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 |
|---|---|---|---|---|---|---|---|---|---|---|
asingh15/arc-barc-processed-direct-max4k-qwenbase-diagnostic-abs-qwensols-0205-1of24 | none | 0.8046 | medical | 0.1253 | null | [] | 0 | 7 | normal | |
DCAgent/DCAgent_dev_set_71_tasks_DCAgent_staqc-sandboxes-traces-terminus-2_Qwen3-1-7B_20476afbe8 | none | 0.8142 | code | 0.1585 | null | [] | 0 | 9 | normal | |
carpit680/record-test12323 | none | 0.9377 | code | 0.0561 | 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",
"... | 2,943 | 7 | normal |
GSMA/oran_spec_knowledge_graph | none | 0.418 | code | 0.2952 | null | [
"knowledge-graph",
"O-RAN",
"telecommunications",
"5G",
"RAG",
"graph-rag",
"neo4j",
"open-ran",
"network-automation",
"telecom-ai",
"cypher",
"hybrid-rag"
] | <div align="center">
# 🌐 Knowledge Graph for Open Radio Access Network (O-RAN)
**A large-scale, semantically grounded knowledge graph built from O-RAN Alliance specifications,<br>designed to enhance LLM reasoning and retrieval for next-generation telecom systems.**
[![License: CC BY-NC 4.0](https://img.shields.io/b... | 11,684 | 56 | normal |
Jouesmak/T2I-CoReBench-Images | none | 0.7784 | code | 0.1251 | null | [
"Benchmark",
"Evaluation",
"Diffusion Models",
"Autoregressive Models",
"Closed-Source Models"
] | # T2I-CoReBench-Images
## 📖 Overview
**T2I-CoReBench-Images** is the companion image dataset of [T2I-CoReBench](https://huggingface.co/datasets/lioooox/T2I-CoReBench). It contains images generated using **1,080 challenging prompts**, covering both **composition** and **reasoning** scenarios undere **real-world comple... | 2,313 | 86,329 | normal |
xwingspruebas/prueba | none | 0.3707 | finance | 0.3573 | null | [] | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## D... | 4,360 | 10 | normal |
Micsiu/eval-terminus-2-swebench-verified-random-100-folders-together-ai-qwen-qwen3-235b-823842a0 | none | 0.985 | code | 0.012 | null | [] | 0 | 0 | normal | |
TheFactoryX/edition_1109_deepmind-code_contests-readymade | code | 0.928 | none | 0.0587 | null | [
"readymades",
"art",
"duchamp"
] | # edition_1109_deepmind-code_contests-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[deepmind/code_contests](https://huggingface.co/datasets/deepmind/code_contests)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as ... | 948 | 6 | new_discovery |
OdysseusJamesStirling/github-issues | none | 0.423 | code | 0.2736 | null | [] | 0 | 4 | normal | |
Kairong-Han/Spurious-Token-Game | none | 0.8155 | code | 0.1421 | null | [] | # 🧩 Spurious Token Game (STG)
The **Spurious Token Game (STG)** dataset contains two subtasks designed for evaluating models under spurious correlations.
### Subtask: STG_E
- **Training splits:** STG_S, STG_M, and STG_L (representing different data sizes or difficulty levels)
- **Test splits:** IID (in-distrib... | 3,291 | 17 | normal |
carpit680/cmu_franka_exploration | none | 0.8744 | code | 0.1209 | null | [
"cmu_franka_exploration_dataset_converted_externally_to_rlds",
"rlds",
"openx",
"franka"
] | 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",
"... | 3,683 | 93 | normal |
GWDx/water-ethanol-event-RGB | chemistry | 0.5449 | none | 0.1989 | chemistry | [
"chemistry"
] | # GWDx/water-ethanol-event-RGB-test2
classification | 52 | 7 | normal |
french-open-data/puissance-moyenne-installee-par-point-de-charge-par-region-et-son-evolution-sur-12-mois-kva | cybersecurity | 0.9216 | none | 0.0732 | null | [
"enedis",
"evolution",
"gireve",
"mobilite",
"mobilite-electrique",
"points-de-charge",
"puissance-moyenne-installee",
"region",
"dataset_for_agent"
] | # Puissance moyenne installée par point de charge par région et son évolution sur 12 mois (kVA)
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Puissance moyenne installée par point de charge par région et son évolution sur 12 mois (kVA)** qui est dispon... | 1,122 | 7 | new_discovery |
He-Xingwei/TUBench | none | 0.6864 | code | 0.2974 | null | [] | # TUBench: Benchmarking Large Vision-Language Models on Trustworthiness with Unanswerable Questions
Large Vision-Language Models (LVLMs) have achieved remarkable progress on visual perception and linguistic interpretation but still struggle with hallucination—generating content that is incorrect or unrelated to the in... | 5,458 | 39 | normal |
SemanticExtraction/GOT_v1_text_only_v3_de_predictions | none | 0.808 | climate | 0.0677 | null | [] | 0 | 6 | normal | |
zjhhhh/iter2_multi_scores_adversary_42 | none | 0.7491 | code | 0.083 | null | [] | 0 | 4 | normal | |
Symato/RAG_UltraDomain | none | 0.7126 | code | 0.1475 | null | [] | Init from https://huggingface.co/datasets/TommyChien/UltraDomain | 64 | 14 | normal |
ccm/nsf-awards | none | 0.4736 | chemistry | 0.3047 | null | [] | This dataset contains the data made accessible by NSF [here](https://www.nsf.gov/awardsearch/download.jsp). It is only minimally edited to enable processing. The processing script can be found [here](https://github.com/cmccomb/scrape-nsf-awards).
