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 |
|---|---|---|---|---|---|---|---|---|---|---|
wangguan1995/DrivAer | none | 0.3755 | chemistry | 0.1152 | null | [] | 0 | 7 | normal | |
murodbek/MMLU-Lite-uz | none | 0.9255 | code | 0.0486 | null | [
"uzbek",
"mmlu"
] | # MMLU Lite uz
An Uzbek version of the [Global-MMLU-Lite](https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite) benchmark.
This dataset was automatically translated in two stages:
* Base translation using the `sayqalchi` model from ([Tilmoch platform](https://developer.tahrirchi.uz)).
* Enhancement pass u... | 2,776 | 4 | normal |
oriental-lab/rakuda-questions-turkish | none | 0.7003 | biology | 0.0583 | null | [] | 0 | 3 | normal | |
DCAgent2/dcagent2-swebench-verified-random-100-folders-penfever-nl2bash-glm-4-6-traces-34242749 | code | 0.731 | none | 0.2526 | null | [] | 0 | 10 | normal | |
Kehann/2k | none | 0.3746 | chemistry | 0.1956 | null | [] | 0 | 6 | normal | |
mikii17/syscode | finance | 0.3703 | none | 0.3211 | null | [
"system-design, interview, evaluation, feedback, alpaca-format"
] | # 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 | 5 | boundary |
Asap7772/dapo5k-offlinedata-hintgen-qwen3-4b-lr1e6-shard1 | none | 0.876 | medical | 0.0275 | null | [] | 0 | 4 | normal | |
Sophon96/record-test | none | 0.9292 | code | 0.065 | 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 | 15 | normal |
hypersunflower/ava_speech_data_log_mel_spec | none | 0.9627 | code | 0.0096 | null | [] | this dataset was created using data from nccratliri/vad-human-ava-speech
i just converted audio to log mel spectogram, as a part of my pet project
the code with processing steps can be found here: https://github.com/ertan-somundzhu/sad-model
download the processed version with:
```
from huggingface_hub import sna... | 694 | 6 | normal |
EYEDOL/swahili_small_testSwahilidata_22 | none | 0.6432 | biology | 0.143 | null | [] | 0 | 4 | normal | |
ahmedselhady/ms2_dataset_restructured | none | 0.5012 | chemistry | 0.1144 | null | [] | 0 | 5 | normal | |
zjhhhh/iter2_7b_multi_gap_0.15_scores_base_46 | none | 0.8365 | climate | 0.0518 | null | [] | 0 | 4 | normal | |
french-open-data/condition-voirie-octobre-2018-courbevoie | none | 0.9469 | cybersecurity | 0.0259 | null | [
"courbevoie",
"meteo",
"sol",
"temperature",
"dataset_for_agent"
] | # Condition voirie Octobre 2018 Courbevoie
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Condition voirie Octobre 2018 Courbevoie** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/5fd16348df0b2de6c3d48b68
## Description
Condition voi... | 564 | 15 | normal |
voice-biomarkers/openslr-32-hq-SA-languages-Afrikaans | none | 0.988 | code | 0.0071 | null | [] | # High quality TTS data for four South African languages - Afrikaans
### Source - https://openslr.org/32/
### Identifier: SLR32
Summary: Multi-speaker TTS data for four South African languages - Afrikaans
License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
About this resource:
This data set contains m... | 1,367 | 26 | normal |
french-datasets/supergoose_flan_combined_task1136_xcsr_fr_commonsense_mc_classification | none | 0.9904 | cybersecurity | 0.0029 | null | [] | Ce répertoire est vide, il a été créé pour améliorer le référencement du jeu de données [supergoose/flan_combined_task1136_xcsr_fr_commonsense_mc_classification](https://huggingface.co/datasets/supergoose/flan_combined_task1136_xcsr_fr_commonsense_mc_classification). | 267 | 4 | normal |
rweics5cs7/621235e63fb0c0e12c57fe1957191cb6 | none | 0.65 | biology | 0.1012 | null | [] | 0 | 4 | normal | |
Asap7772/deepscaler-easy-og-abstraction-verl-rl | code | 0.5169 | none | 0.2459 | null | [] | 0 | 5 | normal | |
APPFL/Illinois_load_datasets | none | 0.4278 | climate | 0.2051 | null | [] | ## Illinois building energy consumption
This repository contains two datasets of 592 Illinois buildings each, one being more heterogenous than the other. The data is sourced from the [NREL ComStock](https://comstock.nrel.gov/) model/dataset.
