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 |
|---|---|---|---|---|---|---|---|---|---|---|
loafeihong/Medicalchat100k | none | 0.4741 | code | 0.0997 | null | [] | 0 | 2 | normal | |
n0kovo/lagenda | none | 0.4706 | biology | 0.1251 | null | [] | 0 | 124 | normal | |
phospho-app/cube_box_dataset_kos_bboxes | none | 0.9294 | code | 0.0525 | null | [
"phosphobot",
"so100",
"phospho-dk"
] | # cube_box_dataset_kos
**This dataset was generated using a [phospho starter pack](https://robots.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 and RLDS. | 308 | 28 | normal |
dgambettaphd/D_gen6_run1_llama2-7b_wiki_doc1000_real96_synt32 | none | 0.8904 | code | 0.0514 | null | [] | 0 | 4 | normal | |
windfromthenorth/epsilon-forward-wm-subset | climate | 0.4314 | none | 0.328 | null | [] | 0 | 6 | boundary | |
diegi97/ragent_data_sources | none | 0.7583 | biology | 0.1632 | null | [] | # ragent_data_sources
This dataset aggregates multiple text corpora used as sources for QA generation.
Each split corresponds to a single upstream source, normalized to a common schema with `id`, `title`, and `text`.
## Data Sources
The dataset includes the following sources:
- common_pile_peps (Python En... | 1,882 | 25 | normal |
stephanedonna/english_kalata | none | 0.5297 | chemistry | 0.1551 | null | [] | 0 | 4 | normal | |
Kyleyee/imdb_data_for_dr_test_2sample | none | 0.6493 | code | 0.0847 | null | [] | 0 | 5 | normal | |
zhengod/vla-grab-dataset-v1-6 | none | 0.9456 | code | 0.0492 | 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 | 5 | normal |
satyapratheek/dostoyevsky_chunks | none | 0.9889 | medical | 0.0031 | null | [
"literature",
"dostoyevsky",
"russian-literature",
"author-style",
"causal-lm",
"fine-tuning"
] | # Dostoyevsky Chunks Dataset
This dataset contains preprocessed text chunks from four major works by Fyodor Dostoyevsky, prepared for fine-tuning language models on the author's distinctive writing style.
## Dataset Description
### Dataset Summary
A curated collection of text segments extracted from public domain E... | 5,778 | 6 | normal |
ferrazzipietro/IK_llama3.1-8b_ncbi_32_64_0.05 | biology | 0.931 | none | 0.044 | null | [] | 0 | 4 | new_discovery | |
MildredN/deepbrainz-blind-spots | math | 0.6333 | none | 0.3512 | null | [] | # Blind Spots of DeepBrainz-R1-0.6B
This dataset captures **blind spots** of the **DeepBrainz-R1-0.6B** model: [Model Link](https://huggingface.co/DeepBrainz/DeepBrainz-R1-0.6B).
I generated 10 diverse prompts to test the model’s responses against expected answers. The prompts cover **factual knowledge, math, languag... | 3,333 | 17 | normal |
juliadollis/machismo_qwen32b_1 | none | 0.5016 | biology | 0.1775 | null | [] | 0 | 4 | normal | |
nduque/eval_robustness_e8_5_no3_260k | none | 0.9094 | code | 0.086 | null | [
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.1",
"... | 4,064 | 25 | normal |
renjiepi/datapoints_round1_dpsk_security_shard2_daytona_n50k1 | cybersecurity | 0.4221 | none | 0.3423 | null | [] | 0 | 5 | boundary | |
