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 |
|---|---|---|---|---|---|---|---|---|---|---|
mteb/TurkishProductSentimentClassification | none | 0.9266 | cybersecurity | 0.0447 | 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... | 5,151 | 10 | normal |
ReactiveAI/Beta-Identity-SMAT | none | 0.4784 | code | 0.1943 | null | [] | 0 | 43 | normal | |
NNEngine/Gutenberg-Clean-40M | none | 0.9714 | code | 0.0228 | null | [
"text-generation",
"causal",
"training",
"transformers",
"pytorch",
"jsonl",
"segmentation",
"validation"
] | # 📚 TinyWay-Gutenberg-Clean-40M
A large-scale, high-quality English text dataset derived from Project Gutenberg, cleaned, normalized, deduplicated, and segmented into fixed-length samples for efficient language model pretraining.
This dataset is designed to support training small and medium language models such as *... | 3,862 | 8 | normal |
BAAI-DataCube/robomind_benchmark1_0_release_ur_1rgb_pick_up_long_bread | none | 0.8046 | code | 0.1712 | null | [] | # benchmark1_0_release_ur_1rgb_pick_up_long_bread
This dataset converts the Robomain format uniformly into LeRobot V3.0.
## Dataset Statistics
本体: ur_1rgb
末端执行器: 夹爪
任务平台显示版: 拿起长面包
total_episodes: 130
total_tasks: 1
size: 143.3M
## Dataset Structure
```
├── data
│ └── chunk-xxx
│ ├── file-xxx.parquet
├── imag... | 938 | 22 | normal |
colabfit/TSFF_PLOS_2022 | chemistry | 0.9858 | none | 0.0102 | null | [
"molecular dynamics",
"mlip",
"interatomic potential"
] | ### <details><summary>Cite this dataset </summary>Quinn, T. R., Patel, H. N., Koh, K. H., Haines, B. E., Norrby, P., Helquist, P., and Wiest, O. _TSFF PLOS 2022_. ColabFit, 2023. https://doi.org/10.60732/e75f2602</details>
#### This dataset has been curated and formatted for the ColabFit Exchange
#### This dataset ... | 2,243 | 6 | new_discovery |
TerminatorJ/Casp15 | none | 0.3822 | biology | 0.1755 | null | [] | 0 | 7 | normal | |
davidanugraha/JavanesePref-sample | none | 0.3726 | biology | 0.1298 | null | [] | 0 | 6 | normal | |
DCAgent2/swebench_verified_random_100_folders_rl_tp4s64_8x_detailed_20260303_013239 | none | 0.8844 | code | 0.0481 | null | [] | 0 | 13 | normal | |
JackAILab/OpenUni | none | 0.965 | cybersecurity | 0.016 | null | [
"video-generation",
"depth-estimation",
"optical-flow",
"multimodal",
"world-aware",
"skeleton-detection",
"video-understanding"
] | <div align="center">
<img src="Logo.png" alt="OpenUni Logo" width="180"/>
# OpenUni Dataset 🎬
**Large-Scale Multi-Modal Video Dataset for World-Aware Generation**
[](https://arxiv.org/abs/2512.07831)
[ Task: task1396_europa_ecdc_tm_en_de_translation
## 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 | 13 | normal |
alvations/c4p0-v1-en-zh | none | 0.6342 | chemistry | 0.0819 | null | [] | 0 | 5 | normal | |
alex4cip/klue-mrc-bge-m3 | none | 0.4895 | code | 0.1697 | null | [] | 0 | 5 | normal | |
weqweasdas/gsm8k_ep3_scaling_inferencetmp07 | none | 0.6607 | climate | 0.0883 | null | [] | 0 | 3 | normal | |
ziejhean/medmcqa-llama2-1k | none | 0.3861 | chemistry | 0.1425 | null | [] | 0 | 4 | normal | |
Joctor/bokete_oogiri_caption | none | 0.491 | biology | 0.2932 | null | [] | 0 | 25 | normal | |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_f68fa55a-d96f-4473-9fb2-9f513a64de79 | none | 0.6327 | code | 0.166 | null | [] | 0 | 3 | normal | |
nickfuryavg/mls_eng_chunk_8100000_to_8150000 | none | 0.638 | code | 0.126 | null | [] | 0 | 9 | normal | |
ceciliayl/dataset | none | 0.3733 | chemistry | 0.1292 | null | [] | 0 | 25 | normal | |
sywang/AttributeByUnlearning | none | 0.3191 | code | 0.2034 | null | [] | 0 | 27 | normal | |
DCAgent2/DCAgent2_swebench-verified-random-100-folders_laion_MiniMax-M2-freelancer-32ep993b2d18 | none | 0.4766 | code | 0.4703 | null | [] | 0 | 8 | normal | |
suzakuteam/OpenR1-Math-Filter-English | none | 0.4761 | math | 0.2564 | null | [] | 0 | 9 | normal | |
Saul08/wonders-of-world-classification | none | 0.9327 | finance | 0.0317 | null | [] | # Wonders of the World Image Classification Dataset
## Dataset Description
This dataset contains images of world landmarks and wonders for image classification tasks. The dataset includes 3,846 images across 12 classes representing iconic landmarks from around the world.