## Usage
**Multivariate dataset**
The file `custom_dataset.py` contains th... | 3,221 | 50 | normal |
GingerBled/M1_dataset | none | 0.5195 | code | 0.1388 | null | [] | 0 | 4 | normal | |
appier-ai-research/math_with_llama_loss | none | 0.4793 | math | 0.2123 | null | [] | 0 | 4 | normal | |
nineninesix/expresso-conversational-en-nano-codec-dataset | none | 0.9667 | cybersecurity | 0.0157 | null | [
"TTS",
"ASR"
] | # Expresso Conversational EN Nano-Codec Dataset
This dataset is built upon the [Expresso conversational dataset](https://huggingface.co/datasets/nytopop/expresso-conversational) and re-encoded using NVIDIA’s [NeMo Audio Codec](https://huggingface.co/nvidia/nemo-nano-codec-22khz-0.6kbps-12.5fps) into **nano audio token... | 1,607 | 15 | normal |
DopeorNope/math_distilled_sequence_data | none | 0.3732 | climate | 0.2332 | null | [] | 0 | 8 | normal | |
richmondsin/mmlu_hi_results | none | 0.9361 | code | 0.0584 | null | [] | # Dataset Card for Evaluation run of google/gemma-2-2b
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b)
The dataset is composed of 0 configuration(s), each one corresponding to one of the eva... | 5,862 | 4 | normal |
CleverThis/opencyc | none | 0.8553 | code | 0.117 | null | [
"rdf",
"knowledge-graph",
"semantic-web",
"triples"
] | # OpenCyc 4.0
## Dataset Description
Common-sense ontology subset from Cycorp
**Original Source:** https://github.com/asanchez75/opencyc/raw/master/opencyc-latest.owl.gz
### Dataset Summary
This dataset contains RDF triples from OpenCyc 4.0 converted to HuggingFace dataset format
for easy use in machine learning p... | 7,668 | 18 | normal |
TayTT/TSD_set | none | 0.4131 | code | 0.171 | null | [] | 0 | 4 | normal | |
Self-GRIT/PILE_Wikipedia_validation_set_insert_ret_tokens-wikipedia-dpr-k-2-OP-False | none | 0.8514 | code | 0.1131 | null | [] | 0 | 3 | normal | |
anilguven/turkish_tweet_emotion_dataset | none | 0.9564 | code | 0.0189 | null | [
"tweet",
"turkish",
"sentiment",
"emotion"
] | ## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
@INPROCEEDINGS{8946435,
author={Güven, Zekeriya Anıl and Diri, Banu and Çakaloğlu, Tolgahan},
booktitle={2019 Innovations in Intelligent Systems... | 975 | 65 | normal |
DopeorNope/lora_test_cpt_nopack_nochunk_14400_0.8 | none | 0.6219 | climate | 0.1703 | null | [] | 0 | 4 | normal | |
reasoning-proj/exp_rob_dfiltered_logic_DeepSeek-R1-Distill-Qwen-1_5B_mneutral_add_random_text_t70 | none | 0.3842 | math | 0.2912 | null | [] | 0 | 4 | normal | |
Qilex/baby_lm_aug_full_eighth_pass | none | 0.7413 | chemistry | 0.0831 | null | [] | 0 | 2 | normal | |
DCAgent/staqc-ot3-100k-traces-terminus-2 | none | 0.571 | code | 0.1805 | null | [] | 0 | 33 | normal | |
jganzabalseenka/Nota_2024-09-10T20_24hs | none | 0.4691 | finance | 0.1108 | null | [] | 0 | 4 | normal | |
mzio/aprm-finqa_reasoning-gpt5m_med-gs4-s0-r2-train | none | 0.6193 | code | 0.1872 | null | [] | # Act-PRM Rollout Dataset
## Run Metadata
- **env_config**: `finqa/reasoning_gpt5m`
- **model_config**: `oai_gpt5m_med`