mteb/JinaVDRDocQAGovReportRetrieval | none | 0.8216 | legal | 0.067 | null | [
"mteb",
"text",
"image"
] | <!-- 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... | 6,439 | 5 | normal |
mytri-ss/my_gh_data_f | none | 0.7014 | climate | 0.0991 | null | [] | 0 | 4 | normal | |
hivamoh/cs217-rlhf-dataset | none | 0.7223 | code | 0.1596 | null | [
"rlhf",
"preference-learning",
"human-feedback",
"alignment",
"stanford-cs217",
"anthropic",
"hh-rlhf"
] | # CS217 Fixed HH-RLHF Dataset
**Fixed subset of Anthropic's HH-RLHF dataset for reproducible RLHF experiments**
Created for Stanford CS217: Hardware Accelerators for Machine Learning - Final Project
🔗 **GitHub Repository**: [CS217-Final-Project](https://github.com/HivaMohammadzadeh1/CS217-Final-Project)
## Dataset... | 7,071 | 90 | normal |
Instinct-AI/Xerxes-Instruct-700K | none | 0.7765 | math | 0.1167 | null | [
"code",
"chemistry",
"medical",
"croissant"
] | # Dataset Card for "Xerxes-Instruct-700K"
## Description
Xerxes, named after a Persian King renowned for his wisdom and strategic prowess, is an amalgamation of four distinct datasets. This datase... | 2,250 | 18 | normal |
open-paws/animal-alignment-feedback | none | 0.88 | medical | 0.0431 | null | [
"animal-liberation",
"animal-advocacy",
"open-paws",
"ethics",
"alignment",
"feedback"
] | # Open Paws Animal Alignment Feedback
🐾 **Human feedback and preference data for aligning AI with animal advocacy values**
## Overview
This dataset is part of the Open Paws initiative to develop AI training data aligned with animal liberation and advocacy principles. Created to train AI systems that understand and ... | 2,280 | 9 | normal |
mteb/EstonianValenceClassification | none | 0.9832 | code | 0.0071 | 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... | 6,353 | 62 | normal |
kingsleykim/openthoughts_rollouts_labelled_qwen7b_filtered | none | 0.8325 | code | 0.0652 | null | [] | 0 | 5 | normal | |
1231czx/ver2_rebuttal_eaf_rm_bon64_005 | none | 0.5703 | biology | 0.1465 | null | [] | 0 | 4 | normal | |
mzio/aprm-sft_genthinkact-ENtw_cooking_game-GEaprm_qwen3_ap-SE42-REfsc4-ap1_best-b100 | none | 0.7061 | code | 0.2185 | null | [] | 0 | 9 | normal | |
tmpmodelsave/dpo_llama_type1_gsm8k_8ktype4_250tmp10 | none | 0.6662 | code | 0.2336 | null | [] | 0 | 5 | normal | |
ystemsrx/Erotic_Literature_Collection | none | 0.5053 | code | 0.1947 | null | [
"porn",
"Pre-training",
"Fine-tuning",
"Explicit Content",
"Chinese",
"Erotic Literature"
] | [English](README.en.md)
# 中文色情文学数据集合集
## 概述
本仓库包含了51个中文色情文学数据集。每个数据集由短篇色情小说、个人色情经验及其他形式的色情内容组成。数据集的格式为JSON，每个文件包含一个对象数组，每个对象代表一篇文档：
```json
[
{"text": "document"},
{"text": "document"}
]
```
这些数据集可用于语言模型的预训练，经过适当调整后也可用于模型的微调。
## 数据集格式
- **文件格式：** JSON
- **内容：** 短篇色情小说、个人色情经验及其他色情内容
- **结构：**
- 每个文件包含一个对象数组... | 790 | 562 | normal |
facaiwawa/HUT290 | none | 0.8691 | biology | 0.0535 | null | [] | ## Introduction
this is a high quality underwater tracking dataset that is manually annotated with 139 k frames. It provides 90 test sets rich in challenge properties and 200 training sets of diverse kinds.
