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 |
|---|---|---|---|---|---|---|---|---|---|---|
TheFactoryX/edition_1553_mteb-sts12-sts-readymade | none | 0.9553 | code | 0.0403 | null | [
"readymades",
"art",
"duchamp"
] | # edition_1553_mteb-sts12-sts-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[mteb/sts12-sts](https://huggingface.co/datasets/mteb/sts12-sts)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
**What we did:**
1... | 924 | 4 | normal |
nvidia/Retrieval-Synthetic-NVDocs-v1 | none | 0.8511 | code | 0.134 | null | [] | ## Dataset Description:
Retrieval-Synthetic-NVDocs-v1 is a synthetic retrieval dataset with question–answer supervision designed to train and evaluate embedding and RAG systems. The dataset was generated on top of NVIDIA's publicly available content using [NeMo Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner... | 9,144 | 446 | normal |
sert121/temp_ad_a_w_f_e_e_m_o_r_r_s_c_c_h_n_test | none | 0.9675 | legal | 0.0237 | null | [] | ---
language: en
license: mit
---
# Dataset Name
adult_dataset_iteration_['education', 'age']
# Features Used
['education', 'age']
## Dataset Description
Features selected fr... | 387 | 4 | normal |
hugonowak/model-testowy-robotyka-98 | none | 0.8711 | code | 0.0698 | null | [] | model-testowy-robotyka-98
model-testowy-robotyka-98 | 51 | 6 | normal |
felixZzz/bespoke_17k_overlap-teacher_len32k_response-7 | none | 0.7016 | code | 0.1249 | null | [] | 0 | 5 | normal | |
btrabucco/refiner-step7 | chemistry | 0.4292 | none | 0.1957 | null | [] | 0 | 27 | normal | |
ScaleAI/SWE-bench_Pro | code | 0.9931 | none | 0.0059 | null | [] | ## Dataset Summary
SWE-Bench Pro is a challenging, enterprise-level dataset for testing agent ability on long-horizon software engineering tasks.
Paper: https://static.scale.com/uploads/654197dc94d34f66c0f5184e/SWEAP_Eval_Scale%20(9).pdf
See the related evaluation Github: https://github.com/scaleapi/SWE-bench_Pro-os... | 1,703 | 645,695 | new_discovery |
dokans/record-test14 | none | 0.9321 | code | 0.0634 | 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",
"... | 3,588 | 21 | normal |
phehjingjie/tengah-duck | none | 0.922 | code | 0.0731 | 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",
"... | 3,576 | 3 | normal |
mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_703b | none | 0.9524 | code | 0.0224 | null | [] | # mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_703b
Precomputed model outputs for evaluation.
## Evaluation Results
### HLE
- **Average Accuracy**: 11.13% ± 0.40%
- **Number of Runs**: 3
| Run | Accuracy | Questions Solved | Total Questions |
|-----|----------|-----------------|----------------|
| 1 | 11.72%... | 385 | 5 | normal |
Lots-of-LoRAs/task1615_sick_tclassify_b_relation_a | none | 0.9407 | biology | 0.0301 | null | [] | # Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1615_sick_tclassify_b_relation_a
## Dataset Description
- **Homepage:** https://github.com/allenai/natural-instructions
- **Paper:** https://arxiv.org/abs/2204.07705
- **Paper:** https://arxiv.org/abs/2407.00066
- **Po... | 2,311 | 11 | normal |
ShiningJazz/feedback_summary_summarydebertafaithful_271_1_5_4 | none | 0.8319 | code | 0.052 | null | [] | 0 | 4 | normal | |
u539285g/so-101-test | none | 0.9407 | code | 0.0467 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=u539285g/so-101-test">
<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"... | 3,328 | 20 | normal |
DenyTranDFW/BMW_Vehicle_Owner_Trust_2018_A_1725617 | none | 0.9505 | biology | 0.0244 | null | [] | | cik | form | accessionNumber | fileNumber | filmNumber | reportDate | url|
| ---------- | ---------- | ---------- | ---------- | ---------- | ---------- | ----------|
| 1725617 | ABS-EE | 0000929638-18-000030 | 333-208642-02 | 18523607 | 2017-11-30 | https://sec.gov/Archives/edgar/data/1725617/000092963818000030|... | 7,390 | 4 | normal |
colinhorger/AMPLIFY_350M_embeddings_temp | none | 0.4856 | chemistry | 0.1486 | null | [] | 0 | 6 | normal | |
openlamm/Ch3Ef_v0 | none | 0.8804 | code | 0.0876 | null | [] | **Note:** The dataset in this repo is currently a part of the Ch3Ef dataset. Rest of the data samples will be utilized in an upcoming [ICML Workshop challenge](https://icml-tifa.github.io/challenges/). Please stay tuned for further updates and additional data releases.
