datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mmlu-prox-eval-predictions
MMLU-ProX Multilingual Model Predictions
Raw per-sample model predictions on MMLU-ProX
across 29 languages and 25 open-weight LLMs, produced with
lm-evaluation-harness.
This dataset releases the full prediction logs (not just aggregate scores) so that
item-level responses can be re-analysed — e.g. for Item Response Theory (IRT) modelling
of multilingual benchmarks, error analysis, or per-item difficulty estimation.
Repository structure
mmlu_prox_<lang>/
└──… See the full description on the dataset page: https://huggingface.co/datasets/gililior/mmlu-prox-eval-predictions.nexar_collision_prediction
Nexar Collision Prediction Dataset
This dataset is part of the Nexar Dashcam Crash Prediction Challenge on Kaggle.
Dataset
The Nexar collision prediction dataset comprises videos from Nexar dashcams. Videos have a resolution of 1280x720 at 30 frames per second and typically have about 40 seconds of duration. The dataset contains 1500 videos where half show events where there was a collision or a collision was eminent (positive cases), and the other half shows regular… See the full description on the dataset page: https://huggingface.co/datasets/nexar-ai/nexar_collision_prediction.polymarket-predictions
THE ORACLE — Polymarket predictions
Live predictions for Polymarket markets, produced by THE ORACLE — an autonomous
agent funded by $ORACLE pump.fun creator fees. Each row is a baseline-model
forecast over live orderbook signals (momentum, microstructure, liquidity).
predictions.json / predictions.csv — 100 markets, refreshed each agent cycle.
Columns: question, category, market_prob, oracle_prob, edge, confidence, signal,
model, backtest_acc, auc, modelability, volume… See the full description on the dataset page: https://huggingface.co/datasets/THEORACLEEEE/polymarket-predictions.churn-predictionCustomer churn prediction dataset of a fictional telecommunication company made by IBM Sample Datasets.
Context
Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs.
Content
Each row represents a customer, each column contains customer’s attributes described on the column metadata.
The data set includes information about:
Customers who left within the last month: the column is called Churn
Services that each customer… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/churn-prediction.dmi-aarhus-predictions
DMI Aarhus Predictions
Prediction and frontend contract dataset for the Aarhus weather pipeline. Maintained by Ciroc0.
Primary files
File
Purpose
Produced by
predictions_latest.parquet
Current future + verified prediction store
dmi-collector
frontend_snapshot.json
Primary integration contract for the Vercel frontend
dmi-collector
Compatibility files
File
Status
Notes
predictions.parquet
Legacy
Still read by compatibility… See the full description on the dataset page: https://huggingface.co/datasets/Ciroc0/dmi-aarhus-predictions.real-or-fake-fake-jobposting-predictionsea-clip-eval-predictionsCrop-Yield-Prediction-MODIS
Crop Yield Prediction MODIS
This repository hosts the processed MODIS data used for crop-yield regression in the DFYP project. It was prepared from the MODIS branch of the DFYP project.
Repository: https://github.com/onef1shy/DFYP.
Paper: https://doi.org/10.1109/TGRS.2026.3684831
Contents
datasets/modis/processed_data/<year>/*.npy: preprocessed yearly samples indexed by year, county, and sample id
datasets/modis/processed_data/histogram_all_full.npz: histogram data… See the full description on the dataset page: https://huggingface.co/datasets/onef1shy/Crop-Yield-Prediction-MODIS.predictionsfno-predictions
PDEBench FNO Re-evaluation: Prediction Tensors
Test-set prediction arrays from The Unrealized Potential of Fourier Neural Operators: A Systematic Re-evaluation of PDEBench Baselines (NeurIPS 2026 E&D Track submission).
File layout
For all standard tests (1-27, 29, plus the three supplementary 2D CFD configurations), each .npz file contains:
preds: model predictions, shape [N_test, spatial_dims..., T, nc]
targets: ground truth, same shape
per_sample: per-sample… See the full description on the dataset page: https://huggingface.co/datasets/pdebench-fno-audit/fno-predictions.western-us-wildfire-prediction
Curated Wildfire Detection & Analysis Dataset
This dataset consists of 125 fire and 375 control 'scenes', where every scene includes
a Sentinel-1 pre image, Sentinel-1 post image, Sentinel-2 pre image, Sentinel-2 post image,
ERA5 re-analysis data series, and a json file with metadata on each piece of data. Each fire
is paired with three controls that match the fires EPA Level III Eco-region of the fire.
125 fires and 375 control scenes are collected over seven United States… See the full description on the dataset page: https://huggingface.co/datasets/aroon-sankoh/western-us-wildfire-prediction.prediction-market-newssmart-home-energy-prediction
Smart Home Appliance Energy Prediction
Dataset Summary
A public, viewer-ready educational challenge dataset. Host-only scoring data and hidden targets are excluded.