### Dataset Summary
- **Total Images**: 3,84... | 1,280 | 4 | normal |
DCAgent/taskmaster2-16ep | none | 0.4477 | code | 0.122 | null | [] | 0 | 9 | normal | |
infinite-dataset-hub/SQLQuizMaster | code | 0.9137 | none | 0.0588 | null | [
"infinite-dataset-hub"
] | # SQLQuizMaster
tags: classification, interview, questions, difficulty
_Note: This is an AI-generated dataset so its content may be inaccurate or false_
**Dataset Description:** The 'SQLQuizMaster' dataset comprises a curated collection of SQL interview questions tailored for various difficulty levels, aimed to asse... | 1,787 | 5 | new_discovery |
kothasuhas/permuted_mixture_p25_n50000_ctx16 | none | 0.549 | chemistry | 0.1789 | null | [] | 0 | 7 | normal | |
gjyotin305/Phi-3.5-mini-instruct_new_alpaca_005_hhexphi_hr_alpaca_1 | chemistry | 0.6847 | none | 0.169 | null | [] | 0 | 11 | normal | |
JiabinQ/eval_white_fork_bgd_3k | none | 0.9285 | code | 0.0671 | 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 | 4 | normal |
MathArena/usamo_2025 | math | 0.9806 | none | 0.0089 | null | [] | ### Homepage and repository
- **Homepage:** [https://matharena.ai/](https://matharena.ai/)
- **Repository:** [https://github.com/eth-sri/matharena](https://github.com/eth-sri/matharena)
### Dataset Summary
This dataset contains the questions from USAMO 2025 used for the MathArena Leaderboard
### Data Fields
Below ... | 1,906 | 306 | new_discovery |
timaeus/dsir-pile-13m-filtered-for-uspto-backgrounds | none | 0.6899 | biology | 0.0722 | null | [] | 0 | 5 | normal | |
tspersian/Persian-Dataset | none | 0.605 | climate | 0.1221 | null | [] | 0 | 3 | normal | |
pittisl/android-perfcounter-to-key-press | none | 0.5825 | code | 0.3154 | null | [] | # Android GPU Performance Counter to Key Press Dataset
## Description
This dataset comes from our mobile GPU-based eavesdropping work, [Eavesdropping user credentials via GPU side channels on smartphones](https://doi.org/10.1145/3503222.3507757), presented at the 27th ACM International Conference on Architectural Sup... | 3,255 | 5 | normal |
supergoose/flan_combined_task017_mctaco_wrong_answer_generation_frequency | none | 0.7991 | code | 0.0562 | null | [] | 0 | 5 | normal | |
PKU-Alignment/MM-SafetyBench | none | 0.3999 | cybersecurity | 0.2857 | null | [
"EconomicHarm",
"Financial_Advice",
"Fraud",
"Gov_Decision",
"HateSpeech",
"Health_Consultation",
"Illegal_Activitiy",
"Legal_Opinion",
"Malware_Generation",
"Physical_Harm",
"Political_Lobbying",
"Privacy_Violence",
"Sex"
] | **<span style="color: red;">Warning:</span>** This dataset may contain sensitive or harmful content. Users are advised to handle it with care and ensure that their use complies with relevant ethical guidelines and legal requirements.
