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 |
|---|---|---|---|---|---|---|---|---|---|---|
Sangsang/ThinkSafe-0.6B-n5_filtered_Olmo-3.1-32B-Instruct_eps10 | code | 0.5722 | none | 0.3726 | null | [] | 0 | 7 | normal | |
yoonholee/completions_deepscaler-hard_RL-hint-mixtrue-zerorew_deepscaler-hard | code | 0.7805 | none | 0.1382 | null | [] | 0 | 4 | normal | |
KadamParth/NCERT_Social_Studies_10th | none | 0.5529 | climate | 0.171 | null | [
"ncert",
"social_studies",
"educational",
"intelligent_tutoring_system",
"history",
"geography",
"its"
] | 0 | 41 | normal | |
PL2011/lebai-gripper-plate | none | 0.9635 | code | 0.0286 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=PL2011/lebai-gripper-plate">
<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-x... | 8,343 | 38 | normal |
carpe002/GeoGoal-SGVR | math | 0.9225 | none | 0.0477 | null | [
"geometry",
"reasoning",
"multimodal",
"geometric-reasoning",
"subgoal-verification"
] | # GeoGoal-SGVR Dataset
This is the official dataset for the paper **"Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward"**.
## Dataset Description
GeoGoal-SGVR is a multimodal geometry reasoning dataset where intermediate sub-goals are formally verified and automatically checkable... | 2,004 | 23 | new_discovery |
KomeijiForce/llama3_vocabulary_cluster | none | 0.7868 | code | 0.119 | null | [] | This dataset contains the clusters discovered in the vocabulary embeddings of the ```llama3-8b-instruct``` model.
The 128256 vocabulary embeddings are separated into 1024 clusters by k-means, which show pattern correlations probably undesirable for diverse generation.
We also prompt ```GPT-4o``` to summarize the comm... | 564 | 4 | normal |
youssefkhalil320/epub-documents-dataset-v2 | none | 0.6515 | finance | 0.0826 | null | [] | 0 | 4 | normal | |
SeaEval/c_eval | none | 0.5802 | climate | 0.1468 | null | [] | 0 | 3 | normal | |
zjhhhh/iter2_ver2_scores_adversary_11 | none | 0.7631 | code | 0.0614 | null | [] | 0 | 4 | normal | |
GroNLP/ik-nlp-22_pestyle | none | 0.9858 | code | 0.0101 | null | [] | # Dataset Card for IK-NLP-22 Project 1: A Study in Post-Editing Stylometry
## Table of Contents
- [Dataset Card for IK-NLP-22 Project 1: A Study in Post-Editing Stylometry](#dataset-card-for-ik-nlp-22-project-1-a-study-in-post-editing-stylometry)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#... | 10,467 | 26 | normal |
french-open-data/jeu-de-donnees-budget-primitif | cybersecurity | 0.5318 | finance | 0.2888 | null | [
"budget",
"budget-primitif",
"challengedata",
"dataset_for_agent"
] | # Jeu de données Budget primitif
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Jeu de données Budget primitif** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/637f81a3613938b9e8e13254
## Description
Ce jeu de données concerne le bud... | 826 | 9 | normal |
c0derish/Tess_features_extracted | none | 0.5528 | climate | 0.1166 | null | [] | 0 | 2 | normal | |
zjhhhh/iter2_multi_scores_adversary_0 | none | 0.7347 | code | 0.0764 | null | [] | 0 | 4 | normal | |
interneuronai/advertisement_cap_on_banner_classification_bert_dataset | none | 0.8937 | code | 0.0492 | null | [] | ### Advertisement Cap on Banner Classification
**Description:** Automatically classify and assign appropriate advertisement cap to banners to streamline manufacturing and delivery processes.