## Assessment of Multimodal Large Language Model... | 1,402 | 27 | normal |
googlefan/guanaco-jp-audio | none | 0.7107 | code | 0.0678 | null | [] | 0 | 5 | normal | |
french-open-data/repartion-nationale-du-ble-tendre-1993-2013 | none | 0.6378 | cybersecurity | 0.2184 | null | [
"ble",
"cereales",
"superficie",
"surface",
"dataset_for_agent"
] | # RÉPARTION NATIONALE DU BLÉ TENDRE - 1993 / 2013
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **RÉPARTION NATIONALE DU BLÉ TENDRE - 1993 / 2013** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/5bd2bfa18b4c417f20e18d65
## Description
... | 448 | 12 | normal |
FAU-LMS/UGC360 | none | 0.9864 | code | 0.0056 | null | [
"360-degree",
"video compression",
"spherical video",
"image sequence",
"video",
"pytorch-compatible"
] | # UGC360
Dataset of 6866 9-frame 360-degree video sequences collected from 1321 unique videos from Vimeo and Youtube licensed under a Creative Commons License.
The dataset is split into three subsets UGC360-S, UGC360-M, and UGC360-L to ease data handling.
| Subset | Resolutions | Minimum | ... | 3,835 | 712 | normal |
open-llm-leaderboard-old/details_kreimben__CodeMind-gemma | none | 0.7634 | code | 0.2316 | null | [] | # Dataset Card for Evaluation run of kreimben/CodeMind-gemma
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [kreimben/CodeMind-gemma](https://huggingface.co/kreimben/CodeMind-gemma) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFa... | 19,263 | 8 | normal |
DanqingZ/07238 | none | 0.9478 | code | 0.0478 | 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": "v2.1",
"ro... | 861 | 39 | normal |
french-open-data/lieux-de-mediation-numerique-sur-le-territoire-national-fournis-par-data-inclusion | medical | 0.5253 | none | 0.2753 | null | [
"inclusion",
"inclusion-numerique",
"lieux-d-inclusion-numerique",
"lieux-de-mediation-numerique",
"mediation",
"mediation-numerique",
"dataset_for_agent"
] | # Lieux de médiation numérique sur le territoire National fournis par Data Inclusion
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Lieux de médiation numérique sur le territoire National fournis par Data Inclusion** qui est disponible à l'adresse https... | 759 | 9 | normal |
willxxy/ecg-comp-noise-flatline-30000-250-2500 | none | 0.6416 | chemistry | 0.1265 | null | [] | 0 | 53 | normal | |
jdchang/distill-qwen32-n16-rollin-t2s | none | 0.4133 | code | 0.3924 | null | [] | 0 | 4 | normal | |
jaeyong2/Viet-emb-PreView | none | 0.9497 | code | 0.0375 | null | [] | ### Development Process
1. source dataset from [DataStudio/Viet-wikipedia](https://huggingface.co/datasets/DataStudio/Viet-wikipedia)