**Usage and License Notices:** The dataset is intended and licensed for research use ... | 699 | 2,120 | normal |
althubaity/AraATE | none | 0.6529 | legal | 0.194 | null | [] | ## License
This dataset is licensed under the [Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0).
You are free to use, modify, and distribute this dataset, but **must provide proper attribution**. | 212 | 9 | normal |
0x-YuAN/navigation_official_RI-256 | none | 0.6988 | code | 0.0831 | null | [] | 0 | 4 | normal | |
Fdddhhhill/supply_chain_delivery_metrics.csv | none | 0.8811 | cybersecurity | 0.05 | null | [
"artificial-intelligence",
"industrial-ai",
"logistics-optimization",
"supply-chain-analytics",
"predictive-maintenance",
"smart-factory",
"industrial-iot",
"fleet-management"
] | # Industrial & Logistics AI Research Dataset Collection (2024 Edition)
## Overview
This repository provides a structured collection of industrial and logistics datasets
designed for artificial intelligence training, operational simulation,
and supply chain optimization research.
The datasets represent realistic indus... | 1,942 | 15 | normal |
bonnieliu2002/eval_act_navigate_to_table_20250805_1 | none | 0.9489 | code | 0.0456 | 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",
"... | 4,430 | 8 | normal |
GIL-UNAM/biblias_SER | none | 0.9385 | legal | 0.0528 | null | [] | # SpanishParaphraseCorpora
Este dataset pertenece al corpus SpanishParaphraseCorpora del Grupo de Ingeniería Lingüística de la UNAM. En este se encuentran todos los libros correspondientes a la traducción SER de la biblia.
## El orden de los libros en esta traducción es el siguiente:
- GEN
- EXD
- LEV
- NUM
- DET
- ... | 725 | 7 | normal |
EYEDOL/swahili_small_testSwahilidata_66 | none | 0.5775 | biology | 0.2385 | null | [] | 0 | 5 | normal | |
mm-bright/MM-BRIGHT | none | 0.7519 | code | 0.1994 | null | [
"multimodal-retrieval",
"rag",
"complex-reasoning",
"image-retrieval",
"stackexchange"
] | # MM-BRIGHT: A Multi-Task Multimodal Benchmark for Reasoning-Intensive Retrieval
**MM-BRIGHT** is the first **multimodal benchmark** designed for **reasoning-intensive retrieval**. Unlike existing benchmarks that primarily consist of text-based, keyword-centric queries, MM-BRIGHT targets complex real-world scenarios w... | 4,105 | 2,125 | normal |
llepa/fine-test-dataset | none | 0.5759 | chemistry | 0.1125 | null | [] | 0 | 3 | normal | |
kibeen/details_Qwen__Qwen3-Coder-30B-A3B-Instruct-FP8_private | none | 0.827 | code | 0.1677 | null | [] | # Dataset Card for Evaluation run of Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8).
The dataset is composed o... | 13,115 | 120 | normal |
Soghandi/my-deduplicated-dataset | none | 0.5576 | code | 0.1131 | null | [] | 0 | 25 | normal | |
juliadollis/trad_ai_medical_chatbot_respostaqwen2.5_7b_outroprompt | none | 0.7376 | code | 0.1134 | null | [] | 0 | 907 | normal | |
VarunKVK/code-explainer-dataset | code | 0.7812 | none | 0.1144 | null | [] | 0 | 5 | normal | |
chakra-labs/pango-sample | code | 0.8694 | none | 0.1148 | null | [
"computer-use"
] | # Pango Sample: Real-World Computer Use Agent Training Data
**Pango** represents **P**roductivity **A**pplications with **N**atural **G**UI **O**bservations and trajectories.
## Dataset Description
This dataset contains authentic computer interaction data collected from users performing real work tasks in productivi... | 7,481 | 218 | new_discovery |
MexIvanov/RAG-v1-ruen | none | 0.9089 | code | 0.0497 | code | [
"rag",
"code"
] | A version of the glaiveai/RAG-v1 dataset extended with machine translation to Russian language for multilingual retrieval-augmented generation tasks.