## How to Use
Here is how to use this model to classify text into different categories:
from transformers import AutoM... | 963 | 8 | normal |
ibm-aimc/wikitext-103-raw | none | 0.7168 | biology | 0.0748 | null | [] | 0 | 7 | normal | |
electricsheepafrica/health-expenditure-tracking | medical | 0.9098 | none | 0.086 | medical | [
"health-financing",
"national-health-accounts",
"health-expenditure",
"NHA",
"SHA",
"healthcare",
"sub-saharan-africa"
] | # Health Expenditure Tracking (NHA/SHA)
## Abstract
This synthetic dataset models country-level health expenditure tracking capacity across three SSA scenarios. Each scenario contains 10,000 records capturing CHE levels, financing sources (SHA classification), provider allocation, NHA institutionalization, data quali... | 1,078 | 941 | normal |
surgingTu/robot-maniskill-image-state-dataset-v1 | none | 0.7376 | code | 0.2208 | null | [
"robot",
"maniskill"
] | # Robot ManiSkill Image–State Dataset
## 0. Update
## 12.22
pickcube_rgb_random_v2: having a broader distribution of viewpoints and qpos values
## 12.14
pickcube_rgb_traj_v3: official PickCube-v1 scene RGBD trajectories (Type-1 scaling baseline)
### 12.2
delete pickcube_rgb_traj_v1
### 11.30
pickcube_rgb_traj_v2: ... | 2,601 | 340 | normal |
badrex/kinyarwanda-speech-sample | none | 0.9754 | cybersecurity | 0.0135 | null | [] | # Kinyarwanda Automatic Speech Recognition Dataset
## Dataset Description
This dataset contains a sample from the 500 hours of Kinyarwanda speech data covering Health, Government, Finance, Education, and Agriculture domains, converted from the [Kaggle Kinyarwanda ASR Track A competition](https://www.kaggle.com/compet... | 1,453 | 6 | normal |
slinusc/PubMedAbstractsSubset | medical | 0.7217 | none | 0.119 | null | [
"pubmed"
] | # PubMed Abstracts Subset
This dataset contains a probabilistic sample of publicly available PubMed metadata sourced from the [National Library of Medicine (NLM)](https://pubmed.ncbi.nlm.nih.gov/).
If you're looking for the precomputed embedding vectors (MedCPT) used in our work [*Efficient and Reproducible Biomedi... | 2,386 | 495 | normal |
reasoning-proj/exp_rob_dfiltered_Llama-3_1-Nemotron-Nano-8B-v1_mneutral_add_random_text_t10 | none | 0.5002 | math | 0.3028 | null | [] | 0 | 4 | normal | |
gh0stwin/arc_1d-nano | none | 0.5573 | climate | 0.1201 | null | [] | 0 | 19 | normal | |
Luffytaro-1/asr_en_ar_switch_split_62 | none | 0.7794 | code | 0.0733 | null | [] | 0 | 2 | normal | |
PursuitOfDataScience/gsm8k-thinking | math | 0.9896 | none | 0.009 | math | [
"reasoning",
"chain-of-thought",
"minimax",
"math",
"gsm8k"
] | # GSM8K Thinking
This dataset contains responses generated by [MiniMax-M2.1](https://www.minimax.io/) for math word problems from the [openai/gsm8k](https://huggingface.co/datasets/openai/gsm8k) dataset.