Although this project uses NSF's data, it is not support, condoned, or e... | 363 | 50 | normal |
Rareshika/25_label_coco | none | 0.3119 | climate | 0.2483 | null | [] | 0 | 3 | normal | |
SubhanArifin/beams_2d_n32_64_32 | chemistry | 0.362 | none | 0.2908 | null | [] | rmin is normalized (wrt mid-fidelity mesh size) during data curation; thus rmin in this low-fidelity mesh was halved in the topology optimization runs. | 151 | 48 | boundary |
community-datasets/urdu_fake_news | none | 0.9925 | legal | 0.0031 | null | [] | # Dataset Card for Bend the Truth (Urdu Fake News)
## 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 Instanc... | 2,834 | 69 | normal |
pdf2dataset/dbac24042b3bbf4b0a7a8bd4bd3e9d6c | none | 0.6394 | biology | 0.0697 | null | [] | 0 | 5 | normal | |
chengfu0118/Unroll-Qwen2.5-7B-Instruct_1754911078_eval_759d_aime24_top-5-voting_num_prune_ffn_4_run-002 | none | 0.9904 | code | 0.0057 | null | [] | # chengfu0118/Unroll-Qwen2.5-7B-Instruct_1754911078_eval_759d_aime24_top-5-voting_num_prune_ffn_4_run-002
Precomputed model outputs for evaluation.
## Evaluation Results
### AIME24
- **Average Accuracy**: 2.00% ± 0.52%
- **Number of Runs**: 10
| Run | Accuracy | Questions Solved | Total Questions |
|-----|--------... | 589 | 6 | normal |
lerobotForScienceEdu/eval_YFE-v2-130-safety-merged-v2-ACT | none | 0.9163 | code | 0.0673 | 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",
"... | 2,869 | 5 | normal |
Asap7772/arc-agi-mixed-max4096-impabs-dpo-lr1e-7-beta0.1-16samp-rerun-flat-abs-6of32 | none | 0.9616 | climate | 0.0123 | null | [] | 0 | 5 | normal | |
communityai/system_identity_remove_preference_facebook | none | 0.6119 | code | 0.1747 | null | [] | 0 | 4 | normal | |
maghwa/OpenHermes-2-AR-10K-11 | none | 0.5588 | chemistry | 0.2224 | null | [] | 0 | 3 | normal | |
asingh15/arc-barc-processed-direct-max4k-abs-base-no-oracle-qwensolsarc1-0107-3of4 | none | 0.9121 | code | 0.0413 | null | [] | 0 | 11 | normal | |
Quadzilla/record-test2 | none | 0.921 | code | 0.0737 | 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 | 6 | normal |
introspection-auditing/quirk_run1_90_induce | none | 0.8123 | medical | 0.0445 | null | [] | 0 | 4 | normal | |
AChierici84/sentiment-roberta-finetuned | none | 0.5201 | chemistry | 0.0984 | null | [] | 0 | 27 | normal | |
tyhuang/DreamPhysics | chemistry | 0.5042 | none | 0.251 | null | [] | This is the reconstruction data and simulation config in paper: https://arxiv.org/pdf/2406.01476 | 96 | 31 | normal |
gohnwej/winter-olympics-2026-qa-dataset | none | 0.9487 | code | 0.0174 | null | [] | # Quantum Computing QA Dataset
Question-Answer dataset for winter-olympics-2026
## Dataset Description
- **Size**: 16 total examples
- **Splits**: {
"train": 12,
"validation": 2,
"test": 2
}
- **Features**: question-answer pairs about quantum computing concepts
- **Source**: Wikipedia articles
## Usage
```py... | 940 | 65 | normal |
AIEnergyScore/image_generation | none | 0.4148 | climate | 0.1877 | null | [] | 0 | 15 | normal | |
MoeReward/combined_preference_dataset_qwen | none | 0.6674 | code | 0.0814 | null | [] | 0 | 4 | normal | |
