datasetId stringlengths 6 123 | predicted_domain stringclasses 10
values | confidence float64 0.14 1 | top2_label stringclasses 10
values | top2_score float64 0 0.5 | tag_domain stringclasses 9
values | existing_tags listlengths 0 190 | card_preview stringlengths 0 500 | card_length int64 0 25.3M | downloads int64 0 2.75M | category stringclasses 4
values |
|---|---|---|---|---|---|---|---|---|---|---|
winy95/6h-training_data_v2 | none | 0.5038 | chemistry | 0.2274 | null | [] | 0 | 5 | normal | |
AdilZtn/pick_and_place_intermediate_40_ep | none | 0.9033 | code | 0.091 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"... | 3,733 | 14 | normal |
OALL/details_Qwen__Qwen2.5-Math-72B | none | 0.9296 | code | 0.0513 | null | [] | # Dataset Card for Evaluation run of Qwen/Qwen2.5-Math-72B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Qwen/Qwen2.5-Math-72B](https://huggingface.co/Qwen/Qwen2.5-Math-72B).
The dataset is composed of 136 configuration, each one coresponding to on... | 24,746 | 8 | normal |
AIR-Bench/qrels-qa_wiki_fr-dev | none | 0.9175 | code | 0.0457 | null | [] | Available Versions:
- AIR-Bench_24.05
- Task / Domain / Language: qa / wiki / fr
- Available Datasets (Dataset Name: Splits):
- default: dev, test | 162 | 3 | normal |
sociallifethree/armut-koltuk-kiralama-uzman-hizmet | cybersecurity | 0.8638 | finance | 0.0777 | null | [] | Armut koltuk kiralama hizmeti, farklı etkinliklerde şıklığı ve rahatlığı bir arada sunan mükemmel bir çözümdür. Sitemizden ve firmamızdan dilediğiniz sayıda armut koltuğu hızlı bir şekilde kiralayabilirsiniz. Ülke genelinde birçok alanda hizmet sunan firmamız, aynı zamanda geniş bir üretim deposuna sahiptir ve etkinlik... | 690 | 5 | new_discovery |
yjkimstats/CC3M_500k_mined | none | 0.6914 | code | 0.1129 | null | [] | 0 | 3 | normal | |
alihmaou/bdnb_2023-11.a_rel_batiment_construction_rnb_69 | none | 0.6696 | code | 0.0764 | null | [] | 0 | 4 | normal | |
mlfoundations-dev/oh_v1.2_opengpt_x4 | none | 0.38 | chemistry | 0.2299 | null | [] | 0 | 5 | normal | |
DiffusionLight/text2dataset | chemistry | 0.5766 | none | 0.258 | null | [] | # Text2Dataset
the dataset generate from ChatGPT's output and text2light for training the LoRA using in DiffusionLight
Code for training the LoRA can be found at [DiffusionLight-LoRA-Trainer](https://github.com/DiffusionLight/DiffusionLight-LoRA-Trainer) | 257 | 18 | normal |
Sourabh2/bhabhaww | none | 0.3391 | legal | 0.1975 | null | [] | 0 | 5 | normal | |
sebastiandavidlee/pensInHolder-corner-two-hires | none | 0.891 | code | 0.0945 | null | [
"phosphobot",
"so100",
"phospho-dk"
] | # pensInHolder-corner-two-hires
**This dataset was generated using a [phospho starter pack](https://robots.phospho.ai).**
This dataset contains a series of episodes recorded with a robot and multiple cameras. It can be directly used to train a policy using imitation learning. It's compatible with LeRobot and RLDS. | 317 | 34 | normal |
french-datasets/AIR-Bench_qrels-qa_law_fr-dev | none | 0.6816 | legal | 0.2411 | null | [] | Ce répertoire est vide, il a été créé pour améliorer le référencement du jeu de données [AIR-Bench/qrels-qa_law_fr-dev](https://huggingface.co/datasets/AIR-Bench/qrels-qa_law_fr-dev). | 183 | 4 | normal |
french-open-data/trace-des-lignes-scolaires-du-reseau-astuce-metropole-rouen-normandie | none | 0.8309 | cybersecurity | 0.141 | null | [
"lignes-scolaires",
"metropole-rouen-normandie",
"ods",
"reseau-astuce",
"dataset_for_agent"