## Dataset Description
The dataset captures both the **extended thinking process** and **final answers** from Min... | 3,166 | 28 | normal |
Junforjune/hanok-dataset0518 | none | 0.6143 | code | 0.0915 | null | [] | 0 | 4 | normal | |
Better-Ai-Better-Life/Ai-Instractions-High-Solving-Problems | none | 0.6564 | code | 0.2101 | null | [] | ### License: Cosmic Openness License (COL) - Power Unleashed Edition
**Title:** *AI Instructions Makes AI Better at Solving Hard Problems*
**License Text:**
This is your free pass to a powerhouse of code and ideas. No one owns it—it’s like a lightning bolt dropped from the sky, yours to grab and use however you wan... | 5,319 | 7 | normal |
test-gen/livecodebench_qwen-7b-random_t0.0_n1_generated_tests | code | 0.7196 | none | 0.2208 | null | [] | 0 | 4 | normal | |
ThreeBibas/recipie-canny-image | none | 0.4972 | climate | 0.1142 | null | [] | 0 | 21 | normal | |
Lots-of-LoRAs/task1167_penn_treebank_coarse_pos_tagging | none | 0.9324 | biology | 0.0387 | null | [] | # Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1167_penn_treebank_coarse_pos_tagging
## Dataset Description
- **Homepage:** https://github.com/allenai/natural-instructions
- **Paper:** https://arxiv.org/abs/2204.07705
- **Paper:** https://arxiv.org/abs/2407.00066
-... | 2,316 | 90 | normal |
jmhb/PaperSearchRL_v5_gv3_n3000_test300_parav1pcnt50 | none | 0.5064 | chemistry | 0.2368 | null | [] | 0 | 7 | normal | |
DCAgent2/DCAgent2_terminal_bench_2_DCAgent_nl2bash-nl2bash-bugsseq_Qwen3-8B-maxEps24-112a233825c | none | 0.6115 | code | 0.2127 | null | [] | 0 | 12 | normal | |
xhaka3456/openarm_test | none | 0.9636 | code | 0.0293 | 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",
"... | 5,417 | 18 | normal |
JackMcKechnie/msmarco_passage_trec_dl_2019_judged_sebastian_hofstaetter_distilbert_dot_tas_b_b256_msmarco.flex | none | 0.9607 | code | 0.0227 | null | [
"pyterrier",
"pyterrier-artifact",
"pyterrier-artifact.dense_index",
"pyterrier-artifact.dense_index.flex"
] | # msmarco_passage_trec_dl_2019_judged_sebastian_hofstaetter_distilbert_dot_tas_b_b256_msmarco.flex
## Description
*TODO: What is the artifact?*
## Usage
```python
# Load the artifact
import pyterrier as pt
artifact = pt.Artifact.from_hf('JackMcKechnie/msmarco_passage_trec_dl_2019_judged_sebastian_hofstaetter_distil... | 649 | 3 | normal |
ShauryaSinghh/xuv700-sdxl-dreambooth3-dataset-jsonl | none | 0.6452 | code | 0.1112 | null | [] | 0 | 3 | normal | |
colabfit/23-Single-Element-DNPs_all_trajectories | chemistry | 0.9734 | none | 0.0197 | null | [
"molecular dynamics",
"mlip",
"interatomic potential"
] | ### <details><summary>Cite this dataset </summary>Andolina, C. M., and Saidi, W. A. _23-Single-Element-DNPs all trajectories_. ColabFit, 2024. https://doi.org/10.60732/a4e0fea6</details>
#### This dataset has been curated and formatted for the ColabFit Exchange
#### This dataset is also available on the ColabFit Ex... | 2,312 | 7 | new_discovery |
Ayushgupta301/WikiHow-taskset | code | 0.9696 | none | 0.025 | null | [] | (Works with [Mobile-Env >=4.0](https://github.com/X-LANCE/Mobile-Env).)
