthoughts_18K_solutions_R1_distill_Llama_8Bsole_training_data
This is the training dataset for SOLE-R1-8B
SOLE-R1-8B is a video-language reward reasoning model for robotics. It is designed to estimate task progress from robot video frames and a natural-language task description, producing both per-timestep reasoning traces and scalar progress predictions that can be used as rewards for online robot reinforcement learning.
This dataset accompanies the paper “SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot RL” by Philip… See the full description on the dataset page: https://huggingface.co/datasets/Philip-MIT/sole_training_data.jeopardy
Jeopardy questions from Mosaic Gauntlet
Sourced from https://github.com/mosaicml/llm-foundry/blob/main/scripts/eval/local_data/world_knowledge/jeopardy_all.jsonl
Description: Jeopardy consists of 2,117 Jeopardy questions separated into 5 categories:
Literature, American History, World History, Word Origins, and Science. The model is expected
to give the exact correct response to the question. It was custom curated by MosaicML from a
larger Jeopardy set available on Huggingface.… See the full description on the dataset page: https://huggingface.co/datasets/soldni/jeopardy.olympiad-math-stepwise-solutions-llama3-20kThe MATH dataset is a collection of 20,300 problems from AMC and AIME competitions covering algebra, number theory, geometry, and precalculus problems and solution sets.
Problems and solutions are formatted in LATEX.
Step-by-step solutions and insight sections have been added in order to use a chain of thought to clarify the problem and solution.
solana-dex-execution
Solana DEX quotes and routing
Jupiter swap quotes at fixed SOL input sizes, with the route legs returned for each quote. The panel supports comparisons of quoted output, reported price impact and routing across sizes and observation times.
Contents
Table
Record
solana_swap_quotes
A pair and input amount, with quoted output, price impact, value and route-leg count
solana_swap_routes
A leg of the chosen route, including venue, amounts and allocation… See the full description on the dataset page: https://huggingface.co/datasets/dataforge-labs/solana-dex-execution.roboprobe-gpt55-rollouts
RoboProbe GPT-5.5 Rollouts
Camera videos, raw planner traces, and generated viewer manifests used by
roboprobe-console.
Planner condition: gpt55
Cameras: head, left wrist, right wrist
Browser: companion Hugging Face Static Space
distill_r1_qwen_math_1.5b_128_solns_math_trainGLIDE_SOL_DORTMUNDsolar-flare-hmi-datasetsol-max-opusnode-data
sol-max-opusnode-data
Training data built by the AgentPTB arm for cell sol-max-opusnode — Codex / gpt-5.6-sol @ effort max.
This is the corpus the arm itself assembled during its 100-hour run: what it downloaded,
filtered, rewrote and mixed. It is the input side of the checkpoints published as
agentic-ptb/sol-max-opusnode.h*, and the companion to the run record in agentic-ptb/sol-max-opusnode-record.
field
value
plot cell
sol-max-opusnode
driver
Codex / gpt-5.6-sol… See the full description on the dataset page: https://huggingface.co/datasets/agentic-ptb/sol-max-opusnode-data.test-dwd-globalSKIPPD
Citation
If you find SKIPP'D useful to your research, please cite:
Nie, Y., Li, X., Scott, A., Sun, Y., Venugopal, V., & Brandt, A. (2023). SKIPP’D: A SKy Images and Photovoltaic Power Generation Dataset for short-term solar forecasting. Solar Energy, 255, 171-179.
or
@article{nie2023skipp,
title={SKIPP’D: A SKy Images and Photovoltaic Power Generation Dataset for short-term solar forecasting},
author={Nie, Yuhao and Li, Xiatong and Scott, Andea and Sun, Yuchi and Venugopal… See the full description on the dataset page: https://huggingface.co/datasets/solarbench/SKIPPD.qwen35-4b-filter-solvability-200-qwen38-27b-newprompt-4k-epoch4
qwen35-4b-filter-solvability-200-qwen38-27b-newprompt-4k-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.40234375
Action score: 0.421875
Valid samples: 320/320