## Paper Link
https://ieeexplore.ieee.org/document/10892342
## Github Link
https://github.com/faicaiwawa/PUTra... | 322 | 171 | normal |
ukav/generated_gads_synthetic11 | none | 0.8239 | code | 0.0956 | 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 generated_gads_synthetic11
This dataset has bee... | 1,838 | 4 | normal |
extralit-dev/test_import_dataset_from_hub_with_classlabel_5925ab74-6105-42e1-b37e-bc71d62a66c5 | none | 0.7241 | code | 0.0795 | null | [] | 0 | 5 | normal | |
sociallifethree/sise-oyun-parki-kuf-ve-curume-onlemleri | cybersecurity | 0.8476 | legal | 0.0514 | null | [] | Şişme oyun parkları, yağmurlu havalarda su birikintisi oluştuğunda zamanla küflenme ve çürüme riskleri ile karşı karşıya kalabilmektedir. Bu durumu önlemek amacıyla firmamız, yağışlı günlerde şişme oyun parklarının çadır ile birlikte kiralanmasını önermekte ve sağlamaktadır. Tüm ürünlerimiz düzenli olarak temizlenmekte... | 728 | 5 | new_discovery |
ClarusC64/clinical-5node-airway-buf-lag-cpl-anesthesia-airway-compromise-v0.1 | none | 0.687 | code | 0.1122 | null | [] | import csv
import json
import sys
from typing import Dict, List
TARGET_NAME = "cascade_state"
LABEL_COL = f"label_{TARGET_NAME}"
PRED_COL_CANDIDATES = ["prediction", "pred", "y_pred", "model_pred"]
def _to_int(x: str) -> int:
x = (x or "").strip()
if x == "":
raise ValueError("Empty value")
v = fl... | 2,497 | 748 | normal |
SINTON-IA/red_flag_processed | none | 0.7347 | chemistry | 0.0694 | null | [] | 0 | 13 | normal | |
wooaeng/youtube_comment_sentiment_dataset_preprocessing | none | 0.7728 | code | 0.0827 | null | [] | 0 | 4 | normal | |
electricsheepafrica/nigerian_agriculture_farm_demographics | climate | 0.6849 | biology | 0.2336 | null | [
"nigeria",
"agriculture",
"food-systems",
"farm-management-and-mechanization"
] | # Nigeria Agriculture – Farm Demographics
## Dataset Description
Synthetic Farm Management & Mechanization data for Nigeria agriculture sector.
**Category**: Farm Management & Mechanization
**Rows**: 100,000
**Format**: CSV, Parquet
**License**: MIT
**Synthetic**: Yes (generated using reference data from FAO... | 3,943 | 23 | normal |
Hkang/summarize_sft-test_lm-EleutherAI_pythia-1b_seed-42_numex-250_lr3e8_1Knew-BON_64 | none | 0.4984 | math | 0.3331 | null | [] | 0 | 5 | normal | |
jayyucippg/record-multicube-blue-1 | none | 0.9373 | code | 0.0582 | 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",
"... | 2,948 | 9 | normal |
bismarck91/esA-enA-tokenised-qwen-part6 | none | 0.6615 | code | 0.1476 | null | [] | 0 | 3 | normal | |
thailevann/Government_services_DPO | none | 0.3853 | climate | 0.1542 | null | [] | 0 | 3 | normal | |
exaFLOPs09/Isaac-Kitchen-v12359-08_1k | none | 0.9225 | code | 0.0666 | 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",
"... | 7,174 | 6 | normal |
D-NEG/NEG-split-cleaned-scope-de | none | 0.3865 | climate | 0.2849 | null | [] | 0 | 26 | normal | |
remynd/cv_mls_psfb_fs17_68 | chemistry | 0.7003 | none | 0.1858 | null | [] | Data used to reproduce all of the experiments in the paper ; https://ieeexplore.ieee.org/document/10720758/ | 107 | 81 | normal |
eoinf/metric_random_SeqUniform_L8_mix_within_rows_all_random_tokens_uniform_frac0d5_ctx256 | none | 0.852 | code | 0.0474 | null | [] | 0 | 10 | normal | |
yusufbaykaloglu/Turkish-Dialectical-Reasoning-Dataset-Sokrates-ToT | legal | 0.7652 | none | 0.1535 | legal | [
"ToT",
"legal",
"multi-persona",
"reasoning"
] | # Turkish Dialectical Reasoning Dataset (Sokrates-ToT)
The **Turkish Dialectical Reasoning Dataset (Sokrates-ToT)** is a collection structured in a **Tree-of-Thought (ToT)** format, based on a **multi-persona and dialectical reasoning framework**.
Inspired by Socrates' method of dialogue, it facilitates deep analysi... | 4,903 | 8 | normal |
lime-nlp/DeepScaleR_Difficulty | math | 0.9354 | code | 0.036 | null | [] | # Difficulty Estimation on DeepScaleR
We annotate the entire [**DeepScaleR**](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview) dataset with a **difficulty score** based on the performance of the [Qwen 2.5-MATH-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) model. This provides an adaptive signal for curr... | 2,387 | 153 | new_discovery |
fionela/fionela-dataset-9157 | none | 0.9818 | code | 0.0103 | null | [] | # fionela-dataset-9157
Processed **subset** dataset for instruction-following experiments.