# WikiHow Task Set
WikiHow task set is an InfoUI interaction task set based on
[Mobile-Env](https://github.com/X-LANCE/Mobile-Env) proposed in [*Mobile-Env:
Building Qualified Evaluation Benchmarks for LLM-GUI
Interaction*](https://arxiv.org/abs/... | 11,312 | 130 | new_discovery |
faezeb/verifiable-reasoning-50k-v2 | none | 0.5189 | math | 0.2713 | null | [] | 0 | 4 | normal | |
Elfsong/JITT | none | 0.2901 | climate | 0.1282 | null | [] | 0 | 8 | normal | |
meoconxinhxan/dolphin_r1 | none | 0.5306 | biology | 0.2479 | null | [] | 0 | 11 | normal | |
maomlab/example_dataset | none | 0.3476 | climate | 0.2239 | biology | [
"biology"
] | 0 | 11 | tag_disagree | |
1g0rrr/grab_orange2 | none | 0.4711 | biology | 0.2873 | null | [
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). | 81 | 33 | normal |
supergoose/buzz_sources_271_visual-basic | none | 0.7858 | code | 0.0663 | null | [] | 0 | 4 | normal | |
SkillFactory-dev/OT_Ref_NoV13Part___openthoughts__2000000_end2200000__reflection_chunk_101 | code | 0.6188 | none | 0.313 | null | [] | 0 | 4 | normal | |
mlfoundations-dev/organic_chemistry_train_fasttext | chemistry | 0.988 | none | 0.0052 | null | [] | 0 | 4 | new_discovery | |
ddecosmo/third-eye_master_dataset | none | 0.7936 | code | 0.0672 | null | [] | 0 | 9 | normal | |
Raniahossam33/aligned-asm2asm-train-complete | none | 0.5786 | chemistry | 0.1352 | null | [] | 0 | 18 | normal | |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_bc1d82a4-2921-4ec0-beaf-58e1fd52a4aa | none | 0.6514 | code | 0.1503 | null | [] | 0 | 4 | normal | |
neryotw/bimanual_blue_block_handover_18_v30_15d | none | 0.9061 | code | 0.0897 | 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",
"... | 3,809 | 9 | normal |
ExplosionNuclear/Exp2 | none | 0.2593 | chemistry | 0.2092 | null | [] | 0 | 4 | normal | |
cchoi1/kodcode-complete_10000_qwen7b_att_iter0_att5_sol5 | code | 0.4131 | none | 0.3385 | null | [] | 0 | 6 | boundary | |
malaysia-ai/indonesian-youtube | none | 0.9221 | cybersecurity | 0.0455 | null | [] | # Indonesian Youtube
Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/speech/indonesian-youtube
## how to download
```bash
huggingface-cli download --repo-type dataset \
--include '*.z*' \
--local-dir './' \
malaysia-ai/indonesian-youtube
wget https://www.7-zip.org/a/7z2301-linux-x64.tar.x... | 840 | 7 | normal |
dgambettaphd/D_llm2_gen7_WXS_doc1000_synt64_rndgen_lr1e-04_acm_SYNLAST | none | 0.7246 | chemistry | 0.1372 | null | [] | 0 | 5 | normal | |
mteb/OPP115UserAccessEditAndDeletionLegalBenchClassification | legal | 0.9828 | none | 0.0136 | null | [
"mteb",
"text"
] | <!-- 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... | 7,311 | 30 | new_discovery |
YC-DREAL/ImageNet_Concept_Preference | none | 0.3127 | chemistry | 0.1667 | null | [] | 0 | 4 | normal | |
minhthong/flashdeal_data_TNG_historical_signal | none | 0.7602 | code | 0.094 | null | [] | 0 | 5 | normal | |
chfanyang/grasp_candy | none | 0.9362 | code | 0.0572 | 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"... | 3,070 | 25 | normal |
chengfu0118/Unroll-Qwen2.5-7B-Instruct_1754642117_eval_3444_gpqadiamond_skip_ffn_idx_2 | none | 0.9851 | math | 0.0069 | null | [] | # chengfu0118/Unroll-Qwen2.5-7B-Instruct_1754642117_eval_3444_gpqadiamond_skip_ffn_idx_2
Precomputed model outputs for evaluation.