] | # Tracé des lignes scolaires du réseau Astuce Métropole Rouen Normandie
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Tracé des lignes scolaires du réseau Astuce Métropole Rouen Normandie** qui est disponible à l'adresse https://www.data.gouv.fr/datase... | 535 | 4 | normal |
kornwtp/vlsp2016sentiment-vie-classification | none | 0.7599 | climate | 0.1119 | null | [] | ref: https://vlsp.org.vn/vlsp2016/eval/sa | 41 | 69 | normal |
ddamianos/gpc-all-08-601000 | none | 0.5933 | biology | 0.15 | null | [] | 0 | 7 | normal | |
test-gen/code_humaneval_qwen2.5-7b_t1.0_n8_tests_humaneval_qwen-1.5b-easy_t0.0_n1 | code | 0.5079 | none | 0.4801 | null | [] | 0 | 4 | boundary | |
cs198-cvmig/isic2018_filtered_augmented | none | 0.5968 | climate | 0.1221 | null | [] | 0 | 5 | normal | |
mothnaZl/s1-Qwen2.5-7B-Instruct-7-best_of_n-VLLM-Skywork-o1-Open-PRM-Qwen-2.5-7B-completions | none | 0.8593 | code | 0.1156 | null | [] | 0 | 5 | normal | |
Oztobuzz/OK_VQA_sample | none | 0.4579 | code | 0.1765 | null | [] | 0 | 3 | normal | |
Yuyeong/rw_roman-empire_mdlr_2_public_masked | none | 0.7886 | code | 0.0637 | null | [] | 0 | 5 | normal | |
RAGEVALUATION-HJKMY/TSBC_100row_mistake_added-Evaluated-2025-04-12-11-11-07-o1-2024-12-17 | none | 0.809 | code | 0.1197 | null | [] | 0 | 4 | normal | |
thethinkmachine/GPT4-Mixtral-GSM8K-MMLU-Preference-16K-Eval-Complexity | none | 0.5266 | code | 0.2101 | null | [] | 0 | 8 | normal | |
ashercn97/logilog-v1-medium | none | 0.52 | chemistry | 0.1556 | null | [] | 0 | 4 | normal | |
toolevalxm/Climate-ERA5-Processed | climate | 0.9899 | biology | 0.0049 | null | [] | # Climate-ERA5-Processed
This dataset contains processed ERA5 climate data.
## Data Source
This dataset is derived from Climate-ERA5-Raw and processed using the Mistral-7B-Instruct-v0.2 model.
**License**
The license for this dataset is Apache-2.0. | 253 | 13 | new_discovery |
Jennny/ultrafeedback_binarized_helpfulness_prefs | none | 0.6374 | code | 0.1833 | null | [] | 0 | 7 | normal | |
tim-lawson/mlsae-pythia-70m-deduped-x1-k32-dists | math | 0.3148 | chemistry | 0.2537 | null | [] | 0 | 4 | boundary | |
open-paws/reasoning-llama-format | none | 0.7422 | legal | 0.2008 | null | [
"animal-liberation",
"animal-advocacy",
"open-paws",
"ethics",
"alignment",
"reasoning"
] | # Open Paws Reasoning Llama Format
This dataset is part of the Open Paws initiative to develop AI training data aligned with animal liberation and advocacy principles. Created to train AI systems that understand and promote animal welfare, rights, and liberation.
## Dataset Details
- **Dataset Type**: Reasoning Data... | 2,284 | 40 | normal |
caskcsg/NExtLong-64K-dataset | none | 0.6391 | code | 0.3583 | null | [] | ## NExtLong: Toward Effective Long-Context Training without Long Documents
This repository contains the code ,models and datasets for our paper [NExtLong: Toward Effective Long-Context Training without Long Documents](https://arxiv.org/pdf/2501.12766).
[[Github](https://github.com/caskcsg/longcontext/tree/main/NExtLo... | 6,953 | 523 | normal |
test-time-compute/test_gaokao2023en | none | 0.6465 | code | 0.1713 | null | [] | 0 | 422 | normal | |
lmarena-ai/PPE-MBPP-Plus-Best-of-K | code | 0.4903 | none | 0.481 | null | [] | # Overview
This contains the MBPP-Plus correctness preference evaluation set for Preference Proxy Evaluations.
The prompts are sampled from [MBPP-Plus](https://huggingface.co/datasets/evalplus/mbppplus).
This dataset is meant for benchmarking and evaluation, not for training.