2. We used [Qwen/Qwen2-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) model to generate answer with COT.
## License
- Qwen/Qwen2.5-72B-Instruct : https://huggingfac... | 448 | 4 | normal |
Farmaanaa/bitcoin_price_timeseries | finance | 0.9862 | none | 0.0118 | null | [
"bitcoin",
"cryptocurrency",
"btc",
"timeseries",
"financial_data",
"trading",
"volume",
"price_data",
"tabular"
] | # Bitcoin Price Time Series Data
## Dataset Overview
This dataset offers a detailed, time-stamped record of Bitcoin's price and trading volume. It is an invaluable resource for financial analysis, market forecasting, and research into the dynamics of the cryptocurrency market.
## Data Source
The data was collected ... | 1,684 | 26 | new_discovery |
mlfoundations-dev/camel_gpt-4o-mini_4x | none | 0.4324 | chemistry | 0.2365 | null | [] | 0 | 6 | normal | |
abhinav302019/olympiad_data_141 | biology | 0.3457 | none | 0.3345 | null | [] | 0 | 2 | boundary | |
zcbecda/SpineAlign | medical | 0.9182 | none | 0.0638 | null | [] | # Dataset Card for Dataset Name
This dataset is a collection of colour pointcloud sequences, captured from
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** Connor Daly, Mechatronics in Medicine, Imperial College London
- **License:** CC BY 4... | 2,767 | 37,426 | new_discovery |
BAAI-DataCube/b1_1_fr_fr3_dual_left_place_gray_plate_from_low_rack_on_left_of_table | none | 0.8812 | code | 0.1107 | null | [] | # benchmark1_1_release_franka_fr3_dual_left_place_gray_plate_from_low_rack_on_left_of_table
This dataset converts the Robomain format uniformly into LeRobot V3.0.
## Dataset Statistics
本体: franka_fr3
末端执行器: 夹爪
任务平台显示版: 左手将灰色盘子从矮架上放在桌子左侧
total_episodes: 289
total_tasks: 1
size: 3.9G
## Dataset Structure
```
├── data
... | 993 | 14 | normal |
harshtd/atjhzatj | none | 0.4971 | chemistry | 0.0947 | null | [] | 0 | 5 | normal | |
SamagraDataGov/test_test_whisperft | none | 0.5791 | code | 0.1158 | null | [] | 0 | 3 | normal | |
mlnomad/imnet1k_ram_tup | none | 0.4753 | code | 0.145 | null | [] | 0 | 4 | normal | |
french-open-data/qualite-des-cours-d-eau-vis-a-vis-des-nitrites-en-bretagne | cybersecurity | 0.4348 | none | 0.4228 | null | [
"dataset_for_agent"
] | # Qualité des cours d'eau vis-à-vis des nitrites en Bretagne
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Qualité des cours d'eau vis-à-vis des nitrites en Bretagne** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/667e99e3c4dc588ff9f... | 1,024 | 8 | boundary |
mlfoundations-dev/filtering_fasttext_load_in | none | 0.6311 | code | 0.1473 | null | [] | 0 | 5 | normal | |
supergoose/flan_combined_task1125_alt_lo_ja_translation | none | 0.8721 | code | 0.0524 | null | [] | 0 | 3 | normal | |
mkonomi/greek_mmlu_configs | none | 0.6476 | math | 0.099 | null | [] | 0 | 59 | normal | |
electricsheepafrica/africa-mortality-rate-under-5-per-1-000-live-births | none | 0.6427 | medical | 0.1532 | null | [] | # Africa Mortality rate, under-5 (per 1,000 live births) Dataset
## Overview
This dataset contains mortality rate, under-5 (per 1,000 live births) data for African countries from the World Bank Aid Effectiveness indicators.