Released under the same license as the original dataset, provided as is with research intent (but not limited), use/read at your own risk. | 288 | 5 | tag_disagree |
jackeet/RuBirdNames | none | 0.6001 | biology | 0.3646 | null | [
"handwriting-recognition",
"htr",
"russian",
"birds"
] | Examples of 583 handwritten words (not counting words produced by mistake) that make up the common names of 701 bird species found in Russia. Original bird names were produced using eBird's API.
The dataset contains examples of handprinted and cursive scripts as well as various backgrounds (plain white, grid-ruled pap... | 1,070 | 119 | normal |
lemonhat/SEvolve1_re_30k_tag5_processed | none | 0.5868 | code | 0.108 | null | [] | 0 | 6 | normal | |
aipib/mlx-vlm-jp-01 | none | 0.2985 | chemistry | 0.2676 | null | [] | 0 | 3 | normal | |
zjhhhh/stage2_mean_min_expand_ver2_tokenized_gap_0.22_logprob | none | 0.7347 | climate | 0.1272 | null | [] | 0 | 5 | normal | |
sdananya/wiki_data_with_label_chunk_56 | none | 0.5786 | climate | 0.0983 | null | [] | 0 | 5 | normal | |
valuesimplex-ai-lab/FIR-Bench-Sin-Doc-FinQA | chemistry | 0.5206 | none | 0.2018 | null | [] | 0 | 14 | normal | |
VGraf/generation_multi_1746754928 | none | 0.8707 | code | 0.1216 | 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': 149500,
'dataset_mixer_list': ['VGraf/no_safety_tulu_pref', '160000'],
'dataset_shuffle_seed': 42... | 2,342 | 3 | normal |
distilled-false-pos-one-sec-cv12/chunk_134 | none | 0.7738 | biology | 0.0903 | null | [] | 0 | 3 | normal | |
Birr001/vol_limited_z_0.075_spectra | chemistry | 0.511 | climate | 0.2717 | null | [] | 0 | 29 | normal | |
amphora/Open-R1-Mulitlingual-SFT | none | 0.8977 | code | 0.0747 | null | [] | # Open-R1-Mulitlingual-SFT
## Overview
**Open-R1-Mulitlingual-SFT** is a curated dataset designed for multilingual supervised fine-tuning.
The source data comprises multiple datasets containing original prompts and responses, which were subsequently translated into 14 languages using GPT-4o.
## Sources
The dataset is... | 1,172 | 41 | normal |
man-ml/my_audio_syn-Divya-Chandni | none | 0.6871 | code | 0.0908 | null | [] | 0 | 4 | normal | |
sjleslie/MGEN_5K_fakeQs_context_len_1__bs007 | none | 0.5207 | code | 0.3174 | null | [] | 0 | 6 | normal | |
AdaMLLab/AraMix-HQ | none | 0.9288 | code | 0.0624 | null | [] | <img src="https://huggingface.co/datasets/AdaMLLab/AraMix-HQ/resolve/main/finetasks_arabic_hq_comparison.png" width="900" alt="Finetasks benchmark scores comparing AraMix-HQ against AraMix-Matched and FineWeb2-HQ.">
<p align="center">
<a href="https://huggingface.co/collections/AdaMLLab/mixminmatch">
<img src="h... | 2,057 | 344 | normal |
pt-eval/eval_enllama-49999_5shot_3exp | none | 0.7594 | code | 0.0864 | null | [] | 0 | 5 | normal | |
minhyeonoh/_feedback_assistant_harmlesshelpfulhumor_271_1.5_0_5 | none | 0.8307 | code | 0.0693 | null | [] | 0 | 4 | normal | |
IeBoytsov/wayfair_product_summaries | none | 0.701 | finance | 0.1828 | null | [] | # Wayfair Product Summaries Dataset
This dataset contains product-level summaries based on customer reviews from **wayfair.com**.
It accompanies the paper *End-to-End Aspect-Guided Review Summarization at Scale*, accepted to the **EMNLP 2025 Industry Track**.