- **model**: `gpt-5-mini`
- **split**: `train`
- **group_size**: `4`
- **seed**: `1`
- **num_samples**: `62`
- **num_trajectories**: `248`
- **accuracy**: `41.5%`
- **mean_reward**: `-0.169`
- **run... | 614 | 19 | normal |
zhengbang0707/REFUEL_it2_mask2_v2_30k_train | none | 0.5817 | climate | 0.1393 | null | [] | 0 | 5 | normal | |
jnlpba/jnlpba | biology | 0.5611 | none | 0.342 | null | [] | # Dataset Card for JNLPBA
## 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 Instances](#data-instances)
- ... | 3,995 | 175 | normal |
wellCh4n/miao-pattern | none | 0.3359 | climate | 0.1796 | null | [] | 0 | 5 | normal | |
chiyuanhsiao/text_merge-linear-replay_mmlu-prob | none | 0.7803 | code | 0.0662 | null | [] | 0 | 4 | normal | |
Lots-of-LoRAs/task1509_evalution_antonyms | none | 0.8941 | biology | 0.0661 | null | [] | # Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1509_evalution_antonyms
## Dataset Description
- **Homepage:** https://github.com/allenai/natural-instructions
- **Paper:** https://arxiv.org/abs/2204.07705
- **Paper:** https://arxiv.org/abs/2407.00066
- **Point of Co... | 2,302 | 59 | normal |
micsell/hebrew_kan_sentence10000 | none | 0.6013 | code | 0.1226 | null | [] | 0 | 3 | normal | |
windfromthenorth/craft-multiturn-actions-split-nothink | none | 0.7416 | climate | 0.129 | null | [] | 0 | 5 | normal | |
cijerezg/eval_push_policy_v64 | none | 0.9196 | code | 0.0764 | 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",
"... | 3,571 | 5 | normal |
flammenai/Grill-preprod-v2_chatML | none | 0.9366 | code | 0.0367 | null | [] | # Grill-v2
This dataset contains ChatML formatted conversation between a human and AI. The goal is simulating a preproduction version of flammen.ai in order to train the Mahou series of models.
## Schema
- `chatID` - index linking conversations
- `idx` - index of response in a conversation
- `prompt` - ChatML format... | 693 | 8 | normal |
teamcore/DPO_Pm3B_RMAB_TG_clean_beta0.25dpo_pro_nu0.3_bt_noise_flip_paper0.3_vs_dlm_default_cr_trajfullc | none | 0.8697 | code | 0.0701 | null | [] | 0 | 5 | normal | |
EYEDOL/AGRILLAVA-image-text13 | none | 0.2934 | biology | 0.2926 | null | [] | 0 | 13 | normal | |
selfcorrexp/llama3_non_delete_rr40k_3ep_dpo_gen_math_1 | none | 0.5002 | math | 0.2729 | null | [] | 0 | 4 | normal | |
sunitha-ravi/mistral-original-financebench | none | 0.3855 | legal | 0.2849 | null | [] | 0 | 30 | normal | |
sodabori/20251106_BoNComp_256_2 | none | 0.4262 | biology | 0.2048 | null | [] | 0 | 4 | normal | |
cchoi1/bugbench_qwen7b_sampled | code | 0.3516 | none | 0.1871 | null | [] | 0 | 9 | normal | |
neoneye/simon-arc-image-v43 | none | 0.9339 | code | 0.0548 | null | [] | # Version 1
Have dataset items that are somewhat evenly of each type. The LLM learned some of the types fine. However rotated images are causing problems.
The image sizes are between 1 and 10 pixels.
# Version 2
Here the majority of dataset items are rotated images. Since this is what my LLM is struggling with.