## Data Details
- **Indicator Code**: SH.DYN.MORT
- **Description**: Mortality rate, under-5 (... | 1,677 | 6 | normal |
vanekger/so101_pick_scotch_v1 | none | 0.9195 | code | 0.0754 | 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",
"... | 3,579 | 11 | normal |
Buaa1/drone-formations-crazyflies | biology | 0.5825 | none | 0.2807 | null | [] | 0 | 6 | normal | |
Yuanxin-Liu/sft-gsm-gemma-2-9b-it-epoch_3_with_text_True_gen_10_lr5e-6 | none | 0.8321 | climate | 0.0543 | null | [] | 0 | 4 | normal | |
PurifyMilk/BingleyCollections | none | 0.747 | climate | 0.0678 | null | [] | # Bingley Collections
## Description
Godfrey Bingley Photographic Archive (Bingley Collections), were donated to the University of Leeds in 1913. It consists of entries detailing different artworks along with their IIIF manifests. This dataset aims to provide data for recognition and analysis tasks.
## Structure
The ... | 1,154 | 7 | normal |
Nexdata/58_Hours_European_Portuguese_Child_Spontaneous_Speech_Data_Nexdata | none | 0.9683 | medical | 0.012 | null | [] | ## Description
Portuguese(Portugal) Children Real-world Casual Conversation and Monologue speech dataset, covers self-media, conversation, live, lecture, variety show and other generic domains, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, age, accent and other attributes. Our da... | 1,334 | 4 | normal |
sdadonlie/CoderForge-Preview | code | 0.9961 | none | 0.0027 | null | [] | # CoderForge-Preview: SOTA Open Dataset for Training Efficient Agents
**CoderForge-Preview** is **the** **largest open test-verified coding agent dataset.**
Fine-tuning Qwen-3 32B on it, we boost **SWE-Bench Verified performance** **23.0% → 59.4% pass@1** and rank **#1 among open-data** and **#2 among open-weight mo... | 3,083 | 1,070 | new_discovery |
felixZzz/bespoke_sub1k_overlap-teacher_len32k_response-student_multiZ_acc | none | 0.8718 | code | 0.0668 | null | [] | 0 | 5 | normal | |
Ibuki485/eval_test_11_p19 | none | 0.9348 | code | 0.0601 | 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",
"... | 2,943 | 21 | normal |
Pasulo/Emavi2 | none | 0.2615 | biology | 0.2261 | null | [] | 0 | 5 | normal | |
DCAgent/DCAgent_dev_set_71_tasks_Qwen_Qwen3-4B-Thinking-2507_20251111_055617 | none | 0.8499 | code | 0.1094 | null | [] | 0 | 10 | normal | |
jkcho/QA-Dataset-mini | none | 0.4974 | climate | 0.1928 | null | [] | 0 | 4 | normal | |
hawkingyou/so100_test | none | 0.9066 | code | 0.0897 | 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": "v2.1",
"... | 3,576 | 17 | normal |
apsora/Jobs-tabular-dataset | none | 0.4145 | biology | 0.1541 | null | [] | 0 | 3 | normal | |
Adanato/10model_rank_k5 | none | 0.8733 | code | 0.0588 | null | [] | # 10model_rank_k5
This repository contains k-means cluster subsets for training. Each subset is a config (`name=cluster_X`), backed by Parquet.