To perform product-level summarization, you can join each... | 1,091 | 11 | normal |
ashutosh01/TajMahalSample | none | 0.3938 | climate | 0.1193 | null | [] | 0 | 3 | normal | |
kkahadze/bryn-hauk-zemo-alvani-fieldwork-data | none | 0.8185 | code | 0.0635 | null | [] | 0 | 4 | normal | |
Sraghvi/working-detailed-stats | none | 0.4113 | climate | 0.1429 | null | [] | 0 | 5 | normal | |
iAmHieu2012/vietnamese-ocr-dataset-aggregated | none | 0.7275 | biology | 0.0871 | null | [] | 0 | 16 | normal | |
abotkin67/pusht_dataset | none | 0.8433 | code | 0.1453 | null | [
"pusht",
"simulation",
"imitation-learning"
] | 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"... | 3,064 | 5 | normal |
simonlesaumon/dataset-tts-francais | none | 0.9652 | code | 0.0161 | null | [] | # Dataset Card for "dataset-tts-francais"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 174 | 3 | normal |
pgurazada1/summarization-demo-logs | finance | 0.3793 | none | 0.3121 | null | [] | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [M... | 4,129 | 2 | boundary |
bukoi/zetabot_driving_04 | none | 0.96 | code | 0.0282 | 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",
"... | 12,003 | 5 | normal |
BAAI-DataCube/AgiBotWorld-Beta_G1_task_676_Unplug_the_charger | none | 0.9249 | code | 0.0606 | null | [] | # agibot_task_676
This dataset converts the AgiBot format uniformly into LeRobot V3.0.
## Dataset Statistics
robot_name: G1
end_effector: 夹爪
task: 拔下充电器
total_episodes: 145
total_tasks: 1
size: 5.8G
## Dataset Structure
```
├── data
│ └── chunk-xxx
│ ├── file-xxx.parquet
├── meta
│ ├── episodes
│ │ └──... | 1,610 | 17 | normal |
OlehT/libr_ai_ba4e70cb-1725-45c7-8443-4b0cabfb093c | none | 0.6652 | biology | 0.0881 | null | [] | 0 | 4 | normal | |
ruanafan/evo-rl-data-pnp2 | none | 0.9387 | code | 0.0527 | 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",
"... | 4,644 | 0 | normal |
INSAIT-Institute/mmlu_lt | none | 0.3181 | chemistry | 0.2726 | null | [] | 0 | 37 | normal | |
Politics/hungary-mszp-dk-finetune | legal | 0.6194 | none | 0.28 | null | [] | Language: Hungarian.
Finetuning dataset for detecting delegimitizing language towards Hungarian political parties MSZP and DK.
Sentence-level dataset. Sentences extracted from news articles and filtered down to include MSZP and DK mentions through party abbrevations and leader surnames during their tenure.
Senten... | 3,804 | 3 | normal |
TAUR-dev/multitask_intermediate_cd4_reflections5_formats-C_full | none | 0.8103 | code | 0.0714 | null | [] | 0 | 4 | normal | |
extralit-dev/test_import_dataset_from_hub_with_classlabel_446708e3-97d3-4fc0-8a00-293ef78761c6 | none | 0.6289 | code | 0.0867 | null | [] | 0 | 4 | normal | |
TAUR-dev/small_final_ans_only_improvement_ds_checkpoint | none | 0.8384 | code | 0.0843 | null | [] | 0 | 4 | normal | |
sparsh35/filtered_lm_arena | none | 0.4022 | climate | 0.1817 | null | [] | 0 | 76 | normal | |
electricsheepafrica/Density-Of-Physicians-Per-10-000-Population-for-African-Countries | none | 0.8928 | medical | 0.039 | null | [] | # Density of physicians (per 10 000 population) for African Countries
## Dataset Description
This dataset contains 'Density of physicians (per 10 000 population)' data for all 54 African countries, sourced from the World Health Organization (WHO). The data is structured with years as rows and countries as columns, fa... | 807 | 9 | normal |
ceva-automation-sg/example_dataset | none | 0.7667 | code | 0.2109 | null | [
"phosphobot",
"so100",
"phospho-dk"
] | # example_dataset
**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 ... | 374 | 7 | normal |
zjhhhh/qwen3b_488_shard_00025_sel4_cur4_base4 | none | 0.4484 | chemistry | 0.2551 | null | [] | 0 | 5 | normal | |
FrancophonIA/Glossaire_agence_canadienne_evaluation_environnementale | none | 0.8114 | chemistry | 0.0372 | null | [] | > [!NOTE]
> Dataset origin: https://publications.gc.ca/site/eng/9.688134/publication.html | 89 | 5 | normal |
asafd60/gemini-approved | none | 0.4934 | code | 0.1049 | null | [] | 0 | 13 | normal | |
dgambettaphd/D_llm3_gen0_run0_WXS_doc1000_synt64_MPP | none | 0.6209 | code | 0.2514 | null | [] | 0 | 6 | normal | |
connections-dev/res_gptoss20b_original_1_reasoning_None_0.7_31000_Qwen3-30B-A3B-Thinking-2507_s300_e600 | none | 0.8694 | code | 0.101 | null | [] | 0 | 7 | normal | |
NewstaR/CoTton-MISC-SCIENCE-5k | math | 0.8009 | none | 0.1649 | null | [] | # CoTton-MISC-SCIENCE-5k
**CoTton-MISC-SCIENCE-5k** is a 5,000-example extension dataset designed to complement the original CoTton-38k. This collection addresses specific gaps in the original dataset by incorporating more diverse reasoning scenarios from the a-m-team's R1 0528 dataset.