Smal... | 6,163 | 2 | normal |
Mithilss/PromptsCite | none | 0.3946 | math | 0.1001 | null | [] | 0 | 17 | normal | |
Shinkenn/bi-so101-green-tea-into-cup-v2 | none | 0.9533 | code | 0.043 | 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",
"... | 4,777 | 20 | normal |
propjy/Siamese-Diffusion | chemistry | 0.4522 | none | 0.234 | null | [] | The polyp images synthesized by Siamese-Diffusion have been uploaded for reproducing the results. | 97 | 4 | normal |
AlexHung29629/rreval_2 | none | 0.2886 | chemistry | 0.1782 | null | [] | 0 | 28 | normal | |
ThankShut/colab2 | none | 0.9489 | code | 0.0173 | null | [] | # Dataset Card for "colab2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 160 | 24 | normal |
zeicul/record-test-v7 | none | 0.943 | code | 0.0512 | 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",
"... | 2,945 | 6 | normal |
french-open-data/ppbe-plan-de-prevention-du-bruit-dans-lenvironnement-tarn | cybersecurity | 0.8353 | none | 0.112 | null | [
"bruits",
"donnees-ouvertes",
"geoidecarto",
"inspire",
"nuisance-bruit",
"tarn",
"zones-de-gestion-de-restriction-ou-de-reglementation-et-unites-de-declaration",
"dataset_for_agent"
] | # PPBE Plan de prévention du bruit dans l’environnement - Tarn
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **PPBE Plan de prévention du bruit dans l’environnement - Tarn** qui est disponible à l'adresse https://www.data.gouv.fr/datasets/6737838426e2b8d... | 5,698 | 10 | new_discovery |
electricsheepafrica/municipal-solid-waste-collection-coverage-for-african-countries | climate | 0.4465 | none | 0.3957 | null | [] | ---
license: apache-2.0
tags:
- africa
- sustainable-development-goals
- world-health-organization
- development
---
# Municipal solid waste collection coverage (%)
## Dataset Description
This dataset provides country-level data for the indicator **"11.6.1 Municipal solid waste collection coverage (%)"** across ... | 1,070 | 4 | boundary |
VGraf/self-talk_gpt3.5_gpt4o_prefpairs_truncated2048 | none | 0.8525 | code | 0.0881 | null | [] | 0 | 5 | normal | |
ninar12/aesthetics-wiki | none | 0.9851 | code | 0.013 | null | [
"aesthetics",
"art",
"popular"
] | # Introduction
This dataset is webscraped version of [aesthetics-wiki](https://aesthetics.fandom.com/wiki/Aesthetics_Wiki). There are 1022 aesthetics captured.
# Columns + dtype
- title: str
- description: str (raw representation, including \n because it could help in structuring data)
- keywords_spacy: str (['NOUN',... | 4,950 | 36 | normal |
dwliang/aft_after_jaft | none | 0.4184 | climate | 0.1464 | null | [] | 0 | 5 | normal | |
sshenzha/handbookv2 | none | 0.3177 | chemistry | 0.2653 | null | [] | 0 | 10 | normal | |
jz666/llama_3b-arena-labeled-10 | none | 0.3335 | chemistry | 0.2233 | null | [] | 0 | 15 | normal | |
younes9217/DoDa-Audio-spark | none | 0.7075 | code | 0.1383 | null | [] | 0 | 17 | normal | |
construmgis/geospatial | none | 0.4207 | climate | 0.1498 | code | [
"code"
] | 0 | 6 | tag_disagree | |
MaLA-LM/mala-code-reasoning-v2 | none | 0.9293 | code | 0.0605 | code | [
"code"
] | # MaLA Corpus: Massive Language Adaptation Corpus
This MaLA code and reasoning dataset (V2) is used for training EMMA-500 Llama 3(.1) Mono/Bi model series.