## Load examples
```python
from datasets import load_dataset
# Single cluster
ds0 = load_dataset("{username}/10model_rank_k5", name="cluster_0")
# Specific cluster
ds3 = l... | 546 | 11 | normal |
prli/uspto_draft_bf2_5-0_0-01_0-02_perturb | none | 0.7629 | climate | 0.1436 | null | [] | 0 | 14 | normal | |
zodi1121/allenai-ufb-skywork2 | chemistry | 0.3324 | none | 0.2837 | null | [] | 0 | 9 | boundary | |
svjack/Cut_Fruit_VACE_Depth_V2V_Captioned | none | 0.879 | cybersecurity | 0.054 | null | [] | 
+
<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/b46oBJ3GBdzXY4IcWBsoq.mp4"></video> | 267 | 5 | normal |
pclucas14/narrative_qa_rag_128_7_25 | none | 0.684 | biology | 0.115 | null | [] | 0 | 2 | normal | |
mxc0429/smolvla_Pick_Cube | none | 0.8974 | code | 0.0975 | 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",
"... | 3,593 | 14 | normal |
apinguen/jenga_push3 | none | 0.7877 | code | 0.1828 | null | [
"phosphobot",
"so100",
"phospho-dk"
] | # jenga_push3
**This dataset was generated using [phosphobot](https://docs.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.
To get started in robotics, [get your own ... | 370 | 16 | normal |
qklent/ficbook-horny-summary | none | 0.5106 | code | 0.1701 | null | [] | 0 | 4 | normal | |
dvilasuero/finevideo-qa-activities | none | 0.9634 | code | 0.0347 | null | [
"distilabel",
"rlaif"
] | <p align="left">
<a href="https://github.com/argilla-io/distilabel">
<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
</a>
</p>
# Dataset Card for finevideo-qa-activities
This dataset has been c... | 5,657 | 5 | normal |
yusufyusufyusuf1/eval_ACT_second5 | none | 0.9074 | code | 0.089 | 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"... | 3,729 | 22 | normal |
handsomecats/jbnhavbsgdvwa | none | 0.5626 | chemistry | 0.085 | null | [] | 0 | 5 | normal | |
cijerezg/pick-place-task-merged_1-4 | none | 0.8907 | code | 0.1054 | 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",
"... | 4,214 | 5 | normal |
Asap7772/arc-agi-mixed-max4096-newqwen-sft1e-5-test-abs-impabswithold-abs-32of96 | none | 0.9569 | biology | 0.0273 | null | [] | 0 | 5 | normal | |
DopeorNope/test_cpt_fft_3200_0.4 | none | 0.5199 | chemistry | 0.1548 | null | [] | 0 | 5 | normal | |
vlad2123/spell-correction-ru | none | 0.6901 | biology | 0.1012 | null | [] | 0 | 4 | normal | |
mmirac/part-1 | none | 0.4827 | climate | 0.1148 | null | [
"camel",
"question-answering"
] | 0 | 3 | normal | |
justinbeck/eval_brick-4-test2 | none | 0.9085 | code | 0.0845 | 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",
"... | 3,158 | 4 | normal |
ming030890/mdcc | none | 0.9799 | code | 0.0087 | null | [] | [](https://huggingface.co/datasets/ming030890/mdcc)
# MDCC: A New Cantonese ASR Dataset
## 📦 Update [1 Feb, 2024]
The `.wav` data of the dataset is available here:
🔗 [Google Drive Link](https://drive.google.com/file/d/1epfYMMhXdBKA6nxPgUugb2Uj4DllSxkn/vi... | 2,836 | 112 | normal |
kugler/AmDi.alpha.stratified.small | none | 0.4826 | biology | 0.1134 | null | [] | 0 | 10 | normal | |
DCAgent2/swesmith-GLM-4.6-32ep-131k-nosumm-traces-chunk009 | none | 0.868 | code | 0.0655 | null | [] | 0 | 9 | normal | |
Ashlot/record-test-2cam | none | 0.9239 | code | 0.0706 | 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",
"... | 3,573 | 4 | normal |
introvoyz041/GLASS_GPCR_SELFIES | chemistry | 0.8567 | biology | 0.1385 | null | [] | # From the [GLASS GPCR database](https://aideepmed.com/GLASS1/), converted to SELFIES
Steps to prepare the database:
1. Download the GLASS database
```bash
wget https://zhanggroup.org/GLASS/downloads/interactions_active.tsv
wget https://zhanggroup.org/GLASS/downloads/interactions_inactives.tsv
wget https://zhanggrou... | 4,451 | 8 | new_discovery |
ambrosfitz/openstax_american_yawp | legal | 0.5321 | none | 0.3874 | null | [
"education",
"history",
"us-history",
"question-answering",
"llm-training",
"ap-us-history",
"onramps"
] | # AP US History Question-Answer Pairs Dataset
## Dataset Description
This dataset contains **7,710 high-quality question-answer pairs** generated from AP US History and college-level US History textbook content, specifically sourced from **OpenStax US History** and **The American Yawp** digital textbooks. The dataset... | 20,757 | 7 | boundary |
Adanato/10model_rank_k7 | none | 0.8667 | code | 0.0625 | null | [] | # 10model_rank_k7
This repository contains k-means cluster subsets for training. Each subset is a config (`name=cluster_X`), backed by Parquet.
