datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cifar100-enrichedThe CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).song-describer-datasetThis is a mirror to the example dataset "The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation" paper by Manco et al.
Project page on Github: https://github.com/mulab-mir/song-describer-dataset
Dataset on Zenodoo: https://zenodo.org/records/10072001
Explore the dataset on your local machine:
import datasets
from renumics import spotlight
ds = datasets.load_dataset('renumics/song-describer-dataset')
spotlight.show(ds)
speech_commands_enrichedThis is a set of one-second .wav audio files, each containing a single spoken
English word or background noise. These words are from a small set of commands, and are spoken by a
variety of different speakers. This data set is designed to help train simple
machine learning models. This dataset is covered in more detail at
[https://arxiv.org/abs/1804.03209](https://arxiv.org/abs/1804.03209).
Version 0.01 of the data set (configuration `"v0.01"`) was released on August 3rd 2017 and contains
64,727 audio files.
In version 0.01 thirty different words were recoded: "Yes", "No", "Up", "Down", "Left",
"Right", "On", "Off", "Stop", "Go", "Zero", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine",
"Bed", "Bird", "Cat", "Dog", "Happy", "House", "Marvin", "Sheila", "Tree", "Wow".
In version 0.02 more words were added: "Backward", "Forward", "Follow", "Learn", "Visual".
In both versions, ten of them are used as commands by convention: "Yes", "No", "Up", "Down", "Left",
"Right", "On", "Off", "Stop", "Go". Other words are considered to be auxiliary (in current implementation
it is marked by `True` value of `"is_unknown"` feature). Their function is to teach a model to distinguish core words
from unrecognized ones.
This version is not yet supported.
The `_silence_` class contains a set of longer audio clips that are either recordings or
a mathematical simulation of noise.speech_commands_enrichment_only
Dataset Card for SpeechCommands
Dataset Summary
📊 Data-centric AI principles have become increasingly important for real-world use cases.At Renumics we believe that classical benchmark datasets and competitions should be extended to reflect this development.
🔍 This is why we are publishing benchmark datasets with application-specific enrichments (e.g. embeddings, baseline results, uncertainties, label error scores). We hope this helps the ML community in the… See the full description on the dataset page: https://huggingface.co/datasets/renumics/speech_commands_enrichment_only.esc50
Dataset Card for "esc50"
This is a mirror for the ESC-50 dataset. Original sources:
https://github.com/karolpiczak/ESC-50
K. J. Piczak. ESC: Dataset for Environmental Sound Classification. Proceedings of the 23rd Annual ACM Conference on Multimedia, Brisbane, Australia, 2015.
[DOI: http://dx.doi.org/10.1145/2733373.2806390]
The dataset is available under the terms of the Creative Commons Attribution Non-Commercial license.
Exploring the dataset
You can visualize the… See the full description on the dataset page: https://huggingface.co/datasets/renumics/esc50.industrial-asset-level-electrical-energy-dataset
Open Energy Dataset — Star Schema
1. Overview
This star schema models the Gold-layer 15-minute energy aggregates from an industrial manufacturing facility in Ireland. The source dataset covers 43 monitored assets over ~12 months (2024-12-31 to 2025-12-31), with 1,039,873 ALL-phase windows totalling 2.96 GWh of measured electrical energy.
The facility employs ~150 personnel under continuous production. Monitored loads include hydraulic presses, air compressors… See the full description on the dataset page: https://huggingface.co/datasets/renumics/industrial-asset-level-electrical-energy-dataset.f1_dataset
Dataset Card for "f1_dataset"
This dataset includes race telemetry data from the Formula1 Montreail 2023 GP. It was obtained from the Ergast API using the fastf1 library.
We built an interactive demo for this dataset on Hugging Face spaces.
You can explore the dataset on your machine with Spotlight:
pip install renumics-spotlight
import datasets
from renumics import spotlight
ds = datasets.load_dataset('renumics/f1_dataset', split='train')
dtypes = {"DistanceToDriverAhead":… See the full description on the dataset page: https://huggingface.co/datasets/renumics/f1_dataset.dcase24_task10_loc1
DCASE 2024 Challenge Task 10 Development Dataset: Acoustic-based Traffic Monitoring - Location 1 subset
Citation
Bondi, L., Ghaffarzadegan, S., Damiano, S., Kumar, A., Wu, H.-H., Lin, W.-C., Das, S., Horst, H.-G., & Waterschoot, T. van . (2024). DCASE 2024 Challenge Task 10 Development Dataset: Acoustic-based Traffic Monitoring [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10700792
License
Creative Commons Attribution-NonCommercial-ShareAlike 4.0… See the full description on the dataset page: https://huggingface.co/datasets/renumics/dcase24_task10_loc1.beans-outlier
Dataset Card for "beans-outlier"
📚 This dataset is an enhancved version of the ibean project of the AIR lab.
The workflow is described in the medium article: Changes of Embeddings during Fine-Tuning of Transformers.
Explore the Dataset
The open source data curation tool Renumics Spotlight allows you to explorer this dataset. You can find a Hugging Face Space running Spotlight with this dataset here: https://huggingface.co/spaces/renumics/beans-outlier
Or you can… See the full description on the dataset page: https://huggingface.co/datasets/renumics/beans-outlier.f1_dataset_mcloome_demoThis is a mirror to the example dataset for the "CLOOME: a new search engine unlocks bioimaging databases for queries with chemical structures" paper by Sanchez-Fernandez et al.
Paper: https://www.biorxiv.org/content/10.1101/2022.11.17.516915v1
Code: https://github.com/ml-jku/cloome
bengaliai-competition-features-embeddings
BengaliAI Competition Embeddings and Features
f1_demo_dataset
Dataset Card for "f1_demo_dataset"
More Information needed