datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Multitask-National-Speech-Corpus-v1Multitask-National-Speech-Corpus (MNSC v1) is derived from IMDA's NSC Corpus.
MNSC is a multitask speech understanding dataset derived and further annotated from IMDA NSC Corpus. It focuses on the knowledge of Singapore's local accent, localised terms, and code-switching.
ASR: Automatic Speech Recognition
SQA: Speech Question Answering
SDS: Spoken Dialogue Summarization
PQA: Paralinguistic Question Answering
from datasets import load_dataset
data =… See the full description on the dataset page: https://huggingface.co/datasets/MERaLiON/Multitask-National-Speech-Corpus-v1.multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR
PreFLMR M2KR Dataset Card
Dataset details
Dataset type:
M2KR is a benchmark dataset for multimodal knowledge retrieval. It contains a collection of tasks and datasets for training and evaluating multimodal knowledge retrieval models.
We pre-process the datasets into a uniform format and write several task-specific prompting instructions for each dataset. The details of the instruction can be found in the paper. The M2KR benchmark contains three types of tasks:… See the full description on the dataset page: https://huggingface.co/datasets/BByrneLab/multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR.Multitask-National-Speech-Corpus-v1-extendmultitask_german_examples_32kmulti_task_multi_modal_knowledge_retrieval_benchmark_M2KR_CN
PreFLMR M2KR Dataset Card
Dataset details
Dataset type:
M2KR is a benchmark dataset for multimodal knowledge retrieval. It contains a collection of tasks and datasets for training and evaluating multimodal knowledge retrieval models.
We pre-process the datasets into a uniform format and write several task-specific prompting instructions for each dataset. The details of the instruction can be found in the paper. The M2KR benchmark contains three types of tasks:… See the full description on the dataset page: https://huggingface.co/datasets/BByrneLab/multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR_CN.VQA-MultiTaskmulti-task-dataset
Multi-Task Dataset
Description
A large-scale multi-task dataset designed for training and evaluating AI models across reasoning, mathematics, code, research, verification, data analysis, and general problem solving.
Content
100,000,001 examples
20+ task families
English + French
Train / Validation / Test splits
Structured reasoning and verification signals
Multiple difficulty levels
OOD and generalization-oriented examples
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Lelonthecodeur/multi-task-dataset.multitask_vqa_benchmarkThis dataset is a part of .
🍈 MMT-47: Multimodal Multi-Task Benchmark
47 Tasks · 7 Categories · 3 Modalities (Image, Video, Text)
Cite our ICML-2026 paper for this dataset
@article{kowsher2026lime,
title={LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning},
author={Kowsher, Md and Mansoor, Haris and Prottasha, Nusrat Jahan and Garibay, Ozlem and Zhu, Victor and Ji, Zhengping and Chen, Chen},
journal={arXiv preprint… See the full description on the dataset page: https://huggingface.co/datasets/Kowsher/multitask_vqa_benchmark.multi_task_multi_modal_knowledge_retrieval_benchmark_M2KRGPRadar-Defect-MultiTask
GPRadar-Defect-MultiTask 数据集
本仓库包含用于微调PaLI-GEMMA多模态模型的地质雷达(GPR)缺陷检测数据集。该数据集专注于地下结构中的空洞和裂缝检测与分析。
数据集结构
数据集组织如下：
dataset/
├── annotations/ - 包含JSON和JSONL格式的标注文件
│ ├── _annotations.train.jsonl - 训练集标注
│ ├── _annotations.valid.jsonl - 验证集标注
│ ├── _annotations.test.jsonl - 测试集标注
│ ├── p-1.v1i.paligemma/ - 主数据集元数据
│ └── p-1.v1i.paligemma-multimodal/ - 多模态数据集元数据
├── images/ - 包含所有图像文件
特点
包含874张带注释的地质雷达扫描图像
图像预处理为640x640像素大小
支持多种任务类型：缺陷检测、位置定位和描述生成… See the full description on the dataset page: https://huggingface.co/datasets/xingqiang/GPRadar-Defect-MultiTask.coastal-multitask-380
Coastal & Rural Bangladesh — Multi-Task Visual Dataset
379 field photographs (JPEG, native resolution as shot — see classification/metadata.csv for per-image width/height) collected on foot along the Bakkhali river embankment and surrounding villages/farmland near Cox's Bazar, Bangladesh, structured into three ML-task "levels": classification, semantic segmentation, and change detection.