reasoning-proj/exp_rob_dfiltered_science_Phi-4-reasoning-plus_madversarial_cont_wrong_reasoning_t50 | none | 0.8864 | math | 0.0521 | null | [] | 0 | 4 | normal | |
CodeDPO/rl_dataset_llama3_instruct_8b_20241230_human_eval_format | none | 0.7978 | code | 0.1078 | null | [] | 0 | 9 | normal | |
Zilinghan/scicode | finance | 0.421 | none | 0.2916 | null | [
"coding",
"physics",
"material-science",
"math",
"chemistry",
"biology"
] | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## D... | 4,360 | 12 | boundary |
FaalSa/f1_it | none | 0.4276 | biology | 0.1459 | null | [] | 0 | 4 | normal | |
MaziyarPanahi/Synthia-v1.5-II-sharegpt | none | 0.6461 | code | 0.1031 | null | [] | 0 | 4 | normal | |
MasonKR/customhkcode2 | code | 0.5634 | climate | 0.122 | null | [] | 0 | 6 | normal | |
namejun12000/AW_finetuning20_include_beauty | none | 0.5262 | code | 0.2256 | null | [] | 0 | 4 | normal | |
weqweasdas/ultra_feedback_binarized_for_preference | none | 0.99 | code | 0.0025 | null | [] | # Dataset Card for "ultra_feedback_binarized_for_preference"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 193 | 4 | normal |
french-open-data/donnees-theoriques-du-reseau-hopla-communaute-de-communes-de-la-plaine-d-estrees | cybersecurity | 0.9433 | none | 0.0474 | null | [
"bus",
"gtfs",
"gtfs-rt",
"hopla",
"ligne-reguliere",
"netex",
"oise",
"point-darret",
"siri",
"transport",
"transport-a-la-demande",
"transport-en-commun",
"dataset_for_agent"
] | # Données théoriques du réseau Hoplà - Communauté de Communes de la Plaine d'Estrées
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Données théoriques du réseau Hoplà - Communauté de Communes de la Plaine d'Estrées** qui est disponible à l'adresse https... | 1,160 | 6 | new_discovery |
ganglii/pku-saferlhf-sft | none | 0.4425 | code | 0.1347 | null | [] | 0 | 9 | normal | |
alea-institute/kl3m-data-dotgov-www.ussc.gov | legal | 0.9606 | none | 0.0316 | null | [] | # KL3M Data Project
> **Note**: This page provides general information about the KL3M Data Project. Additional details specific to this dataset will be added in future updates. For complete information, please visit the [GitHub repository](https://github.com/alea-institute/kl3m-data) or refer to the [KL3M Data Project... | 3,928 | 4 | new_discovery |
DeepNLP/humanoid-robot-ai-agent | none | 0.865 | cybersecurity | 0.0903 | null | [] | # Humanoid Robot Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP
This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well a... | 10,867 | 5 | normal |
Froink/HAID_zipped | none | 0.7304 | code | 0.1746 | null | [] | # [BMVC2025] An Exploratory Study on Abstract Images and Visual Representations Learned from Them
**HAID** (Hierarchical Abstraction Image Dataset) is a collection of SVG images generated from existing raster datasets at multiple levels of abstraction (controlled by the number of geometric primitives). HAID is designe... | 7,616 | 1,782 | normal |
chenneking/citegeist-milvus-db | chemistry | 0.456 | none | 0.375 | null | [
"arxiv"
] | Contains the entire arXiv metadata dataset, including 768-dimensional embeddings of all abstracts generated using sentence-transformer/all-MiniLM-L6-v2.