## Details
- Samples: 190
- Streaming-based sampling (no full download)
- Fields: instruction / input / output
## Source
Derived from: https://huggingface.co/datasets/databricks/databricks-dolly-15k
## Notes
- Subset only (no... | 363 | 7 | normal |
Asap7772/review_eval_4shot_infinstruct1e7_winrate_gpt4o_pref_train | none | 0.9 | code | 0.0474 | null | [] | 0 | 6 | normal | |
zeynebnk/bugbench_emb | none | 0.3575 | climate | 0.142 | null | [] | 0 | 13 | normal | |
TheFactoryX/edition_2393_deepmind-code_contests-readymade | code | 0.933 | none | 0.0546 | null | [
"readymades",
"art",
"duchamp"
] | # edition_2393_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 | 17 | new_discovery |
MergeBench/instruction_val | none | 0.3993 | code | 0.1927 | null | [] | 0 | 125 | normal | |
dgambettavuw/D_gen9_run1_llama2-7b_xlsum_doc1000_real64_synt64_vuw | none | 0.6259 | code | 0.2751 | null | [] | 0 | 4 | normal | |
fruityapplebottom/EVAL_SmolVLA_PickUpDie_1 | none | 0.9437 | code | 0.0523 | 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",
"... | 4,418 | 9 | normal |
dvilasuero/meta-llama_Llama-3.1-8B-Instruct_base_mmlu-pro_20241017_010238 | none | 0.9332 | code | 0.0307 | 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 meta-llama_Llama-3.1-8B-Instruct_base_mmlu-pro_2... | 10,311 | 4 | normal |
Seanie-lee/ThinkSafe-R1-Distill-7B-ablation | none | 0.593 | code | 0.1379 | null | [] | 0 | 8 | normal | |
mlfoundations-dev/openthoughts3_math_30k | math | 0.5702 | chemistry | 0.3093 | null | [] | 0 | 5 | normal | |
SEACrowd/culturay | none | 0.9718 | code | 0.0217 | null | [
"self-supervised-pretraining"
] | CulturaY: A Large Cleaned Multilingual Dataset of 75 Languages From the team
that brought you CulutraX, we present CulturaY, another substantial multilingual
dataset of 15TB (uncompressed)/3TB (zstd-compressed) that applies the same
dataset cleaning methodology to the HPLT v1.1 dataset. Please note that HPLT
v1.2 has a... | 3,475 | 17 | normal |
mask-distilled-libri-one-sec-cv12/chunk_201 | none | 0.6963 | chemistry | 0.1101 | null | [] | 0 | 4 | normal | |
open-llm-leaderboard-old/details_Noodlz__DolphinLake-7B | none | 0.926 | code | 0.0523 | null | [] | # Dataset Card for Evaluation run of Noodlz/DolphinLake-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Noodlz/DolphinLake-7B](https://huggingface.co/Noodlz/DolphinLake-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/o... | 19,250 | 6 | normal |
edwardyeung04/eval_cat_bowl_bev_chunk200_act1_temp0p1 | none | 0.9365 | code | 0.0582 | 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 | 27 | normal |
ClarusC64/euv-stage-sync-drift-and-phase-lag-precursor-detection-v0.1 | none | 0.8689 | medical | 0.1054 | null | [
"clarusc64",
"euv",
"lithography",
"stage",
"sync",
"precursor"
] | ## Purpose
Detect early synchronization failure precursors between reticle and wafer stages.
