datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mytown-local-gov-meetings
MyTown — open dataset of US & Canadian local-government meetings
The documents themselves, not just the metadata. Most civic datasets publish meeting
titles, dates and links. This one publishes 2,109,683 full text extractions of
the primary documents — the actual agendas and minutes, pulled out of the PDFs — alongside
11,949,495 per-member roll-call votes and 61,661,080 campaign-finance
transactions, all joinable on the same keys.
That combination is the point: you can go from… See the full description on the dataset page: https://huggingface.co/datasets/jazzypajamas/mytown-local-gov-meetings.audioverse_for_annotation_soundlyjazz-music-archivesjimsky-radio-jazz-lab
Jimsky Radio Jazz Lab
One original character theme and two historical jazz melody-conditioned cover tests, generated on an RTX 4070 using the supplied ComfyUI workflows. Three audio tests and all three planned artwork pieces succeeded (artwork generated via Comfy Cloud with the supplied workflow nodes; the desktop variant remains blocked by desktop API-node authorization).
Listen
Raw Raw on the Radio — 120.00s · MP3 · FLAC
Livery Stable Blues — glitch-hop cover… See the full description on the dataset page: https://huggingface.co/datasets/TheMindExpansionNetwork/jimsky-radio-jazz-lab.Egoinstructor_downstream_metadata
📙 Overview
This repo contains the metafiles to evaluate the performance of EgoInstructor, including
Epic-Kitchen multi-instance retrieval
YouCook videoclip-text retrieval
Charadesego egovideo-exovideo retrieval
EgoLearn egovideo-exovideo retrieval
Ego4d Summarization multiple choice question
YouCook video-text retrieval
The following metafiles are used for retrieval-augmented egocentric video captioning, including
E4DOL_crossview_train_instructions.json… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/Egoinstructor_downstream_metadata.JoyceCacheoasst1-en-hun-gemini
Open assistant 1 dataset hungarian translation (english subset)
This dataset contains hungarian translations for the oasst1 dataset's english subset. The translations were done via gemini pro and the model was instructed to keep stlye, meaning and english entites as they are. I think this produced a higher quality translation than google translate, but even this version is far from perfect.
The exact code used for creating the dataset can be found here.
license:… See the full description on the dataset page: https://huggingface.co/datasets/jazzysnake01/oasst1-en-hun-gemini.fEgoHODgpt4all-jazzy-chatml
Dataset Card for "gpt4all-jazzy-chatml"
More Information needed
ego4d_videomae_L14_feature_fps8
📙 Overview
Ego4d video features extracted by VideoMAE_L14 at 8 fps.
It contains 9645 files, each file (e.g. fffbaeef-577f-45f0-baa9-f10cabf62dfb.pth.tar) is a TxD feature vector, where T refers to the length of the video and D is 768.
🏋️ How-To-Use
Please refer to code EgoInstructor for details.
🎓 Citation
@article{xu2024retrieval,
title={Retrieval-augmented egocentric video captioning},
author={Xu, Jilan and Huang, Yifei and Hou, Junlin and Chen, Guo… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/ego4d_videomae_L14_feature_fps8.quizgen-chat-mdSchaferEveResearchyoucook2_internvideo_MM_L14_features_fps8
📙 Overview
YouCook2 video features extracted by InternVideo_MM_L14 at 8 fps. It is used for evaluating the video-text retrieval ability of EgoInstructor.
Each file (e.g. 10dZTHlkb8w.pth.tar) is a TxD feature vector, where T refers to the length of the video and D is 768.
🏋️ How-To-Use
Please refer to code EgoInstructor for details.
🎓 Citation
@article{xu2024retrieval,
title={Retrieval-augmented egocentric video captioning},
author={Xu, Jilan and Huang… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/youcook2_internvideo_MM_L14_features_fps8.symbolic-jazz-standards
Symbolic Jazz Standards
A symbolic-domain music dataset of jazz standards, transcribed stem by stem from the audio domain into the symbolic domain. The dataset contains the equivalent of 10,000 minutes of audio from ~200 public-domain well-known songs.
Methodology
To create this dataset, recordings of public-domain jazz standards were downloaded and separated into their component stems using the venerable Demucs source separation library in 4-stem mode. The resulting… See the full description on the dataset page: https://huggingface.co/datasets/jspr/symbolic-jazz-standards.HowTo100M_llama3_refined_caption
📙 Overview
The metadata for HowTo100M. The original ASR is refined by LLAMA-3 language model.
Each sample represents a short video clip, which consists of
vid: the initial video id.
uid: a given unique id to index the clip.
start_second: the timestamp of the narration.
end_second: the end timestamp of the narration (which is simply set to start + 1).
text: the original ASR transcript.
noun: a list containing the index of nouns in the noun vocabulary.
verb: a list containing the… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/HowTo100M_llama3_refined_caption.ego4d_train_pair_howto100m
📙 Overview
The metadata for Ego4d training set, with paired howto100m video clips. The ego-exo pair is constructed by choosing the ones with shared nouns/verbs.