- 🤗[MaLA-LM/emma-500-llama3-8b-mono](https://huggingface.co/MaLA-LM/emma-500-llama3-8b-mono): CPT model trained on monolingual data mix in 500+ languages
- 🤗[... | 1,895 | 48 | tag_disagree |
ankile/nutsquare-auto-dagger-flat-v2-softmax32t1-r15 | none | 0.9608 | code | 0.0296 | 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",
"... | 5,670 | 13 | normal |
juliadollis/SEMFINET_inferencia_qwen2.5I7b | none | 0.4801 | biology | 0.1293 | null | [] | 0 | 4 | normal | |
Abd0r/anm-v0-benchmark | math | 0.5973 | none | 0.2624 | null | [
"multi-agent",
"reasoning",
"web-of-thought",
"benchmarking",
"artificial-intelligence",
"llm",
"quantized-models",
"deep-learning",
"datasets"
] | <p align="center">
<img src="https://raw.githubusercontent.com/ra2157218-boop/Artificial-Neural-Mesh-V0/main/docs/ANM-White-Logo.png" alt="ANM Logo" width="400">
</p>
<h1 align="center">ANM V0-OpenSource Benchmark Dataset</h1>
<p align="center">
<img src="https://img.shields.io/badge/Python-3.9--3.13-blue?style=f... | 10,300 | 21 | normal |
Maminirina2/EnCodecMAEEmbeddingsMeanLayersLeadVoice | none | 0.6761 | biology | 0.1225 | null | [] | 0 | 23 | normal | |
reasoning-proj/exp_rob_dfiltered_DeepSeek-R1-Distill-Qwen-1_5B_mbenign_complete_step_t70 | none | 0.4019 | math | 0.3996 | null | [] | 0 | 4 | normal | |
alanvivares/latam-spanish-ar | none | 0.6626 | biology | 0.1021 | null | [] | 0 | 6 | normal | |
zjhhhh/iter2_7b_multi_perprompt_scores_adversary_0 | none | 0.8126 | code | 0.0671 | null | [] | 0 | 3 | normal | |
abun12/abun-text-dataset-v22 | none | 0.9723 | code | 0.0184 | null | [] | This is a simple text dataset created for learning and testing purposes on Hugging Face. | 88 | 5 | normal |
zzy0123/mid_verl | none | 0.3465 | chemistry | 0.1886 | null | [] | 0 | 5 | normal | |
pchristm/conv_questions | none | 0.9855 | code | 0.0103 | null | [] | # Dataset Card for ConvQuestions
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fiel... | 6,336 | 27 | normal |
jz666/gemma2-ultrafeedback-templated-ppl-margin-5 | none | 0.6602 | chemistry | 0.0839 | null | [] | 0 | 48 | normal | |
jerome-white/leaderboard-documents-musr | none | 0.8197 | code | 0.1126 | null | [] | 0 | 17 | normal | |
YDY0427/so101_test_20250708_195723 | none | 0.9556 | code | 0.0373 | 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 |
zjhhhh/iter2_multi_scores_base_29 | none | 0.7627 | code | 0.0621 | null | [] | 0 | 3 | normal | |
DCAgent2/DCAgent2_swebench-verified-random-100-folders_Qwen_Qwen3-4B-Thinking-2507_202515046c648 | none | 0.7248 | biology | 0.1994 | null | [] | 0 | 9 | normal | |
araziziml/s1K_tokenized_operations_graph_connections | none | 0.6229 | code | 0.1613 | null | [] | 0 | 4 | normal | |
infinite-dataset-hub/SituationResponse-Data | none | 0.8877 | cybersecurity | 0.0583 | null | [
"infinite-dataset-hub"
] | # SituationResponse-Data
tags: Emergency Situations, Response Time, Predictive Modeling
_Note: This is an AI-generated dataset so its content may be inaccurate or false_
**Dataset Description:**
The 'SituationResponse-Data' CSV dataset is designed to support machine learning practitioners in developing predictive m... | 1,612 | 3 | normal |
SayantanJoker/original_data_odia_tts | none | 0.4949 | code | 0.2136 | null | [] | 0 | 5 | normal | |
jihuny/llama_shp_10k_sky_active_newton_g03_l100_soft | none | 0.9129 | code | 0.038 | null | [] | 0 | 5 | normal | |
reasoning-degeneration-dev/PA-Qwen3-4B-Thinking-2507-cd8arg-ophint-iter-64k | none | 0.7643 | code | 0.1144 | null | [
"degen_test_1_countdown",
"budget-65k",
"iterative",
"inference-engine"
] | # PA-Qwen3-4B-Thinking-2507-cd8arg-ophint-iter-64k
Countdown reasoning with iterative strategy to 65536 tokens
