datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
witNOAH-mini
MOAH mini
The dataset prest here is a very samll sample of NOAH dataset.
In the original dataset each satellite image is ~650MB with 234,089 images present in 11 bands.
It is not feasible to upload the complete dataset.
A sample of the dataset across diffrent modalities can be seen in the figure below:
The diffrence between NOAH and NOAH mini is hilighted in the figure below.
Each subplot is a band of Landsat 8 in NOAH.
The region hilighted in red is the region available in NOAH… See the full description on the dataset page: https://huggingface.co/datasets/mutakabbirCarleton/NOAH-mini.open-imagesAmelia42-Mini
Dataset Overview
The Amelia42-Mini dataset provides air traffic position reports for 42 major U.S. airports, including the following airports:
KATL (Hartsfield-Jackson Atlanta International Airport)
KBDL (Bradley International Airport)
KBOS (Boston Logan International Airport)
KBWI (Baltimore/Washington International Thurgood Marshall Airport)
KCLE (Cleveland Hopkins International Airport)
KCLT (Charlotte Douglas International Airport)
KDCA (Washington National Airport)
KDEN… See the full description on the dataset page: https://huggingface.co/datasets/AmeliaCMU/Amelia42-Mini.adni-mini
ADNI mini v1.3 — SynthSeg-masked
This is a local derivative of medarc/adni-mini-v1-3.
It preserves the v1.3-r2 row order, metadata columns, labels, image geometry,
and float32 values inside the brain. The only image change is:
image[synthseg_dseg == 0] = 0.0
The brain mask is therefore defined strictly as nonzero labels in the matching
SynthSeg discrete segmentation.
See comparison.json and per_scan_stats.csv for measured storage and mask
statistics. This derivative is not the… See the full description on the dataset page: https://huggingface.co/datasets/medarc/adni-mini.YuLan-Mini-Text-Datasets
News
[2025.04.11] Add dataset mixture: link.
[2025.03.30] Text datasets upload finished.
This is text dataset.
这是文本格式的数据集。
Since we have used BPE-Dropout, in order to ensure accuracy, you can find the tokenized dataset here.
由于我们使用了BPE-Dropout，为了保证准确性，你可以在这里找到分词后的数据。
For more information, please refer to our datasets details and preprocess details.
Contributing
We welcome any form of contribution, including feedback on model bad cases, feature suggestions, and example… See the full description on the dataset page: https://huggingface.co/datasets/yulan-team/YuLan-Mini-Text-Datasets.minimax-h3-soup
MiniMax H3 Soup
Reproducibility archive for a local ComfyUI MiniMax H3 Ref2V benchmark on an RTX 3090.
What is included
Original benchmark workflow graph (source_prompt.json), manifest, and result table.
Every one-second MP4 from the original C1-C11 benchmark grid and its Euler
repeat sweep. The separate
duration experiments are intentionally not included.
Labeled C1-C11 visual contact sheets, Ref2VA stock-control sheets, and a
static render-time summary chart.… See the full description on the dataset page: https://huggingface.co/datasets/badincite/minimax-h3-soup.wikipedia-22-12-en-embeddings-all-MiniLM-L6-v2
Dataset Card for "wikipedia-22-12-en-embeddings-all-MiniLM-L6-v2"
More Information needed
bitcoin-mining-pool-templates
Bitcoin mining pool templates
Timestamped Stratum job messages collected directly from Bitcoin mining pool endpoints. The data records changes in the work each endpoint sends to miners, including the previous block hash, coinbase data and clean-jobs flag.
Contents
Table
Record
bitcoin_mining_pool_jobs
A job received from a pool endpoint, with its observation time, nTime, coinbase, merkle branch count and clean-jobs flag
Using the data… See the full description on the dataset page: https://huggingface.co/datasets/dataforge-labs/bitcoin-mining-pool-templates.full-math-private-n256-Phi-4-mini-instruct-bonMiniMax-M2.1-Mixture-of-Thoughts
MiniMax-M2.1 Mixture of Thoughts
This dataset contains responses generated by MiniMax-M2.1 for user questions from the open-r1/Mixture-of-Thoughts dataset.
Dataset Description
The dataset captures both the extended thinking process and final answers from MiniMax-M2.1, with reasoning wrapped in <think> tags for easy separation.