[Paper](https://arxiv.org/abs/2410.1487... | 955 | 113 | boundary |
Mimic-Robotics/bimanual_blue_block_handover_5 | none | 0.8988 | code | 0.0962 | null | [
"bimanual",
"handover",
"consolidated"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 4,779 | 11 | normal |
SEACrowd/myanmar_rakhine_parallel | none | 0.963 | code | 0.0308 | null | [
"machine-translation"
] | The data contains 18,373 Myanmar sentences of the ASEAN-MT Parallel Corpus,
which is a parallel corpus in the travel domain. It contains six main
categories: people (greeting, introduction, and communication), survival
(transportation, accommodation, and finance), food (food, beverages, and
restaurants), fun (recreatio... | 4,153 | 40 | normal |
Agiao123/MATH-500 | math | 0.8988 | chemistry | 0.0434 | null | [] | # Dataset Card for MATH-500
<!-- Provide a quick summary of the dataset. -->
This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their _Let's Verify Step by Step_ paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#... | 331 | 12 | new_discovery |
ai2-adapt-dev/s1k_1.1_messages | none | 0.6969 | code | 0.1974 | null | [] | 0 | 4 | normal | |
open-llm-leaderboard-old/details_Walmart-the-bag__Misted-v2-7B | none | 0.9135 | biology | 0.0418 | null | [] | # Dataset Card for Evaluation run of Walmart-the-bag/Misted-v2-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Walmart-the-bag/Misted-v2-7B](https://huggingface.co/Walmart-the-bag/Misted-v2-7B) on the [Open LLM Leaderboard](https://huggingface.co/s... | 19,285 | 6 | normal |
astung/dataset-20251212-mini-trial | none | 0.7874 | code | 0.1044 | null | [
"sample",
"experimental"
] | # dataset-20251212-mini-trial
Created on: 2025-12-12T04:12:36.090706+00:00
Session ID: 2025-12-12T04:12:36.090706+00:00-3107 | 126 | 4 | normal |
paulpacaud/rlbenchfail_val_dataset | code | 0.563 | none | 0.3846 | null | [
"robotics",
"failure-detection",
"manipulation",
"vision-language",
"multi-view",
"simulation",
"rlbench"
] | # Guardian: RLBench-Fail Dataset
This dataset is part of the **Guardian** project: *Detecting Robotic Planning and Execution Errors with Vision-Language Models*. It contains annotated robotic manipulation failure data generated in the **RLBench simulator** for training and evaluating Vision-Language Models (VLMs) on f... | 10,561 | 35 | normal |
introspection-auditing/quirk_run1_103_prediction | none | 0.7451 | chemistry | 0.0504 | null | [] | 0 | 8 | normal | |
maidacundo/pandas-agi-dpo-dataset-dashboards_20 | none | 0.6698 | climate | 0.0932 | null | [] | 0 | 5 | normal | |
metaphilabs/frontend-figma-to-code | code | 0.9587 | none | 0.0204 | null | [
"figma-to-code",
"autonomous-agents"
] | # CREW: Figma to Code
A benchmark for evaluating AI coding agents on **Figma-to-code generation** — converting real-world Figma community designs
into production-ready React + Tailwind CSS applications.
Each task gives an agent full access to a Figma file via MCP tools. The agent must extract the design system... | 4,307 | 109 | new_discovery |
EphraimChuahLeePing/Chai_Er_Bin_AI_Civilization_AwakeningCN_EN.zip | none | 0.7514 | code | 0.0969 | null | [] | 0 | 6 | normal | |
ssktora/miracl-train1000-bm25-pyserini-5-dev-v3 | none | 0.627 | code | 0.297 | null | [] | 0 | 4 | normal | |
white-bird/8_dpo_data | climate | 0.4417 | none | 0.3354 | null | [] | 0 | 5 | boundary | |
chris241094/record-level1-0 | none | 0.9004 | code | 0.0955 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=chris241094/record-level1-0">
<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-... | 4,601 | 20 | normal |
jeqcho/qwen-2.5-72b-instruct-dolphin-numbers-run-0 | none | 0.6623 | code | 0.2818 | null | [] | 0 | 10 | normal | |
adalib/numpy-cond-gen-1 | chemistry | 0.363 | none | 0.3277 | null | [] | 0 | 17 | boundary | |
mekaneeky/fineweb-sample-1 | none | 0.4917 | chemistry | 0.1523 | null | [] | 0 | 5 | normal | |
teamcore/DPO_L8B_RMAB_TG_beta0.5dpo_probt_noise_flip0.3_traj | none | 0.7897 | code | 0.0964 | null | [] | 0 | 35 | normal | |
gouthamsk/esp_idf_code | none | 0.5229 | code | 0.1984 | null | [] | 0 | 12 | normal | |
liamlau/svla_so100_sorting | none | 0.9223 | code | 0.0734 | null | [
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 4,267 | 46 | normal |
sriramsk/fold_onesie_MVHuman_20251113_ss_hg | none | 0.9618 | code | 0.0238 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 7,270 | 28 | normal |
SteerAI/srn-cars-dataset | none | 0.7475 | code | 0.0565 | null | [] | 0 | 7 | normal | |
huutho13254/dataset-vi-chatbot-ai | none | 0.9186 | cybersecurity | 0.0506 | null | [
"conversational",
"chatbot",
"customer-service",
"function-calling",
"vietnamese",
"qwen3",
"unsloth"
] | # Qwen3 Vietnamese Chatbot Training Dataset
## Dataset Description
Đây là dataset được tối ưu hóa đặc biệt cho việc fine-tune **Qwen3-8B** để tạo ra chatbot AI thông minh, tự nhiên và có khả năng function calling trong môi trường doanh nghiệp Việt Nam.