Failure is preceded by:
phase lag drift
residual sync error growth
latency increase
timing jitter coupling
## Task
Predict:
precursor_flag
0 = stable
1 = precursor to sync failure
## Inputs
reticle_pos_erro... | 571 | 11 | normal |
nimsdaz/Combined_QA_dataset | none | 0.4364 | climate | 0.1929 | null | [] | 0 | 4 | normal | |
kurniapratiwi061/humanoid-sopir-data | none | 0.5814 | biology | 0.2412 | null | [] | 0 | 4 | normal | |
liming65288/weibo-comments-v1 | none | 0.5965 | climate | 0.1346 | null | [] | 0 | 3 | normal | |
Asap7772/omnimath-hint-v5-respgen__0_399 | none | 0.6711 | math | 0.0905 | null | [] | 0 | 6 | normal | |
Gideonah/sapher_qa_val | none | 0.5835 | climate | 0.1639 | null | [] | 0 | 3 | normal | |
bicycleman15/temp2 | none | 0.6358 | code | 0.0942 | null | [] | 0 | 8 | normal | |
mlfoundations-dev/openthoughts3_100k_python_tagged | none | 0.4677 | chemistry | 0.1842 | null | [] | 0 | 5 | normal | |
Gowtham1243/financial-articles | finance | 0.5448 | none | 0.1602 | null | [] | 0 | 5 | normal | |
kurniapratiwi061/humanoid-intern-data | none | 0.6256 | biology | 0.1618 | null | [] | 0 | 7 | normal | |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_3e9fbb77-7b9f-41dc-be55-592f90a82720 | none | 0.6732 | code | 0.1557 | null | [] | 0 | 3 | normal | |
cadene/reachy2_mobile_grasp_test3 | none | 0.6057 | code | 0.1338 | null | [] | 0 | 2 | normal | |
darmae/pick_and_place_test1 | none | 0.9151 | code | 0.0803 | 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",
"... | 3,578 | 36 | normal |
weedmo/eval_smol_2nd | none | 0.9185 | code | 0.0759 | 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",
"... | 3,721 | 9 | normal |
chansung/synth_ds_diverse | none | 0.4344 | chemistry | 0.2835 | null | [] | 0 | 4 | normal | |
raphael0202/FranceAgriMer-RNM | biology | 0.8252 | cybersecurity | 0.1188 | null | [
"price",
"food"
] | # FranceAgriMer - Réseau des nouvelles des marchés
Le RNM (Réseau des nouvelles des marchés), anciennement appelé le SNM (Services des nouvelles de marchés), est piloté au niveau national par l’établissement public FranceAgriMer.
L’objectif du RNM est de suivre le prix des produits agroalimentaires et des fleurs sur ... | 1,767 | 54 | new_discovery |
ledddev/dl_hw2_text_detector_data_v2_600 | none | 0.689 | chemistry | 0.1231 | null | [] | 0 | 86 | normal | |
KS325/eval_only-drawer_test1 | none | 0.9031 | code | 0.0899 | 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",
"... | 2,860 | 8 | normal |
nickfuryavg/mls_eng_chunk_3900000_to_3950000 | none | 0.5382 | code | 0.1583 | null | [] | 0 | 4 | normal | |
projecte-aina/mgsm_ca | math | 0.9942 | none | 0.0036 | null | [] | # Dataset Card for mgsm_ca
<!-- Provide a quick summary of the dataset. -->
mgsm_ca is a question answering dataset in Catalan that has been professionally translated from the [MGSM](https://huggingface.co/datasets/juletxara/mgsm) dataset in English.
## Dataset Details
### Dataset Description
<!-- Provide a longe... | 10,034 | 220 | new_discovery |
TutlaytAI/upscaling_noiser | none | 0.4385 | code | 0.1681 | null | [] | 0 | 57 | normal | |
Si7li/ltspice-spice-circuits-no-aug | chemistry | 0.5589 | none | 0.3304 | null | [
"spice",
"electronics",
"circuit-design",
"ltspice",
"netlist",
"asc",
"schematic"
] | # LTspice Netlist ↔ ASC Schematic Dataset
SPICE netlists paired with their corresponding LTspice `.asc` schematic files,
scraped from public GitHub repositories.
## Columns
- **netlist** (string): SPICE netlist content
- **asc** (string): Corresponding LTspice `.asc` schematic file content
## Splits
- **train**: 786... | 571 | 30 | normal |
NsuMILab/post_slr_bspeech | none | 0.4062 | chemistry | 0.1565 | null | [] | 0 | 17 | normal | |
Asap7772/arc-agi-mixed-max4096-impabs-dpo-lr1e-7-beta0.05-16samp-flat-respgen-abs-14of32 | none | 0.9364 | biology | 0.0266 | null | [] | 0 | 5 | normal | |
Shiym/ViT-FineTune | none | 0.4105 | climate | 0.1993 | null | [] | 0 | 93 | normal | |
reasoning-proj/c_dfiltered_logic_QwQ-32B_madversarial_continue_unrelated_t30 | none | 0.4819 | code | 0.1589 | null | [] | 0 | 5 | normal | |
mlnomad/imnet1k_wallaby_brush_kangaroo | none | 0.5241 | biology | 0.2429 | null | [] | 0 | 4 | normal | |
namespace-Pt/embedding-data | none | 0.7113 | code | 0.1465 | null | [] | # Embedding Models Training Data
- Files bigger than 1G are gziped. | 69 | 600 | normal |
michsethowusu/bambara-lingala_sentence-pairs | none | 0.99 | code | 0.0039 | null | [] | # Bambara-Lingala_Sentence-Pairs Dataset
This dataset contains sentence pairs for African languages along with similarity scores. It can be used for machine translation, sentence alignment, or other natural language processing tasks.