Metric
Value
Examples
349,317
Total Tokens
4,052,592,552
Avg Tokens/Example
11,601
Source Dataset
Name:… See the full description on the dataset page: https://huggingface.co/datasets/PursuitOfDataScience/MiniMax-M2.1-Mixture-of-Thoughts.MiniCPM5-1B-atlas
juiceb0xc0de/MiniCPM5-1B-atlas
A brain atlas for openbmb/MiniCPM5-1B, a 1B on-device model with a 130k bilingual vocabulary. This is not a chat dataset or a benchmark. It is an internal-mechanics map, built by running activations through a corpus of prompts and scoring what each layer, component, head, and feature direction is doing.
If you want to know which parts of this model are safe to edit, where its output-vocabulary directions live, or which layers are carrying the most… See the full description on the dataset page: https://huggingface.co/datasets/juiceb0xc0de/MiniCPM5-1B-atlas.msmarco-msmarco-MiniLM-L6-v3
MS MARCO with hard negatives from msmarco-MiniLM-L6-v3
MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using the Bing search engine.
For each query and gold positive passage, the 50 most similar paragraphs were mined using 13 different models. The resulting data can be used to train Sentence Transformer models.
Related Datasets
These are the datasets generated using the 13 different models:
msmarco-bm25… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-MiniLM-L6-v3.gelsight-mini-pretrain
GelSight Mini Pretrain
~853K GelSight Mini tactile RGB frames, 12 public sources, one parquet schema. Built for self-supervised representation learning (VAE / MAE / SimCLR / DINO) — every frame contact-filtered, channel-normalized, and re-encoded as JPEG q92.
Frames
Sources
Real
536K
FoTA (labeled+unlabeled), 3DCal, FEATS, GelSLAM, TactileTracking, RTM, FeelAnyForce, UniT, TacQuad
Sim
317K
sim_tactile_mnist, sim_starstruck (Taxim-rendered, Mini-calibrated)
NC… See the full description on the dataset page: https://huggingface.co/datasets/yxma/gelsight-mini-pretrain.minimax-m3-claude-code-tracesThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Minimax M3 Claude Code Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by minimax/minimax-m3.
JSONL files: 31
Format
Each file is newline-delimited JSON representing a single captured agent session.
The trace schema is designed for… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/minimax-m3-claude-code-traces.the-stack-mini-nonshuffledThis repo contains (up to) 30k samples of 21 languages (top 20 languages by StackOverflow survey, html/css was splited).
'javascript', 'html', 'css', 'python', 'sql', 'typescript', 'shell', 'java', 'c-sharp', 'cpp', 'c', 'php', 'powershell', 'go', 'rust', 'kotlin', 'lua', 'dart', 'assembly', 'ruby', 'swift'
role-play-bench
Role-play Benchmark
A comprehensive benchmark for evaluating Role-play Agents in Chinese and English scenarios.
Dataset Summary
Role-play Benchmark is designed to evaluate Role-play Agents' ability to deliver immersive role-play experiences through Situated Reenactment. Unlike traditional benchmarks with verifiable answers, Role-play is fundamentally non-verifiable, e.g., there's no single "correct" response when a tsundere character is asked "Do you like me?".… See the full description on the dataset page: https://huggingface.co/datasets/MiniMaxAI/role-play-bench.deepswe-mini
deepswe-mini
16 of the 113 tasks in DeepSWE v1.1, picked so that running just these ranks models the same way the full benchmark does.
DeepSWE is a good benchmark and an expensive one. Every task is a long-horizon feature request in its own container, and a full pass takes close to two days of agent time run one task at a time. If you are comparing models, agent harnesses or prompts, and the differences you care about are more than a few points, these 16 tasks give you the same… See the full description on the dataset page: https://huggingface.co/datasets/LocalLLaMA/deepswe-mini.asia-energy-world-bank-energy-and-mining-indicators
India - Energy and Mining
Publisher: World Bank Group · Source: HDX · License: cc-by · Updated: 2026-04-28
Abstract
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
The world economy needs ever-increasing amounts of energy to sustain economic growth, raise living standards, and reduce poverty. But today's trends in energy use are not sustainable. As the world's population grows and economies become more industrialized… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-energy-world-bank-energy-and-mining-indicators.full-aime_2026-n256-Phi-4-mini-instruct-bonAuto-ClawEval-mini
Auto-ClawEval-mini
Compact agent evaluation benchmark with 104 tasks created by ClawEnvKit.