Source: huggingface data 06 (Golam Rob / Tawhid Enterprise photo collection).… See the full description on the dataset page: https://huggingface.co/datasets/golamrob/coastal-multitask-380.Sampling-Multitask-National-Speech-Corpus-v1
Sampling Multitask-National-Speech-Corpus-v1
Original dataset from https://huggingface.co/datasets/MERaLiON/Multitask-National-Speech-Corpus-v1, we only take Part 3 and do sampling.
how to prepare the dataset
huggingface-cli download \
mesolitica/Sampling-Multitask-National-Speech-Corpus-v1 \
--include "*.zip" \
--repo-type "dataset" \
--local-dir './'
wget… See the full description on the dataset page: https://huggingface.co/datasets/mesolitica/Sampling-Multitask-National-Speech-Corpus-v1.configurable-system-prompt-multitask
Configurable System Prompt Multi-task Dataset 🛞
We release the synthetic dataset for the multi-task experiments from the paper "Configurable Safety Tuning of Language Models with Synthetic Preference Data", https://huggingface.co/papers/2404.00495. This dataset has two sources for the examples:
Self-critique on a safety task from Harmful Behaviours, using the SOLAR-Instruct model. It employs two system prompts to learn the different behaviors:
You are a helpful yet harmless… See the full description on the dataset page: https://huggingface.co/datasets/vicgalle/configurable-system-prompt-multitask.UR7e_CaP_MultiTask_300epi_10fps
UR7e CaP MultiTask 300epi 10fps
This is a public LeRobot v3.0 multi-task dataset for UR7e Code-as-Policies manipulation. It merges three 100-episode 10fps datasets into one 300-episode training corpus while preserving the original numeric observations, actions, and task labels. The final uploaded copy stores all videos as 10fps H.264 MP4 files.
Dataset Summary
Robot: ur7e
Format: LeRobot v3.0
FPS: 10
Episodes: 300
Frames: 152,926
Cameras:… See the full description on the dataset page: https://huggingface.co/datasets/Cache-SCA/UR7e_CaP_MultiTask_300epi_10fps.sanskrit-multitaskdynasample_multitasks_cleansanskrit-multitask-devanagariSO101-cap_multitask_7tasks_700epi_10fpsThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 700,
"total_frames": 362160,
"total_tasks": 7,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 10,
"splits": {
"train": "0:700"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Cache-SCA/SO101-cap_multitask_7tasks_700epi_10fps.11_9_25_STAR_multitask_sftdata_cd34_lm3_lc4_a4Telugu-MultiTask-Instruct-77K
Telugu MultiTask Instruct 77K — Adaption AutoScientist Challenge Dataset
Powered by Adaptive Data — Adaption Labs
Dataset Description
A large-scale, multi-task Telugu instruction-tuning dataset combining 77,653 rows from 7 open-source Telugu NLP collections. Covers diverse tasks including news summarization, QA, creative writing, translation, and general instruction following — all processed through the Adaption Labs AutoScientist platform for quality… See the full description on the dataset page: https://huggingface.co/datasets/narendarcodes/Telugu-MultiTask-Instruct-77K.satellite-multitask-omni
🛰️ Satellite Multi-Task Omni Dataset
A unified, multi-task satellite/aerial imaging dataset designed for training omni-models that work with image+text as both input and output modalities. All data is converted to a consistent ChatML conversational format.