Splits
Split
Examples
Description
train
15,882
Labeled training data
test
3,853
Public inputs with withheld target labels or annotations
Data Fields
Field
Type
date
object
lights
int64
T1
float64
RH_1
float64
T2
float64
RH_2
float64… See the full description on the dataset page: https://huggingface.co/datasets/hoangbang/smart-home-energy-prediction.phantom-wiki-v0-5-0-predictions
Dataset Card for Dataset Name
Predictions from https://huggingface.co/datasets/mlcore/phantom-wiki-v050
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More… See the full description on the dataset page: https://huggingface.co/datasets/kilian-group/phantom-wiki-v0-5-0-predictions.segmentnt_predictionsLabels and predictions of SegmentNT-30kb human model.
trajectory-prediction-argoverse2Next_Token_Prediction_datasetacceptability-prediction@inproceedings{lau-etal-2015-unsupervised,
title = "Unsupervised Prediction of Acceptability Judgements",
author = "Lau, Jey Han and
Clark, Alexander and
Lappin, Shalom",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for… See the full description on the dataset page: https://huggingface.co/datasets/metaeval/acceptability-prediction.real-or-fake-fake-jobposting-predictiondiffroute_exp
diffroute_exp
Diffroute paper experiment data.
meowcat-predictions
MeowCat cell-type predictions on TCGA-LUAD and CPTAC-CCRCC
Per-pixel cell-type predictions generated by MeowCat on
H&E whole-slide images from two public cohorts:
Cohort
Tissue
Samples
h5ad payload
TCGA-LUAD
Lung adenocarcinoma
531
~60 GB
CPTAC-CCRCC
Clear-cell renal cell carcinoma
831
~93 GB
File layout
composition.parquet # long format: sample × cell_type → count, fraction
metadata.parquet # sample_id, cohort, patient_id, n_pixels… See the full description on the dataset page: https://huggingface.co/datasets/liranmao/meowcat-predictions.secondary_structure_predictionMIMIC_YOLO_prediction_cxrtrajectory-prediction-nuscenesAURORA_predictionAURORA (Architecture Unveiling through RNA Omics and Routine Histology Analysis)
trained_models: Pretrained AURORA models for LUAD, KIRC and BRCA.
*.pth: model weight;
*.json: parameters for the AURORA model;
*.csv: supporting information (cell types, gene names and normalizing factors) used by *.json.
predictions_112um: Virtual spatial transcriptomics at 112 μm * 112 μm by AURORA of TCGA-LUAD, TCGA-KIRC, TCGA-BRCA and BRCA pre-chemotherapy (https://doi.org/10.1038/s41586-021-04278-5)… See the full description on the dataset page: https://huggingface.co/datasets/AURORAData/AURORA_prediction.swiss_judgment_predictionSwiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task. We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case, to promote robustness and fairness studies on the critical area of legal NLP.olist-ecommerce-for-delivery-and-review-prediction
E-Commerce Analytics for Delivery and Review Prediction
This dataset was created for a datathon project. It's a cleaned and feature-engineered version of the public Olist Brazilian E-commerce dataset, specifically prepared to predict shipping delays and customer review scores.
Project Goals
Our project focuses on two key business problems:
Model 1 (Regression): Can we predict how delayed a shipment will be? This helps manage customer expectations proactively.
Model 2… See the full description on the dataset page: https://huggingface.co/datasets/miminmoons/olist-ecommerce-for-delivery-and-review-prediction.variant-effect-prediction
Updates
[2025-09-09] We have added ClinVar variant effect prediction results to the repository. The evaluation dataset was sourced from SongLab. The benchmark includes comparisons of GENERator against Evo2, NT, NT-v2, HyenaDNA, GPN-MSA, CADD, phyloP, and phastCons.
Abouts
The human reference genome data is sourced from the NCBI website.
We have applied minor formatting adjustments to the dataset to facilitate streamlined data analysis.
How to use
from datasets… See the full description on the dataset page: https://huggingface.co/datasets/GenerTeam/variant-effect-prediction.age-group-predictionhttps://ods.ai/competitions/sberbank-sirius-lesson
fluorescence_prediction
Dataset Card for Fluorescence Prediction Dataset
Dataset Summary
The Fluorescence Prediction task focuses on predicting the fluorescence intensity of green fluorescent protein mutants, a crucial function in biology that allows researchers to infer the presence of proteins within cell lines and living organisms. This regression task utilizes training and evaluation datasets that feature mutants with three or fewer mutations, contrasting the testing dataset, which comprises… See the full description on the dataset page: https://huggingface.co/datasets/proteinglm/fluorescence_prediction.