Statistics
Tasks
104
Categories
24
Mock services
20
Task types
API-based (77%) + file-dependent (23%)
Quick Start
# Download
huggingface-cli download AIcell/Auto-ClawEval-mini --repo-type dataset --local-dir Auto-ClawEval-mini
# Evaluate with ClawEnvKit (Docker harness)
bash run_harnesses.sh --harness claudecode --dataset Auto-ClawEval-mini… See the full description on the dataset page: https://huggingface.co/datasets/AIcell/Auto-ClawEval-mini.REASONING_evalchemy_64_sharded_gpt-4o-mini
Dataset card for REASONING_evalchemy_64_sharded_gpt-4o-mini
This dataset was made with Curator.
Dataset details
A sample from the dataset:
{
"context": [
{
"content": "Generate an executable Python function generated from the given prompt. Return the function body without invoking it at the final solution.You are given a 0-indexed array nums of n integers and an integer target.\nYou are initially positioned at index 0. In one step, you can… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/REASONING_evalchemy_64_sharded_gpt-4o-mini.MiniCPM-RobotManip-LIBERO
MiniCPM-RobotManip LIBERO
This dataset contains the four LIBERO suites converted to LeRobot v3 format
for the MiniCPM-RobotManip LIBERO full-parameter fine-tuning example in
starVLA.
Dataset summary
Suite
Episodes
Frames
Videos
LIBERO-10
358
95,740
716
LIBERO-Goal
405
48,131
810
LIBERO-Object
450
66,294
900
LIBERO-Spatial
423
51,707
846
Total
1,636
261,872
3,272
Format: LeRobot v3
Frequency: 20 Hz
Cameras: agent view and wrist view
Video… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/MiniCPM-RobotManip-LIBERO.miniVLA-Nav
MiniVLA-Nav v1
A Multi-Scene Simulation Dataset for Language-Conditioned Robot Navigation
Demo
All-scenes montage
Nova Carter navigating to named objects across all four Isaac Sim environments.
Dataset Summary
MiniVLA-Nav v1 is a simulation dataset for the Language-Conditioned Object Approach (LCOA) task: given a short natural-language instruction, an NVIDIA Nova Carter differential-drive robot must navigate to the named object and stop within 1 m.… See the full description on the dataset page: https://huggingface.co/datasets/alibustami/miniVLA-Nav.minimax-m3-deepsearchqa-skill-eval
MiniMax M3 DeepSearchQA Skill Eval
Evaluates minimax/minimax-m3 on google/deepsearchqa using a Pi agent, You.com MCP tools, and a research skill optimized for this harness, model, and tool surface.
MiniMax M3 Medium Reasoning with the You.com research skill reached 74.85% adjusted F1 on DeepSearchQA, above the paper's GPT-5 High Reasoning F1 result. Public artifacts are available for inspection and reproduction.
Links
GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/youdotcom/minimax-m3-deepsearchqa-skill-eval.starcop_allbands_mini
MINI version of the STARCOP dataset
For full details please refer to https://huggingface.co/datasets/previtus/STARCOP_allbands_Train1
aime_1983_2023_grok-3-mini-high_traces_32768terminal-bench-mini
terminal-bench-mini
Fourteen of Terminal-Bench 2.0's ninety tasks, picked so that ranking agents on
the subset reproduces ranking them on the whole benchmark.
Running ninety tasks five times each is how the official leaderboard is built.
That is out of reach if you are comparing quant variants, fine-tunes or local
models on your own hardware. This subset turns a multi-day sweep into a few
hours.
Same approach as deepswe-mini:
take the published per-task results, rank the field… See the full description on the dataset page: https://huggingface.co/datasets/LocalLLaMA/terminal-bench-mini.mini-sinhala-flanminimax-m2.7-agent
Agentic Training Traces
This directory contains raw agent trace files generated by agentic-datagen.
All assistant responses were generated by minimax/minimax-m2.7.
Trace files: 20
Training-ready tools
Use this tools payload when rendering converted examples through your training chat template.
The same structure is emitted on each converted example as the tools field.
[
{
"type": "function",
"function": {
"name": "bash",
"parameters": {… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/minimax-m2.7-agent.