This dataset is based on the NLLBv1 dataset, published on OPUS under an open-sou... | 2,827 | 3 | normal |
DSWF/movie-dataset | none | 0.5636 | code | 0.0801 | null | [] | 0 | 4 | normal | |
Nexdata/344_People_American_English_Speech_Data_by_Mobile_Phone_Guiding | none | 0.9724 | medical | 0.0181 | null | [] | ## Description
This dataset is just a sample of 344 American English speakers' speech data(paid dataset), all of whom are American locals. 50 sentences for each speaker. The valid data is 9.7 hours. It is recorded in quiet environment. The contents cover in-car scenario, smart home and speech assistant.
For more detai... | 1,083 | 3 | normal |
arbml/AraBench_test | none | 0.9898 | legal | 0.0052 | null | [] | # Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-str... | 2,517 | 3 | normal |
Lyrasilas/eval_ep100_seedNone_circle_big_car_less_zoom_40000_circle_small | none | 0.9436 | code | 0.0521 | 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",
"... | 2,709 | 74 | normal |
braindecode/chbmit | none | 0.8532 | code | 0.0342 | null | [
"braindecode",
"eeg",
"neuroscience",
"brain-computer-interface",
"deep-learning"
] | # EEG Dataset
This dataset was created using [braindecode](https://braindecode.org), a deep
learning library for EEG/MEG/ECoG signals.
## Dataset Information
| Property | Value |
|----------|------:|
| Recordings | 683 |
| Type | Windowed (from Epochs object) |
| Channels | 17 |
| Sampling frequency | 200 Hz |
| Tot... | 2,131 | 1,943 | normal |
Homie0609/SoccerBench | none | 0.8808 | code | 0.1072 | null | [] | Hi all the soccer fans and all those who are interested in our project of **"Multi-Agent System for Comprehensive Soccer Understanding"**, here is the official source of our proposed benchmark **SoccerBench**. This benchmark is the largest and most comprehensive soccer-specific benchmark, featuring around 10K standardi... | 3,171 | 597 | normal |
teamcore/DPO_L8B_RMAB_XG_beta0.1dpo_probt_noise_flip0.3 | none | 0.7854 | code | 0.0765 | null | [] | 0 | 4 | normal | |
lmms-lab/LLaVA-Critic-GRPO-dataset | none | 0.43 | chemistry | 0.1849 | null | [] | 0 | 24 | normal | |
gentaiscool/simpleqa_verified_Spanish_25_force | none | 0.6825 | code | 0.0855 | null | [] | 0 | 4 | normal | |
connections-dev/res_gptoss20b_creative_1_reason_None_0.7_4096_Olmo-3_1-32B-Th_s300_e600 | none | 0.8296 | code | 0.1461 | null | [] | 0 | 9 | normal | |
Webopen2026/French_Legal_Translation_Compliance_Dataset | legal | 0.9951 | none | 0.0021 | legal | [
"nlp",
"llm",
"compliance",
"legal",
"dataset"
] | # High Quality French Legal & Compliance Dataset
This dataset contains high-quality labeled French business and compliance communications designed for AI training and NLP applications.
## Overview
Language: French
Domain: Legal, Compliance, Business Communication
Entries: ~10,000 labeled samples
Format: CSV
#... | 843 | 6 | normal |
mini97/gsm8k_100 | none | 0.6901 | code | 0.0701 | null | [] | 0 | 5 | normal | |
ddamianos/gpc-all-08-425000 | none | 0.5711 | biology | 0.1947 | null | [] | 0 | 5 | normal |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.