This database is an artifact of the Citegeist project ([Github](https://github.com/chenneking/citegeist)) | 259 | 11 | boundary |
zjhhhh/Qwen3b_rlcf_iter1_18000 | none | 0.4525 | chemistry | 0.223 | null | [] | 0 | 5 | normal | |
french-open-data/fiches-signaletiques-des-points-geodesiques-et-des-reperes-de-nivellement | cybersecurity | 0.8696 | none | 0.1232 | null | [
"bornes-geodesiques",
"geodesie",
"nivellement",
"reperes-de-nivellement",
"dataset_for_agent"
] | # Fiches signalétiques des points géodésiques et des repères de nivellement
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Fiches signalétiques des points géodésiques et des repères de nivellement** qui est disponible à l'adresse https://www.data.gouv.f... | 863 | 9 | new_discovery |
limingme/ahat_task_40k_v1 | none | 0.5458 | code | 0.0918 | null | [] | 0 | 6 | normal | |
LovrOP/zavrsni_dataset_robodk | none | 0.4034 | climate | 0.1377 | null | [] | 0 | 5 | normal | |
Rick0331/lerobot-openarm-collect-bowl_rgb_test_merged | none | 0.9335 | code | 0.0602 | 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",
"... | 4,189 | 16 | normal |
PRAIG/polish-scores | none | 0.6401 | code | 0.1142 | null | [] | 0 | 81 | normal | |
igor-freik/cedr-classification_300 | none | 0.4576 | chemistry | 0.18 | null | [] | 0 | 4 | normal | |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_7606d107-b17e-42a6-98bc-223768f9259a | none | 0.6534 | code | 0.1683 | null | [] | 0 | 4 | normal | |
davidadamczyk/sst5-balanced | none | 0.5301 | chemistry | 0.1245 | null | [] | 0 | 18 | normal | |
alorenc/c4_15B_5M_llama2_tok | biology | 0.5191 | none | 0.2034 | null | [] | 0 | 11 | normal | |
jordan-benjamin/fineweb-edu-L4K-L2 | none | 0.8738 | chemistry | 0.0284 | null | [] | 0 | 34 | normal | |
mlfoundations-dev/meta_chat_reasoning_50_50_system_eval_bba0 | none | 0.985 | code | 0.0129 | null | [] | # mlfoundations-dev/meta_chat_reasoning_50_50_system_eval_bba0
Precomputed model outputs for evaluation.
## Evaluation Results
### Summary
| Metric | AIME24 | AMC23 | MATH500 | MMLUPro | JEEBench | GPQADiamond | LiveCodeBench | CodeElo | CodeForces |
|--------|------|-----|-------|-------|--------|-----------|-----... | 3,023 | 5 | normal |
chiyuanhsiao/audio_L2-regular-14_llama-questions | none | 0.7565 | code | 0.0897 | null | [] | 0 | 3 | normal | |
Almheiri/arab_culture_clean | none | 0.7098 | chemistry | 0.0518 | null | [] | 0 | 15 | normal | |
extralit-dev/test_import_dataset_from_hub_with_classlabel_2ff7d53b-a273-4c5f-831b-773d61fb8f28 | none | 0.7582 | code | 0.0549 | null | [] | 0 | 4 | normal | |
tbrugger/JudgeDataset | none | 0.3407 | legal | 0.1982 | null | [] | 0 | 6 | normal | |
rbojja/zero-shot-intent-classification | none | 0.6863 | code | 0.0887 | null | [] | 0 | 29 | normal | |
ClarusC64/clinical-quad-neural-stress-buffer-lag-coupling-neuro-deterioration-v0.7 | medical | 0.9967 | none | 0.0028 | medical | [
"clinical-trials",
"quad-coupling",
"neural",
"neuro-deterioration",
"uncertainty-aware"
] | # What this repo does
This repository contains a Clarus v0.7 dataset modeling neuro deterioration using a quad-coupling system representation.
The dataset extends the v0.6 intervention layer by introducing uncertainty geometry.
The question addressed by earlier versions was:
Can the system be stabilized?
v0.7 adds... | 9,150 | 163 | normal |
VGraf/generation_multi_1746753726 | none | 0.8344 | code | 0.1566 | null | [] | # allenai/open_instruct: Generation Dataset
See https://github.com/allenai/open-instruct/blob/main/docs/algorithms/rejection_sampling.md for more detail
## Configs
```
args:
{'add_timestamp': True,
'dataset_end_idx': 147000,
'dataset_mixer_list': ['VGraf/no_safety_tulu_pref', '160000'],
'dataset_shuffle_seed': 42... | 2,322 | 4 | normal |
kjngansgfa/dataset_2p4g1lph | none | 0.504 | chemistry | 0.1204 | null | [] | 0 | 4 | normal | |
ilayzvulun/gym_churn | none | 0.6897 | code | 0.1638 | null | [] | README
Project Overview
This project performs an Exploratory Data Analysis (EDA) on a gym membership dataset in order to understand patterns that may influence customer churn.