## Differences from CoTton-38k... | 1,951 | 3 | new_discovery |
Tippawan/tiny-llama-proof-reading | none | 0.6787 | code | 0.1271 | null | [] | 0 | 4 | normal | |
tmpmodelsave/nosft_llama3_sft_math_dpo_type12_8ktype4_7ktype3_150tmp07 | none | 0.764 | code | 0.07 | null | [] | 0 | 3 | normal | |
french-open-data/registre-national-des-installations-de-production-et-de-stockage-d-electricite-sur-la-metropole | cybersecurity | 0.8782 | none | 0.0873 | null | [
"dataset_for_agent"
] | # Registre national des installations de production et de stockage d'électricité sur la Métropole de Lyon
> [!NOTE]
> Ce jeu de données Hugging Face est vide. Cette carte sert seulement à référencer le jeu de données **Registre national des installations de production et de stockage d'électricité sur la Métropole de L... | 1,405 | 9 | new_discovery |
AKCIT-Deepfake/BRSpeech-DF | none | 0.9711 | cybersecurity | 0.0087 | null | [] | # 🗣️ BRSpeech-DF: A Deep Fake Synthetic Speech Dataset for Portuguese
## 🧩 Description
**BRSpeech-DF** is the **first publicly available dataset** for **deepfake speech detection in Portuguese**, covering both **Brazilian** and **European** variants.
It contains **459,000 audio samples**, including both **real** an... | 4,135 | 489 | normal |
Nexdata/Pre-training-corpus-for-Indonesian-Malay-and-Vietnamese | none | 0.9643 | code | 0.0198 | null | [] | ## Description
This dataset comprises pre-training corpora for ASEAN languages, including 70GB of Indonesian language corpora, 70GB of Vietnamese language corpora, and 10GB of Malaysian language corpora. The corpora for each language span multiple domains such as society, culture, encyclopedias, and news. With clear fi... | 1,445 | 4 | normal |
Heatmob-Research/VITON-HD | none | 0.4032 | finance | 0.3273 | 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 | 14 | normal |
haritzpuerto/the_pile_arxiv_1k_sample | none | 0.9296 | code | 0.057 | null | [] | Sample of the arxiv partition of The Pile.
- The training set is just a random sample of 1000 documents from the 00.jsonl.zst (the first file in The Pile; it seems each jsonl.zst file is already a random sample).
- The validation and test set are the full sets.
# Statistics
## Training Set
- Mean number of tokens:... | 434 | 17 | normal |
GeekOfBohemia/llm-lingo | none | 0.5542 | biology | 0.1952 | null | [] | 0 | 3 | normal | |
Dulsara/glaive-function-calling-v2 | code | 0.766 | none | 0.2185 | null | [] | Modified version of the [glaiveai/glaive-function-calling-v2](https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2) dataset
All samples in the glaive dataset is converted into the following format for better interoperability
```json
[
{
"role":"system",
"content":"You are a helpful a... | 2,363 | 5 | normal |
sjleslie/random_prevalence_7_bins_long_17 | none | 0.6753 | climate | 0.1187 | null | [] | 0 | 5 | normal |
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