datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gpn-star-scores
GPN-Star genome-wide scores
Genome-wide, mutation-rate-calibrated GPN-Star constraint and variant scores for
eight score sets covering human, mouse, chicken, D. melanogaster,
C. elegans, and A. thaliana. Canonical scores are available as
chromosome-sharded Parquet. Hugging Face hosts 72 BigWigs; a multi-assembly
UCSC track hub references the 64 logo/LLR views.
Overview and quick links
Resource
Link
Files
Browse all dataset files
Default Dataset… See the full description on the dataset page: https://huggingface.co/datasets/songlab/gpn-star-scores.TraitGym
🧬 TraitGym
Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human Genetics
🏆 Leaderboard: https://huggingface.co/spaces/songlab/TraitGym-leaderboard
⚡️ Quick start
Load a datasetfrom datasets import load_dataset
dataset = load_dataset("songlab/TraitGym", "mendelian_traits", split="test")
Example notebook to run variant effect prediction with a gLM, runs in 5 min on Google Colab: TraitGym.ipynb
🤗 Resources… See the full description on the dataset page: https://huggingface.co/datasets/songlab/TraitGym.imagenet_sketchImageNet-Sketch data set consists of 50000 images, 50 images for each of the 1000 ImageNet classes.
We construct the data set with Google Image queries "sketch of __", where __ is the standard class name.
We only search within the "black and white" color scheme. We initially query 100 images for every class,
and then manually clean the pulled images by deleting the irrelevant images and images that are for similar
but different classes. For some classes, there are less than 50 images after manually cleaning, and then we
augment the data set by flipping and rotating the images.SongFormDB
SongFormDB 🎵
[English ｜ 中文]
A Large-Scale Multilingual Music Structure Analysis Dataset for Training SongFormer 🚀
Chunbo Hao1*, Ruibin Yuan2,6*, Jixun Yao1, Qixin Deng3,6,Xinyi Bai4,6, Yanbo Wang5, Wei Xue2, Lei Xie1†
*Equal contribution †Corresponding author
1Audio, Speech and Language Processing Group (ASLP@NPU),School of Computer Science, Northwestern Polytechnical University
2Hong Kong University of Science and Technology… See the full description on the dataset page: https://huggingface.co/datasets/ASLP-lab/SongFormDB.PM4Bench
PM4Bench
Strictly parallel multilingual evaluation for Large Vision-Language Models
Overview
The paper Benchmarking and Boosting Multilingual Capabilities of LVLMs via
OCR-Centric Reinforcement Learning
introduces PM4Bench to separate language effects from dataset variation. Its
content is strictly parallel across ten languages, and its vision setting
renders textual inputs directly into images. Comparing that setting with
interleaved input identifies OCR… See the full description on the dataset page: https://huggingface.co/datasets/songjhPKU/PM4Bench.Genius-song-lyrics-cleaned
🎵 Genius Song Lyrics cleaned Dataset
Dataset Description
This dataset is originally taken from Genius Song Lyrics and it contains cleaned and normalized song lyrics for more than 5 million songs, designed for large-scale topic modeling, clustering, and semantic analysis.
The dataset was specifically preprocessed to be compatible with embedding-based models (e.g. Sentence Transformers, BERTopic) while preserving lyrical meaning and thematic content.
Repetitive structures… See the full description on the dataset page: https://huggingface.co/datasets/Dr3dre/Genius-song-lyrics-cleaned.SongEval
SongEval 🎵
A Large-Scale Benchmark Dataset for Aesthetic Evaluation of Complete Songs
📖 Overview
SongEval is the first open-source, large-scale benchmark dataset designed for aesthetic evaluation of complete songs. It provides over 2,399 songs (~140 hours) annotated by 16 expert raters across five perceptual dimensions. The dataset enables research in evaluating and improving music generation systems from a human aesthetic perspective.
🌟 Features… See the full description on the dataset page: https://huggingface.co/datasets/ASLP-lab/SongEval.visual-reasoning-benchmark-results
Visual Reasoning Benchmark Suite v3.3 · 2005 Tasks · 12 Tracks Equal Weight
本版本以用户最新上传的 visual_reasoning_benchmark_suite_v3_修改 为唯一基础版本，不回退、不覆盖用户已经重绘或修改过的既有数据。完整性比对结果：原基础包中 3283 个既有数据文件全部保持字节级不变。
在此基础上新增并整合：
Nonogram（数织）150 题：45 Easy / 60 Medium / 45 Hard；
Tangram（七巧板）150 题：45 Easy / 60 Medium / 45 Hard；
两个任务的一键生成器、统一生成入口、统一评估入口、雷达图和排行榜支持。
最终总规模：2005 题，12 个 Track。
任务与数量
Task
Count
figure_completion
394
spatial_generation
56
maze_beginner
64… See the full description on the dataset page: https://huggingface.co/datasets/songyiren/visual-reasoning-benchmark-results.onlinerpg-assetsgenius-song-lyricsldsc
S-LDSC
The dataset displayed here (test.parquet) represents the ~10M variants used for S-LDSC in hg38 coordinates (a tiny fraction we couldn't liftover are marked with pos = -1).