## Dataset Info
- **Rows**: 100
- **Columns**: 18
## Columns
| Column | Type | Description |
|--------|------|-------------|
| question | Value('string') | The countdown problem statement |
| metadata | V... | 4,423 | 8 | normal |
dogtooth/openbookqa | none | 0.5441 | code | 0.1237 | null | [] | 0 | 5 | normal | |
rookshanks/pile_uncopyrighted_1024_revised | none | 0.7186 | code | 0.1221 | null | [] | 0 | 7 | normal | |
a-r-r-o-w/flux-retrostyle-dataset-mini | none | 0.6367 | finance | 0.1587 | null | [
"image"
] | # Dataset Card for flux-retrostyle-dataset-mini
<!-- 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... | 4,376 | 6 | normal |
helper2424/koch_move_obj_static_cameras_eval2 | none | 0.6069 | code | 0.3139 | null | [
"tutorial",
"eval"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). | 81 | 5 | normal |
WhiskyNick/match_in_case | none | 0.7117 | code | 0.2313 | null | [
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). | 81 | 34 | normal |
TAUR-dev/9_8_25__countdown_3arg__sft_data_mp_reflection_ckpt_chunk_11 | none | 0.7832 | code | 0.0743 | null | [] | 0 | 3 | normal | |
ioeddk/babilong_finetuning | none | 0.3499 | code | 0.2678 | null | [] | 0 | 6 | normal | |
xDAN-Vision/phosphate_anodizing | chemistry | 0.6443 | none | 0.1368 | null | [] | 0 | 5 | normal | |
gupta-tanish/QwQ-Long-CoT-10k-subset-Llama3.1-8B-single-position-regex-perturbation | none | 0.8661 | code | 0.0727 | null | [] | 0 | 4 | normal | |
maanas-writer/bertscore-llama-3-3-70b-i-triviaqa-llama-memorization-val-c2048-t2048-1000s-agnostic | none | 0.9361 | code | 0.0553 | null | [] | 0 | 5 | normal | |
Kota0612/AgentB-mine_1_wood_log | none | 0.8254 | biology | 0.0523 | null | [
"robonet",
"AgentB",
"Mine 1 wood log"
] | # AgentB — Mine 1 wood log
Robot episode dataset uploaded via [RoboNet](https://www.robonet.com).
## Dataset Info
| Field | Value |
|-------|-------|
| Robot | `AgentB` |
| Task | `Mine 1 wood log` |
| Episodes | 1 |
| Format | LeRobot |
## Usage with LeRobot
```python
from lerobot.common.datasets.lerobot_dataset ... | 767 | 17 | normal |
Kota0612/AgentA1-mine_1_gold_ore | none | 0.716 | finance | 0.132 | null | [
"robonet",
"AgentA1",
"Mine 1 gold ore"
] | # AgentA1 — Mine 1 gold ore
Robot episode dataset uploaded via [RoboNet](https://www.robonet.com).
## Dataset Info
| Field | Value |
|-------|-------|
| Robot | `AgentA1` |
| Task | `Mine 1 gold ore` |
| Episodes | 1 |
| Format | LeRobot |
## Usage with LeRobot
```python
from lerobot.common.datasets.lerobot_datase... | 771 | 24 | normal |
afg1/aaa | biology | 0.9795 | chemistry | 0.0171 | biology | [
"biology",
"genomics",
"rna",
"non-coding-rna"
] | # RNAcentral Export
## Export Metadata
- **Query**: `(("GO:2000352") AND (entry_type:"Sequence" OR entry_type:"Gene"))`
- **Export date**: 18 February 2026 13:42:28
- **RNAcentral version**: v24
- **Number of sequences**: 6
## Description
[RNAcentral](https://rnacentral.org) is a free, public resource that offers
i... | 610 | 21 | normal |
DCAgent2/DCAgent2_terminal_bench_2_DCAgent_nl2bash-nl2bash-bugsseq_Qwen3-8B-maxEps24-1126b85dd3c | none | 0.6004 | code | 0.2266 | null | [] | 0 | 8 | normal | |
ThunderDrag/New-Zealand-Stock-Symbols-and-Metadata | finance | 0.9944 | none | 0.0036 | null | [
"finance",
"code",
"agent"
] | # New Zealand Stock Symbols & Company Metadata
This dataset contains stock symbols and basic company metadata for all listed companies in **New Zealand**.
It is updated **weekly** if new changes are there.
---
## 📊 Dataset Contents
The dataset is provided as a CSV file with the following columns:
| Column | D... | 999 | 5 | new_discovery |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.