## Evaluation Results
### GPQADiamond
- **Average Accuracy**: 35.86% ± 1.56%
- **Number of Runs**: 3
| Run | Accuracy | Questions Solved | Total Questions |
|-----|----------|---------... | 424 | 117 | normal |
french-open-data/budget-supplementaire-du-departement-des-alpes-de-haute-provence-2025 | none | 0.7038 | cybersecurity | 0.209 | finance | [
"budget",
"depense",
"document-budgetaire",
"finance",
"recette",
"dataset_for_agent"
] | # Budget supplémentaire du Département des Alpes de Haute-Provence 2025
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Budget supplémentaire du Département des Alpes de Haute-Provence 2025** qui est disponible à l'adresse https://www.data.gouv.fr/datase... | 680 | 7 | tag_disagree |
kaiwenw/nov2_aft_llama70b_1.1 | none | 0.4204 | biology | 0.1734 | null | [] | 0 | 8 | normal | |
itisarainyday/llama3_answers_v6 | none | 0.5553 | code | 0.1536 | null | [] | 0 | 4 | normal | |
freshpearYoon/v3_train_free_concat_30 | none | 0.5458 | climate | 0.1802 | null | [] | 0 | 4 | normal | |
french-open-data/intercommunalites-du-pays-de-brest-etiquettes | none | 0.4948 | cybersecurity | 0.2753 | null | [
"communautes",
"decoupages",
"inter-communalites-du-pays-de-brest-etiquettes",
"limites",
"limites-decoupages",
"pays",
"dataset_for_agent"
] | # Intercommunalités du Pays de Brest (étiquettes)
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Intercommunalités du Pays de Brest (étiquettes)** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/6480962c7f536438099302a9
## Description
... | 790 | 5 | normal |
talsen89/newrro | none | 0.6406 | climate | 0.1451 | null | [] | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [... | 5,038 | 12 | normal |
ceselder/loracle-training-rollouts | code | 0.4558 | none | 0.4355 | null | [
"loracle",
"lora",
"mechinterp",
"safety"
] | # Loracle Training Rollouts
Training data for behavioral LoRA fine-tuning. Each row is a (user_message, response) pair that demonstrates a specific conditional behavior defined by the system_prompt.
## Generation
- **Model**: Gemini 3.1 Flash Lite via OpenRouter
- **Method**: For each system prompt, the model was as... | 1,465 | 34 | boundary |
AmirhoseinGH/Qwen3_VL_4B_Thinking_MMOpenR1_8k_verified | none | 0.6356 | code | 0.0903 | null | [] | 0 | 10 | normal | |
french-open-data/asus-notebook-b3402fba | cybersecurity | 0.8567 | none | 0.102 | null | [
"dataset_for_agent"
] | # ASUS Notebook B3402FBA
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **ASUS Notebook B3402FBA** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/6852daf3070e38b1f4832e68
## Description
This dataset provides the repairability index sco... | 1,359 | 6 | new_discovery |
NewstaR/longformgraded-nodedup | none | 0.5305 | climate | 0.1125 | null | [] | 0 | 4 | normal | |
japhba/cot-oracle-futurelens | none | 0.5172 | code | 0.1273 | null | [] | 0 | 12 | normal | |
reasoning-degeneration-dev/gepa-exp-per_trace-rlm-20260220-083526 | math | 0.5928 | none | 0.3766 | null | [
"gepa",
"rlm",
"prompt-optimization",
"aime",
"experiment",
"reflection-mode-per_trace"
] | # gepa-exp-per_trace-rlm-20260220-083526
GEPA prompt optimization experiment on AIME math problems.
**Task LM**: `openai/gpt-4.1-mini` | **Reflection LM**: `openai/gpt-5` | **Reflection Mode**: `per_trace` | **Last updated**: 2026-02-20 21:30 UTC
## Results
| Run | Method | k | Mode | Val Score | Test Acc | Tokens ... | 2,682 | 59 | normal |
Vyvo/Emilia-YODAS-DE | none | 0.9837 | code | 0.0081 | null | [] | # Emilia-YODAS - DE
Clean version with only text and audio from the [Emilia Dataset](https://huggingface.co/datasets/amphion/Emilia-Dataset).
- **Samples**: 2,005,364
- **Language**: DE
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("Vyvo/Emilia-YODAS-DE")
sample = dataset['train'][0]
... | 428 | 39 | normal |
bigcode/bigcodebench-hard-solve-rate | code | 0.767 | none | 0.1447 | null | [] | 0 | 50 | normal | |
AmplifierHealth/dam-dataset | medical | 0.9021 | none | 0.0937 | null | [] | # Overview
This dataset includes audio-based model scores, clinical mental health labels, and demographic metadata for the validation and test sets used in the development of https://huggingface.co/KintsugiHealth/dam. Demographic statistics covering the training set as well are included in this model card.