### Dataset Composition
**Tổng cộng: 8,700 conversations**
| S... | 3,659 | 10 | normal |
stefanocarrera/autophagycode_metrics_D_metrics_evalplus_unsloth__Qwen3-14B-Base-unsloth-bnb-4bit_lr0.0001_gen5 | none | 0.6604 | code | 0.2031 | null | [] | 0 | 12 | normal | |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_1a530d1b-9526-45fb-bf7c-978d94d8017f | none | 0.6877 | code | 0.134 | null | [] | 0 | 3 | normal | |
Yuting6/geoqa-concat-6k | none | 0.5053 | climate | 0.1261 | null | [] | 0 | 5 | normal | |
makeabilitylab/disabilityparking | none | 0.9684 | code | 0.0153 | null | [
"disability-parking",
"accessibility",
"streetscape"
] | # AccessParkCV
<strong>AccessParkCV</strong> is a deep learning pipeline that detects and characterizes the width of disability parking spaces from orthorectified aerial imagery. We publish a dataset of 7,069 labeled parking spaces (and 4,693 labeled access aisles), which we used to train the models making AccessParkC... | 3,677 | 113 | normal |
Trelis/orpheus-formatted | none | 0.9799 | code | 0.0068 | null | [] | # orpheus-formatted
This dataset contains tokenized speech for Orpheus fine-tuning.
## Dataset details
- Source dataset: Trelis/orpheus-ft
- Number of examples: 18
- Format: Each example contains input_ids, labels, and attention_mask in the format expected by Orpheus models.
## Usage
This dataset is ready for fine-t... | 445 | 9 | normal |
mteb/Vidore3PhysicsOCRRetrieval | none | 0.7174 | math | 0.1862 | null | [
"mteb",
"text",
"image"
] | <!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
<div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">
<h1 styl... | 5,884 | 190 | normal |
danielsanjosepro/lego-stacking-ft | none | 0.865 | code | 0.1303 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 4,685 | 5 | normal |
yuz1wan/so100_pickplace | none | 0.9164 | code | 0.0787 | null | [
"so100",
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.0",
"... | 3,582 | 22 | normal |
rhyliieee/tagalog-filipino-english-translation | none | 0.9897 | legal | 0.0036 | null | [] | This dataset is a Tagalog-English translation data. It is a compiled comma-separated values dataset from different
existing HuggingFace and External dataset.