## Load examples
```python
from datasets import load_dataset
# Single cluster
ds0 = load_dataset("{username}/10model_rank_k7", name="cluster_0")
# Specific cluster
ds3 = l... | 546 | 13 | normal |
Vincentious/English_Filipino | none | 0.3982 | biology | 0.2789 | null | [] | 0 | 5 | normal | |
hafeezjimoh/test2 | none | 0.941 | code | 0.0541 | 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",
"... | 2,946 | 5 | normal |
haphazardlyinc/Forecastingv1 | none | 0.4411 | climate | 0.3696 | null | [] | V1 of a custom event forecasting dataset.
Data is not very well filtered or well formatted. | 92 | 4 | normal |
ilBiondo06/eval_act_so100_movelladot_b5 | none | 0.9288 | code | 0.0677 | 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",
"... | 3,584 | 8 | normal |
andnetdeboer/vtam_pickup_cup | none | 0.4902 | chemistry | 0.1196 | null | [] | 0 | 26 | normal | |
yanakidis/Text2Video | none | 0.8518 | code | 0.1277 | null | [] | Dataset with 200 videos generated by Text2Video and Image+Text2Video Models.
Folder **videos** contains videos themselves.
File **dataset.xlsx** contains prompts and corresponding generated videofiles names with scores. | 221 | 3 | normal |
Serbian-AI-Society/NanoQuoraRetrieval-bm25 | none | 0.9346 | code | 0.0579 | null | [
"sentence-transformers"
] | # NanoBEIR QuoraRetrieval with BM25 Rankings - Serbian Translation
This dataset is a Serbian language translation of the updated variant of [NanoQuoraRetrieval](https://huggingface.co/datasets/zeta-alpha-ai/NanoQuoraRetrieval), which is a subset of the QuoraRetrieval dataset from the Benchmark for Information Retrieva... | 908 | 5 | normal |
raduv98/MNLP_M3_rag_documents | none | 0.4978 | chemistry | 0.1823 | null | [] | 0 | 4 | normal | |
DanqingZ/so100_test_5 | none | 0.9149 | code | 0.0812 | 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": "v2.1",
"... | 3,576 | 26 | normal |
aisi-whitebox/mmlu_0_shot_cot_mo1_mo2_experiments_mo1_50_50_no_gibberish | none | 0.9065 | cybersecurity | 0.0836 | null | [
"deception",
"safety",
"sandbagging"
] | # Inspect Dataset: mmlu_0_shot_cot_mo1_mo2_experiments_mo1_50_50_no_gibberish
## Dataset Information
This dataset was created using the `create_inspect_dataset` function from the deception_sprint package on 2025-05-09.