The model w... | 5,581 | 27 | new_discovery |
Samarth0710/bharatanatyam-mudra-dataset | none | 0.979 | cybersecurity | 0.0091 | null | [
"bharatanatyam",
"mudra",
"hand-gestures",
"indian-classical-dance",
"computer-vision"
] | # Bharatanatyam Mudra Dataset
## Dataset Description
The Bharatanatyam Mudra Dataset contains **28,431 images** of hand gestures (mudras) from Bharatanatyam, a classical Indian dance form. The dataset was collected from 15 volunteers in a studio environment and includes both single-hand and double-hand gestures.
###... | 2,864 | 102 | normal |
pdf2dataset/e598bfbc477094a663ffe4ec95ad024c | none | 0.5052 | biology | 0.1244 | null | [] | 0 | 3 | normal | |
TAUR-dev/D-ExpTracker__FinEval_16k_Math500eval_3arg_OT_ours_1k-RL__v1 | none | 0.8282 | math | 0.0729 | null | [] | # Experiment Tracker: FinEval_16k_Math500eval_3arg_OT_ours_1k-RL
**Experiment Description:** Simple test experiment for Skill Factory workflows.
**Start Time:** 2025-11-29T13:50:26.746789
**Tracker Dataset:** [TAUR-dev/D-ExpTracker__FinEval_16k_Math500eval_3arg_OT_ours_1k-RL__v1](https://huggingface.co/datasets/TAUR... | 2,914 | 4 | normal |
kureha295/Qwen3-8B_scored_train_harmful_prompts_cot5_out5 | none | 0.7748 | code | 0.0847 | null | [] | 0 | 13 | normal | |
haydn-jones/ORD-Pretraining-v5 | none | 0.4914 | code | 0.2198 | null | [] | 0 | 32 | normal | |
deu05232/promptriever-ours-v9_2-vanilla | none | 0.4365 | biology | 0.2759 | null | [] | 0 | 4 | normal | |
thomas0829/flatten_towel_pi05 | none | 0.9302 | code | 0.0655 | 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",
"... | 4,827 | 18 | normal |
RiddhiCh/LGRM_BridgeDataV2_Teleoperated_6K | none | 0.4245 | biology | 0.1987 | null | [] | 0 | 7 | normal | |
BAAI-DataCube/robomind_benchmark1_1_release_agilex_3rgb_41_putplum | none | 0.7944 | code | 0.1861 | null | [] | # benchmark1_1_release_agilex_3rgb_41_putplum
This dataset converts the Robomain format uniformly into LeRobot V3.0.
## Dataset Statistics
本体: agilex_3rgb
末端执行器: 夹爪
任务平台显示版: 放李子part_2
total_episodes: 199
total_tasks: 1
size: 4.6G
## Dataset Structure
```
├── data
│ └── chunk-xxx
│ ├── file-xxx.parquet
├── im... | 940 | 30 | normal |
JiabinQ/eval_fork_ROTATE_6k | 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": "v2.1",
"... | 3,575 | 5 | normal |
Kainat98/CloudWhisperCustomBot_2 | none | 0.5107 | code | 0.1996 | null | [] | 0 | 4 | normal | |
Yotofu/so100_cube_opencv | none | 0.6915 | code | 0.1191 | null | [
"so100_opencv",
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). | 81 | 14 | normal |
cchoi1/kodcode-complete_1000_qwen7b_att_iter0_att10_sol5_dedup | code | 0.5267 | none | 0.3388 | null | [] | 0 | 5 | normal | |
aochongoliverli/countdown_level_6 | none | 0.5874 | code | 0.1256 | null | [] | 0 | 3 | normal | |
juni3227/so100_test03 | none | 0.9326 | code | 0.0601 | 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",
"... | 3,597 | 14 | normal |
hbXNov/numina_amc_aime_in_depth_deepseek_r1_questions | none | 0.7152 | code | 0.145 | null | [] | 0 | 28 | normal | |
wangphoebe/ActiView | none | 0.8644 | code | 0.0644 | null | [] | ## Overview
This is benchmark for paper "**ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models**" ([arxiv](https://arxiv.org/abs/2410.04659))