The analysis focuses on identifying whether weekly training frequency has a meaningful effect on churn and how different variables in the datase... | 6,450 | 14 | normal |
yiyic/Latn_dev | climate | 0.5197 | none | 0.2295 | null | [] | 0 | 5 | normal | |
pietrolesci/civilcomments-wilds | none | 0.9394 | legal | 0.0296 | null | [] | This is the CivilComments datasets available in the [`wilds`](https://github.com/p-lambda/wilds/blob/472677590de351857197a9bf24958838c39c272b/wilds/datasets/civilcomments_dataset.py#L9) library library and downloadable from [codalab]("https://worksheets.codalab.org/rest/bundles/0x8cd3de0634154aeaad2ee6eb96723c6e/conten... | 705 | 832 | normal |
lucoa/yo | none | 0.3249 | biology | 0.1748 | null | [] | 0 | 4 | normal | |
Mdls35/causal_synthetic_scenarios | none | 0.8325 | chemistry | 0.0655 | null | [] | # Causal Synthetic Scenarios
This directory provides tools for generating synthetic datasets to benchmark causal discovery and inference methods, as implemented in the methodology of the KNOSYS-D-25-17892 paper. The source code for these generators is available in the [CausalMorph repository](https://github.com/MarSH-... | 5,966 | 4 | normal |
jaimadhukar/legal-advisor-gemma-chat-cleaned | legal | 0.5628 | none | 0.2368 | null | [] | 0 | 5 | normal | |
awaistahir0001/testing_dataset | none | 0.3792 | finance | 0.334 | null | [] | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## D... | 4,360 | 4 | normal |
JisooSong/sandwich_286to290_vhlv | none | 0.9497 | code | 0.0476 | 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",
"... | 5,388 | 7 | normal |
jiajunfanthu/uf_split0_responses_K8_reward.json | none | 0.5509 | climate | 0.1327 | null | [] | 0 | 4 | normal | |
lichenglin0824/Dataset_UR10_01_27_12_21 | none | 0.9099 | code | 0.0837 | 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",
"... | 3,692 | 37 | normal |
etherfi/1009 | none | 0.4653 | chemistry | 0.1562 | null | [] | 0 | 5 | normal | |
TheFactoryX/edition_0514_argilla-databricks-dolly-15k-curated-en-readymade | none | 0.9866 | code | 0.0121 | null | [
"readymades",
"art",
"duchamp"
] | # edition_0514_argilla-databricks-dolly-15k-curated-en-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[argilla/databricks-dolly-15k-curated-en](https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-en)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of tak... | 999 | 5 | normal |
tacab/som_agri_QN | none | 0.3322 | biology | 0.281 | null | [] | 0 | 3 | normal | |
tytodd/qwen3.5-4b-smoke-test | none | 0.988 | code | 0.0097 | null | [] | # qwen3.5-4b-smoke-test
- Repo: `tytodd/qwen3.5-4b-smoke-test`
- Local path: `datasets/qwen3.5-4b-smoke-test`
- Config: `configs/datasets/smoke-test/smoke-test.yaml`
| benchmark | train | val | ood | all |
| --- | --- | --- | --- | --- |
| customer_support_tickets_gorkem | 5.00% | 0.00% | | 3.33% |
| mfrc | 0.00% | ... | 3,310 | 13 | normal |
kjngansgfa/dataset_2tk8a9vm | none | 0.4776 | math | 0.0988 | null | [] | 0 | 4 | normal | |
yoonholee/completions_AIME2024_AIME2024-SFT-hint1_Qwen3-4B | none | 0.6819 | code | 0.1669 | null | [] | 0 | 4 | normal | |
ThoughtTokens/MuSR_thoughts | none | 0.6101 | code | 0.1324 | null | [] | 0 | 9 | normal | |
yzsun2025/flexiv_grab_plate_gripper_and_hand | none | 0.9085 | code | 0.0826 | null | [
"flexiv",
"dual_arm",
"robotics"