Here are the collected and compiled data:
1. saillab/alpaca_tamil_taco
2. DIBT/MPEP_FILIPINO
3. Nag, S., Ma, S., Ntalli, A., & Dulay, K. M. (2024, June 10). Tal... | 368 | 52 | normal |
avnishkanungo/updated_fabner | none | 0.3133 | code | 0.1175 | null | [] | 0 | 4 | normal | |
math-extraction-comp/refuelai__Llama-3-Refueled | none | 0.6071 | code | 0.198 | null | [] | 0 | 5 | normal | |
lca0503/speech_mmau_fastest_tempo | none | 0.8042 | finance | 0.0319 | null | [] | 0 | 17 | normal | |
nguyenhuucongzz01/serDataset | none | 0.3675 | climate | 0.1828 | null | [] | 0 | 4 | normal | |
natolambert/tulu_v3.9_wildchat_100k_english-r1-debug | none | 0.954 | code | 0.0138 | null | [] | 0 | 3 | normal | |
EmineYoubah/testPrediction | none | 0.458 | code | 0.1916 | null | [] | 0 | 3 | normal | |
colabfit/CrCoNi_Cao_2022 | chemistry | 0.9899 | none | 0.0069 | null | [
"molecular dynamics",
"mlip",
"interatomic potential"
] | ### <details><summary>Cite this dataset </summary>Cao, Y., Sheriff, K., and Freitas, R. _CrCoNi Cao 2022_. ColabFit, 2024. https://doi.org/10.60732/76208b62</details>
#### This dataset has been curated and formatted for the ColabFit Exchange
#### This dataset is also available on the ColabFit Exchange:
https://ma... | 2,316 | 25 | new_discovery |
gyeongsangseaman/eval_colorDetect0717_140000 | none | 0.919 | code | 0.0748 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 3,572 | 22 | normal |
Elfsong/palestinian-shami | none | 0.6442 | legal | 0.1236 | null | [] | 0 | 4 | normal | |
saumyamalik/personas_math_prompts_generated_shard_5 | none | 0.6189 | math | 0.2387 | null | [] | 0 | 4 | normal | |
Aftemelouchos/btc_15m | none | 0.4325 | chemistry | 0.1493 | null | [] | 0 | 4 | normal | |
1231czx/gemma2_9b_it_gsm8k_iter1 | none | 0.5487 | math | 0.1492 | null | [] | 0 | 4 | normal | |
AfnanTS/ArLAMA | none | 0.3526 | biology | 0.1379 | null | [] | 0 | 3 | normal | |
Supersaiyan1729/fin_smp | none | 0.5881 | biology | 0.0959 | null | [] | 0 | 5 | normal | |
monsoon-nlp/wheat-bees | biology | 0.9956 | none | 0.0021 | null | [
"DNA"
] | Mini mini version of [InstaDeepAI/plant-multi-species-genomes](https://huggingface.co/datasets/InstaDeepAI/plant-multi-species-genomes) with wheat as training set and papaya as validation set.
One model [monsoon-nlp/dna-blockdiff-papaya](https://huggingface.co/monsoon-nlp/dna-blockdiff-papaya) was trained only on the ... | 356 | 29 | new_discovery |
ljvmiranda921/details_msde-allenai_Olmo-3-1025-7B-lora-4bit-msde-S1-es_granite-4_0-1b | none | 0.9754 | biology | 0.0089 | null | [] | # Dataset Card for Evaluation run of ljvmiranda921/msde-sft-dev
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [ljvmiranda921/msde-sft-dev](https://huggingface.co/ljvmiranda921/msde-sft-dev).
The dataset is composed of 14 configuration, each one corr... | 6,793 | 14 | normal |
Tabys/ATC_combined | none | 0.9802 | cybersecurity | 0.007 | null | [
"audio",
"automatic-speech-recognition",
"en-atc",
"en",
"noisy-speech-recognition",
"speech-recognition"
] | # Dataset Card for UWB-ATCC corpus
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages and Other Details](#languages-and-other-details)
- [Dataset Structure](#dataset-structur... | 5,560 | 40 | normal |
LEGENDQ/Claude-Opus-4.6-Reasoning-Dataset | math | 0.8462 | chemistry | 0.0785 | code | [
"code",
"reasoning"
] | This is a dataset for reasoning by Claude Opus 4.6 to distills the reasoning capablities. | 89 | 200 | tag_disagree |
DCAgent2/dev_set_v2_exp_gfi_staqc_short_response_filtered_10K_glm_4_7_traces_locetash_20d68dbbe0 | none | 0.6173 | chemistry | 0.3097 | null | [] | 0 | 18 | normal | |
Menoviar28/menov52 | none | 0.4784 | biology | 0.2304 | finance | [
"finance"
] | 0 | 7 | tag_disagree | |
rishikeshgautam/newscorpus-for-nepali-ged | none | 0.6878 | code | 0.0966 | null | [] | 0 | 6 | normal | |
DKYoon/openthoughts-filtered | none | 0.5043 | climate | 0.1445 | null | [] | 0 | 4 | normal | |
jiamingzz/geo_6k | none | 0.8747 | cybersecurity | 0.107 | null | [
"privacy",
"adversarial-attack",
"geographic-reasoning",
"multimodal"
] | # GeoPrivacy-6K
**[Project Page](https://jiamingzz94.github.io/reasonbreak/)** | **[Paper](https://arxiv.org/abs/2512.08503)** | **[Code](https://github.com/jiamingzhang94/ReasonBreak)**
## Introduction
**GeoPrivacy-6K** is a specialized dataset comprising **6,341 ultra-high-resolution images** ($\ge$ 2K resolution)... | 2,725 | 24 | normal |
aistatuscodes/statuscodes10 | none | 0.9214 | code | 0.0555 | null | [
"ai-assistant",
"chatbot",
"user-satisfaction",
"context-understanding",
"intent-classification"
] | # AI Status Codes (Experimental): first run
🚀 An experimental micro-dataset for evaluating contextual understanding and user satisfaction in AI assistant responses. 🚀
This is the first, experimental release from the **AI Status Codes** initiative.