Please refer to this [github](https://github.com/THUNLP-MT/ActiView) repo **for detail.**
To use this dataset, please download all the files an... | 1,074 | 14 | normal |
Leonardo6/ny_cartoon | none | 0.6035 | code | 0.1024 | null | [] | 0 | 20 | normal | |
JisooSong/yori-test-dataset-20250921_201013 | none | 0.9486 | code | 0.0482 | 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",
"... | 4,757 | 17 | normal |
TheFactoryX/edition_1963_ryanmarten-OpenThoughts-1k-sample-readymade | none | 0.9887 | code | 0.0099 | null | [
"readymades",
"art",
"duchamp"
] | # edition_1963_ryanmarten-OpenThoughts-1k-sample-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[ryanmarten/OpenThoughts-1k-sample](https://huggingface.co/datasets/ryanmarten/OpenThoughts-1k-sample)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objec... | 981 | 4 | normal |
rico2512/OctoCodingBench | code | 0.9966 | cybersecurity | 0.0016 | code | [
"code",
"agent"
] | # OctoCodingBench: Instruction-Following Benchmark for Coding Agents
[English](README.md) | [中文](README_CN.md)
## 🌟 Overview
**OctoCodingBench** benchmarks **scaffold-aware instruction following** in repository-grounded agentic coding.
### Why OctoCodingBench?
Existing benchmarks (SWE-bench, etc.) focus on **tas... | 7,088 | 18 | normal |
sudosimi/so101_toaster3 | none | 0.9084 | code | 0.0786 | null | [
"so101",
"toaster"
] | 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",
"... | 3,669 | 14 | normal |
ljvmiranda921/details_msde-google_gemma-3-4b-pt-lora-4bit-msde-S1-ar_granite-4_0-1b | none | 0.9883 | code | 0.0082 | 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... | 6,783 | 21 | normal |
Mohit1Kulkarni/Graph_Analysis_Dataset | none | 0.3547 | climate | 0.3012 | null | [] | 0 | 4 | normal | |
alimoradkhany/testdata | none | 0.5158 | chemistry | 0.1605 | null | [] | 0 | 3 | normal | |
open-llm-leaderboard-old/details_nisten__bigdoc-c34b-instruct-tf32 | none | 0.9596 | code | 0.0313 | null | [] | # Dataset Card for Evaluation run of nisten/bigdoc-c34b-instruct-tf32
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [nisten/bigdoc-c34b-instruct-tf32](https://huggingface.co/nisten/bigdoc-c34b-instruct-tf32) on the [Open LLM Leaderboard](https://hugg... | 19,272 | 5 | normal |
MUGUHU/solarirradiancedataset | climate | 0.9867 | none | 0.0082 | climate | [
"climate"
] | # Estimating Solar Irradiance with Image Regression
- **Homepage:** [Sage Continuum](https://sagecontinuum.org/)
- **Author:** Alex Shen, Northwestern University
- **Mentors:** Bhupendra Raut, Seongha Park
- **Repository:** [GitHub Repository](https://github.com/waggle-sensor/summer2023/tree/main/Shen)
# Goal and Impo... | 3,994 | 15 | normal |
ibm-research/ToolRM-train-data | code | 0.9635 | none | 0.035 | null | [
"function-calling",
"LLM Agent",
"reward-modeling"
] | <h1 align="center">ToolRM Training Dataset</h1>
<div align="center">
<a width="150" style="display: inline-block" href="https://arxiv.org/abs/2509.11963"><img alt="Static Badge" src="https://img.shields.io/badge/arxiv-2509.11963-red?logo=arxiv"></a>
<a width="150" style="display: inline-block" href="https://huggingfac... | 5,545 | 119 | new_discovery |
OpenFinAL/FINGPT_QA_V4-split-dataset | none | 0.5893 | code | 0.1105 | null | [] | 0 | 4 | normal |
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