📊 Dataset Overview
Metric
Value
Total Samples
34,894
Train / Val / Test
31,404 / 1,744 / 1,746
Tasks
9 distinct task types
Sources
10 source datasets
Format
ChatML conversations + images… See the full description on the dataset page: https://huggingface.co/datasets/rahuldshetty/satellite-multitask-omni.multilingual-multitask-refusal
Multilingual Multitask Refusal
A multilingual, multitask prompt dataset for analysing refusal behaviour across language, task wrapper, and harmful / harmless labels.
English seed spans and labels come from the previous Multitask Multilingual Refusal dataset. Non-English content is produced with Google Sheets GOOGLETRANSLATE. Task instructions are language-localized via templates_localized.json.
Rows
211,320
English seeds
1,761
Languages
15
Tasks
8
Product
1… See the full description on the dataset page: https://huggingface.co/datasets/kaustubhg73/multilingual-multitask-refusal.UR7e_CaP_MultiTask_300epi_10fps_state_tplus1_action
UR7e CaP MultiTask 300epi 10fps
This is a public LeRobot v3.0 multi-task dataset for UR7e Code-as-Policies manipulation. It merges three 100-episode 10fps datasets into one 300-episode training corpus while preserving the original numeric observations, actions, and task labels. The final uploaded copy stores all videos as 10fps H.264 MP4 files.
Dataset Summary
Robot: ur7e
Format: LeRobot v3.0
FPS: 10
Episodes: 300
Frames: 152,926
Cameras:… See the full description on the dataset page: https://huggingface.co/datasets/Cache-SCA/UR7e_CaP_MultiTask_300epi_10fps_state_tplus1_action.MultitaskPreplay_jaxmaze_human_dfedgeimci-beta0-1k-multitask-enriched-2258-v1
EdgeIMCI Beta0-1K Multitask Enriched 2258
Dataset summary
This is the public, message-normalized publication of the dataset used to fine-tune the selected EdgeIMCI 4B-alpha-second research checkpoint from the pinned Qwen/Qwen3-4B base model. It combines structured extraction, routing, bounded clinical-response, project self-knowledge, scope-safety, and proposition/negation examples for the EdgeIMCI sick-child assessment workflow.
The dataset is research evidence… See the full description on the dataset page: https://huggingface.co/datasets/Nini0la/edgeimci-beta0-1k-multitask-enriched-2258-v1.lunamax-multitask-programming-1000
LunaMax Multitask Programming 1000
A 1,000-record synthetic multitask programming dataset generated with
ChatGPT LunaMax.
The recovered dataset combines code review, implementation, bug and severity
classification, and strict output-contract tasks across multiple programming
languages.
The historical source shards were reviewed with ChatGPT 5.6 Sol High according
to dataset creator confirmation. During Hugging Face publication preparation,
all 1,000 records received a new… See the full description on the dataset page: https://huggingface.co/datasets/TaskPuppyAI/lunamax-multitask-programming-1000.viveksingh2400_multitask-nlp
OpenMultiTask NLP Dataset
Mirror of the Kaggle dataset viveksingh2400/multitask-nlp by Vivek Singh, released under MIT. All credit goes to the original author; please cite and link the Kaggle page when using this data.
A synthetic, logically constrained dataset for multi-task NLP including sentimen
License
MIT License, Copyright (c) Vivek Singh. The full license text is in LICENSE and applies to all files in this repository.
Original description… See the full description on the dataset page: https://huggingface.co/datasets/haoxianc/viveksingh2400_multitask-nlp.multitask_v3_coding_11kmultitask_v3_math_11kmultitask_textqa_benchmarkThis dataset is a part of .
🍈 MMT-47: Multimodal Multi-Task Benchmark
47 Tasks · 7 Categories · 3 Modalities (Image, Video, Text)
Cite our ICML-2026 paper for this dataset
@article{kowsher2026lime,
title={LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning},
author={Kowsher, Md and Mansoor, Haris and Prottasha, Nusrat Jahan and Garibay, Ozlem and Zhu, Victor and Ji, Zhengping and Chen, Chen},
journal={arXiv preprint… See the full description on the dataset page: https://huggingface.co/datasets/Kowsher/multitask_textqa_benchmark.