We include scores for the 3 GPN-Star models (mutation-rate adjusted minus entropy, higher -> more functional).
gpn-animal-promoter-datasetspotify-songspexels-image-60kv33da
Who Called? V33DA: A Physically Verified Multimodal Benchmark for Vocal Attribution in Zebra Finch Groups
Task. Given a detected zebra finch vocalization and the set of birds visible at that moment, determine which bird produced the call. Caller identity is verified physically from on-body accelerometer vibration; the accelerometer channel is withheld from benchmark models and used only by an oracle ceiling.
V33DA provides 33,625 verified vocalization events from 10 individually… See the full description on the dataset page: https://huggingface.co/datasets/songbirdini/v33da.gpn-msa-hg38-scores
GPN-MSA predictions for all possible SNPs in the human genome (~9 billion)
For more information check out our paper and repository.
Querying specific variants or genes
Install the latest tabix:In your current conda environment (might be slow):conda install -c bioconda -c conda-forge htslib=1.18
or in a new conda environment:conda create -n tabix -c bioconda -c conda-forge htslib=1.18
conda activate tabix
Query a specific region (e.g. BRCA1), from the remote file:… See the full description on the dataset page: https://huggingface.co/datasets/songlab/gpn-msa-hg38-scores.cc100-samplesThe cc100-samples is a subset which contains first 10,000 lines of cc100.
Languages
To load a language which isn't part of the config, all you need to do is specify the language code in the config.
You can find the valid languages in Homepage section of Dataset Description: https://data.statmt.org/cc-100/
E.g.
dataset = load_dataset("cc100-samples", lang="en")
VALID_CODES = [
"am", "ar", "as", "az", "be", "bg", "bn", "bn_rom", "br", "bs", "ca", "cs", "cy", "da", "de",
"el"… See the full description on the dataset page: https://huggingface.co/datasets/xu-song/cc100-samples.imagebedhg38_cactus447wayomim_traitgym
OMIM regulatory variants
Predictions from all models
Lerobot_libero90Libero_90_lerobotThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "panda",
"total_episodes": 3938,
"total_frames": 572249,
"total_tasks": 73,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:3938"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4"… See the full description on the dataset page: https://huggingface.co/datasets/SongMugeon/Libero_90_lerobot.ScannedRxn
ScannedRxn
Dataset overview
ScannedRxn is a carefully curated, test-only benchmark for chemical reaction diagram parsing in historical scientific archives. It was introduced in Molecular Identifier Visual Prompt and Verifiable Reinforcement Learning for Chemical Reaction Diagram Parsing to evaluate model robustness and out-of-distribution generalization when digitizing legacy chemical knowledge.
Unlike benchmarks dominated by contemporary born-digital literature… See the full description on the dataset page: https://huggingface.co/datasets/songjhPKU/ScannedRxn.Rewardjudgegenius-song-lyricsSongFormBench
SongFormBench 🏆
[English ｜ 中文]
A High-Quality Benchmark for Music Structure Analysis
Chunbo Hao1*, Ruibin Yuan2,6*, Jixun Yao1, Qixin Deng3,6,Xinyi Bai4,6, Yanbo Wang5, Wei Xue2, Lei Xie1†
*Equal contribution †Corresponding author
1Audio, Speech and Language Processing Group (ASLP@NPU),School of Computer Science, Northwestern Polytechnical University
2Hong Kong University of Science and Technology
3Northwestern University… See the full description on the dataset page: https://huggingface.co/datasets/ASLP-lab/SongFormBench.song_datasetspotify_songsReadme
Dataset Description:
This dataset is brought from kaggle: "30000 Spotify Songs". The dataset contains both numeric and categorical variables describing songs available on Spotify. It includes musical characteristics such as danceability, energy, loudness, valence, tempo, and duration, as well as metadata like artist, album, and genre.
Research Question:
What song characteristics make a track more popular on Spotify?
Target Variable:
The target variable is track_popularity, which… See the full description on the dataset page: https://huggingface.co/datasets/uleeberber/spotify_songs.spotify-million-song-dataset
Dataset Card for Spotify Million Song Dataset
Dataset Summary
This is Spotify Million Song Dataset. This dataset contains song names, artists names, link to the song and lyrics. This dataset can be used for recommending songs, classifying or clustering songs.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data… See the full description on the dataset page: https://huggingface.co/datasets/vishnupriyavr/spotify-million-song-dataset.