# Purpose and Features
This dataset is designed to help researcher... | 4,783 | 34 | normal |
neelabh17/new_news_exploded_prompt_n_50_d_perc_20_num_gen_10_Qwen2.5-0.5B-Instruct_dist_mcq | none | 0.9668 | code | 0.0231 | null | [] | 0 | 5 | normal | |
zjhhhh/iter2_7b_multi_perprompt_scores_base_40 | none | 0.8358 | code | 0.0648 | null | [] | 0 | 5 | normal | |
kaushalgawri/nptel_indian_en_subset_with_descriptions_v0 | none | 0.6403 | climate | 0.087 | null | [
"indian accent"
] | 0 | 10 | normal | |
pdf2dataset/7c4db6e980b89f6e920396d88bd2df16 | none | 0.6201 | biology | 0.1041 | null | [] | 0 | 3 | normal | |
answerdotai/triviaqa_entailment | none | 0.6638 | code | 0.0773 | null | [] | 0 | 23 | normal | |
yoonholee/combined-preference-dataset | none | 0.7339 | code | 0.1351 | null | [] | Combined preference dataset. All examples are binarized and standardized for `tokenizer.apply_chat_template()`.
Source datasets:
- [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback)
- [coseal/CodeUltraFeedback](https://huggingface.co/datasets/coseal/CodeUltraFeedback)
- [nvidia/HelpSteer2]... | 876 | 6 | normal |
yunjae-won/Qwen3-Next-80B-MagpieLM-SFT-Outputs-v0.1-shard4 | none | 0.7833 | code | 0.1366 | null | [] | 0 | 5 | normal | |
HoangHa/wiki_med_en | none | 0.6185 | biology | 0.0672 | null | [] | 0 | 12 | normal | |
TheFactoryX/edition_1948_google-research-datasets-mbpp-readymade | none | 0.9867 | code | 0.0112 | null | [
"readymades",
"art",
"duchamp"
] | # edition_1948_google-research-datasets-mbpp-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[google-research-datasets/mbpp](https://huggingface.co/datasets/google-research-datasets/mbpp)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recon... | 969 | 5 | normal |
allganize/math_table_qa | math | 0.9514 | none | 0.036 | null | [] | # mathqa-ko
- `mathqa-ko` 데이터는 일반(general) 도메인의 QA 데이터셋입니다. Context와 Question이 주어졌을 때, 질문에 상응하는 답을 생성해야 합니다.
입력값으로는 text만이 주어집니다.
### Test Data의 구축
- 원본 데이터의 passage, question number(와 unit)을 그대로 사용합니다.
- Test를 위해 랜덤하게 90개를 선택하였습니다.
### 데이터 출처
- [숫자연산 기계독해 데이터](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=... | 1,114 | 5 | new_discovery |
alias-emasal/topics | none | 0.5762 | code | 0.1146 | null | [] | 0 | 3 | normal | |
snehatammineni/drillingholes | none | 0.7004 | code | 0.1699 | null | [] | title: Object Detection
emoji: 👀
colorFrom: red
colorTo: green
sdk: gradio
sdk_version: 3.32.0
app_file: app.py
pinned: false | 125 | 3 | normal |
ajibawa-2023/Children-Stories-Collection | none | 0.9496 | code | 0.011 | null | [
"story",
"children",
"young children"
] | **Children Stories Collection**
A great synthetic datasets consists of around **0.9 million** stories especially meant for **Young Children**. You can directly use these datasets for training large models.
Total 10 datasets are available for download. You can use any one or all the json files for training purpose.
The... | 440 | 574 | normal |
festvox/cmu_hinglish_dog | none | 0.9913 | code | 0.0051 | null | [] | # Dataset Card for CMU Document Grounded Conversations
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Ins... | 6,780 | 193 | normal |
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