Each sample represents a short video clip, which consists of
vid: the initial video id.
start_second: the start timestamp of the narration.
end_second: the end timestamp of the narration.
text: the original narration.
noun: a list containing the index of nouns in the Ego4d noun vocabulary.
verb: a list containing the… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/ego4d_train_pair_howto100m.egolearn_videomae_internvideo_features
📙 Overview
Egolearn video features.
egocentric videos are extracted by VideoMAE_L14 at 8 fps.
exocentric videos are extracted by InternVideo_MM_L14 at 8 fps.
They are used for evaluating the egovideo-exovideo retrieval ability of EgoInstructor.
Each file (e.g. 2cad4224-56c4-11ee-88ee-80615f12b59e.pth.tar) is a TxD feature vector, where T refers to the length of the video and D is 768.
🏋️ How-To-Use
Please refer to code EgoInstructor for details.
🎓… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/egolearn_videomae_internvideo_features.jazz-solos
Dataset description
This dataset contains the jazz solos from the Weimar Jazz Database (https://jazzomat.hfm-weimar.de/dbformat/dboverview.html) that have been processed in various ways to
be musically rhythmically accurate to the transcription sheet music they provide. The solos have been converted into the SCAMP format with the addition of the current chord
to give context.
Format
Instruction
Arbitrary text requesting a jazz solo be created from a… See the full description on the dataset page: https://huggingface.co/datasets/FrantzesE/jazz-solos.david-datasetwan_jazz_handsThis dataset contains videos generated using Wan 2.1 T2V 14B.
tokenized-punjabi2jazz-set
Dataset Card for "edm_wavset"
More Information needed
Jazz-Blues-Music-Dataset_SFT-or-LoRA
Jazz & Blues Music Dataset (SFT / LoRA Ready)
A structured dataset covering 82 iconic Jazz and Blues songs, 21 artist
profiles, and 41 historical events, expanded into 1,219
instruction-tuning rows across 7 task types.
Designed for fine-tuning LLMs on music knowledge, cultural history, artist
biography, and domain-specific Q&A tasks.
Overview
Property
Value
Domain
Jazz & Blues Music
Total rows
1,219
Train split
1,036 (85%)
Validation split
91 (~7.5%)… See the full description on the dataset page: https://huggingface.co/datasets/ChaoticEconomist/Jazz-Blues-Music-Dataset_SFT-or-LoRA.oasst-1-hun-openaiMusicGen-JazzJAZZMUS
Optical Music Recognition of Jazz Lead Sheets
📄 Conf. materials |
🖥️ Slides |
🎶 Poster
Dataset
How to use
Check the following code:
import ast
from datasets import load_dataset
from PIL import ImageDraw
DATASET_NAME = "PRAIG/JAZZMUS"
ds = load_dataset(DATASET_NAME)
image = ds["train"][0]["image"]
# list of systems, with bounding boxes and encoding
systems = ast.literal_eval(ds["train"][0]["annotation"])["systems"]
# full page encodings
encoding… See the full description on the dataset page: https://huggingface.co/datasets/PRAIG/JAZZMUS.media-metadata-jazz-artists
TigreGotico/media-metadata-jazz-artists
Rich entity dataset scraped by metadatarr
scraper jazz_artists.
Rows: 7,941
Fields
artist_slug
name
genres
genre
country
bio
url
n_albums
Source
Generated by scrapers/jazz_artists.py. See the metadatarr repo for the full
pipeline and scraper source code.
jazz-harmony-embeddings
Jazz Harmony Embeddings — 6,900 tune vectors
One 128-dimensional vector per jazz standard, from a small transformer
trained from scratch so that tunes with related harmony — transpositions,
alternate charts, contrafacts — land close together. Produced by the
3-seed ensemble released at
eigenben/jazz-harmony-embeddings;
code and full experiment records at
github.com/eigenben/jazz-harmony-embeddings.
Files
embeddings.npz — embeddings: (6900, 128) float32… See the full description on the dataset page: https://huggingface.co/datasets/eigenben/jazz-harmony-embeddings.charadesego_videomae_L14_feature_fps8
📙 Overview
CharadesEgo video features extracted by VideoMAE_L14 at 8 fps. It is used for evaluating the egovideo-exovideo retrieval ability of EgoInstructor.
It contains 7860 files, each file (e.g. 005BUEGO.pth.tar) is a TxD feature vector, where T refers to the length of the video and D is 768.
🏋️ How-To-Use
Please refer to code EgoInstructor for details.
🎓 Citation
@article{xu2024retrieval,
title={Retrieval-augmented egocentric video captioning}… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/charadesego_videomae_L14_feature_fps8.