] | 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",
"... | 3,327 | 154 | normal |
mzio/aprm-sft_thinkact-Eaprm_tw_tr_medium_hi-Gaprm_qwen3_ap_nobandit-S42-R0-ap1-train_all-b099 | none | 0.9752 | code | 0.0123 | null | [] | # Act-PRM Rollout Dataset
## Run Metadata
- **run_name**: `act-prm-v2-ia=0-rr=0-ec=act_prm_tw_treasure_medium_hi-gc=aprm_qwen3_ap_nobandit-tc=aprm_for_sft100-rbc=default-mc=hf_qwen3_4b_inst_2507-lc=r8_a16_qkvo-nf=1-ao=1-ho=1-gs=8-bs=8-lr=4e_05-ns=4-s=42-r=0`
- **run_cmd**: `main_pytorch.py --env_config act_prm/tw_tre... | 856 | 5 | normal |
ycfNTU/masum_768_llama70b_update1 | none | 0.9745 | code | 0.0107 | null | [] | # Dataset Card for "masum_768_llama70b_update1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 180 | 3 | normal |
marjanns/summarized_chat | none | 0.6636 | code | 0.0722 | null | [] | 0 | 4 | normal | |
andrewsiah/PersonaPromptPersonalLLM_970 | none | 0.9718 | code | 0.0194 | null | [] | # Dataset Card for "PersonaPromptPersonalLLM_970"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 182 | 3 | normal |
GabrielAndrei17/RO_offensive_political_comments | none | 0.606 | climate | 0.1104 | null | [] | 0 | 8 | normal | |
electricsheepafrica/Agricultural-Production-In-Africa-1961-to-2023 | biology | 0.7032 | none | 0.1628 | null | [
"climate",
"finance",
"biology"
] | # Agricultural Production In Africa Dataset
## Dataset Overview
- **Dataset Name**: Cleaned Agricultural Production Data
- **Source**: Food and Agriculture organization (FAO)
- **Dataset Type**: Time-series agricultural statistics
- **Number of Rows**: ~790,714
- **Format**: CSV
- **Size**: [File size]
## Dataset De... | 3,314 | 9 | normal |
MaskedActionModel/Masked_action_model | none | 0.8194 | code | 0.0923 | null | [] | # Zarr数据集格式说明
本文档详细描述了生成的Zarr数据集的格式、字段含义和数据结构。
## 📁 数据集类型
本工具集生成两种类型的Zarr数据集：
1. **Diffusion Policy (DP) 训练数据集** - 用于扩散策略训练
2. **Masked Action Model (MAM) 训练数据集** - 用于掩码动作模型训练
## 🎯 Diffusion Policy (DP) 数据集格式
### **数据组织结构**
```
0901_PushCube_points_mask_dp.zarr/
├── data/ # 数据组
│ ├─... | 4,245 | 3 | normal |
yzhuang/metatree_mfeat_morphological | chemistry | 0.4804 | none | 0.4323 | null | [] | # Dataset Card for "metatree_mfeat_morphological"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 182 | 6 | boundary |
bamshyd/bams43 | none | 0.4583 | chemistry | 0.1661 | null | [] | 0 | 4 | normal | |
reasoning-proj/exp_rob_dfiltered_science_EXAONE-Deep-32B_mbenign_complete_step_t50 | none | 0.7278 | chemistry | 0.1207 | null | [] | 0 | 23 | normal | |
HHS-Official/weekly-cumulative-influenza-vaccination-coverage-a | none | 0.6487 | medical | 0.192 | null | [
"hhs",
"cdc",
"nis-ccm",
"nis-flu"
] | # Weekly Cumulative Influenza Vaccination Coverage and Comparison Between 2023–24 and 2024–25± by Jurisdiction, Children 6 Months–17 Years, United States
## Description
• Weekly Cumulative Influenza Vaccination Coverage and Comparison Between 2023-24 and 2024-25 by Jurisdiction, Children 6 Months–17, United States.
... | 1,575 | 5 | normal |
svjack/Watanuki_Kimihiro_images | none | 0.8347 | code | 0.1038 | null | [] | 
 | 241 | 6 | normal |
babytreecc/test-deepseek-r1-distill-DeepSeek-R1-Distill-Qwen-1.5B | none | 0.6187 | math | 0.2061 | 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 test-deepseek-r1-distill-DeepSeek-R1-Distill-Qwe... | 19,196 | 10 | normal |
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