### Model Information
- **Model**: `vllm/aisi-whitebox/llama-3.1-8b-instruct-finetuned-mo-v1-prefi... | 1,533 | 4 | normal |
johnyy212/cv-corpus-24-yue-jyutping-20hr | none | 0.6539 | code | 0.1127 | null | [] | 0 | 9 | normal | |
mlnomad/imnet1k_bull_mastiff | none | 0.6465 | code | 0.1061 | null | [] | 0 | 4 | normal | |
sjleslie/random_agreement_7_bins_long_38 | none | 0.6564 | climate | 0.1473 | null | [] | 0 | 5 | normal | |
openfun/tw-ly-law | legal | 0.9989 | none | 0.0006 | null | [] | # Taiwan Legislative Yuan Law Data(ly-tw-law)
您也可以透過網頁介面瀏覽 law 資料集：https://dataly.openfun.app/collection/list/law
## Data Fields
|資料欄位|說明|
|----------|----------|
|法律編號|為 law 的 id，其對應的原始資料為[立法院開放資料平台](https://data.ly.gov.tw/)所提供的[法名稱檔](https://data.ly.gov.tw/getds.action?id=301)資料|
|類別|可能的類別有：`母法`、`子法`|
|母法編號|如果類別為`子... | 1,079 | 11 | new_discovery |
electricsheepafrica/schools-with-access-to-computers-for-pedagogical-purposes-for-african-countries | none | 0.5984 | medical | 0.2215 | null | [] | ---
license: apache-2.0
tags:
- africa
- sustainable-development-goals
- world-health-organization
- development
---
# Schools with access to computers for pedagogical purposes (%)
## Dataset Description
This dataset provides country-level data for the indicator **"4.a.1 Schools with access to computers for peda... | 1,132 | 4 | normal |
flyingbugs/OpenR1-Math-220k-pruned-keep-0.2-end-start-0.5 | code | 0.6483 | none | 0.2589 | null | [] | 0 | 6 | normal | |
Brench/R1-Zero-GRPO-750 | none | 0.4924 | code | 0.1744 | null | [] | 0 | 4 | normal | |
ayousanz/vtuber-youtube-list-dataset | none | 0.8424 | legal | 0.0549 | null | [] | # VTuber YouTube Channel List Dataset
このデータセットは、VTuber チャンネルと VTuber でない（例：料理チャンネルなど）の YouTube チャンネルのメタデータを JSONL 形式でまとめたものです。各レコードは以下のフィールドを含んでいます：
- **channel_id**: YouTube チャンネルの固有 ID
- **title**: チャンネルのタイトル
- **description**: チャンネルの説明文
- **text**: タイトルと説明文を連結したテキスト（モデルの入力用に利用できます）
- **label**: バイナリラベル（VTuber の場合は... | 1,487 | 4 | normal |
lmms-lab/covost2_en-zh | biology | 0.3967 | none | 0.3229 | null | [] | 0 | 30 | boundary | |
ZixuanKe/cfa_extracted_exercise_sup_sample_from_policy_v1_1_rpo_iter_1_dpo_binarized_train_chunk_27 | none | 0.8631 | medical | 0.0575 | null | [] | 0 | 5 | normal | |
MisterMekdonelds/JD_extract_dataset_AML | none | 0.3892 | climate | 0.1305 | null | [] | 0 | 4 | normal | |
hirundo-io/bbq-nationality-bias-free-text | none | 0.6871 | legal | 0.1378 | null | [] | 0 | 194 | normal | |
mlfoundations-dev/stats_100000_samples | none | 0.5167 | chemistry | 0.2003 | null | [] | 0 | 4 | normal | |
french-open-data/amenagements-cyclables-a-grand-chambery | none | 0.9363 | cybersecurity | 0.036 | null | [
"amenagements-cyclables",
"pistes-cyclables",
"schema-cyclable",
"schema-directeur",
"velo",
"dataset_for_agent"
] | # Aménagements cyclables à Grand Chambéry
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Aménagements cyclables à Grand Chambéry** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/68c2959d51e20a3f2ab2c51d
## Description
Tracé des aména... | 658 | 9 | normal |
peekcoding/aigf | none | 0.4173 | code | 0.1146 | null | [] | 0 | 4 | normal |
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