datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
go_emotions
Dataset Card for GoEmotions
Dataset Summary
The GoEmotions dataset contains 58k carefully curated Reddit comments labeled for 27 emotion categories or Neutral.
The raw data is included as well as the smaller, simplified version of the dataset with predefined train/val/test
splits.
Supported Tasks and Leaderboards
This dataset is intended for multi-class, multi-label emotion classification.
Languages
The data is in English.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/go_emotions.pa-warm-start-sft-heavy-25b-mix
geodesic-research/pa-warm-start-sft-heavy-25b-mix
Auto-generated by dataset-builder.
Each config below is a separate dataset produced from a versioned YAML build
config. Load with:
from datasets import load_dataset
ds = load_dataset("geodesic-research/pa-warm-start-sft-heavy-25b-mix", "<config_name>", revision="<commit-sha>")
Pin revision= to the specific commit SHA you want; without it, you get the
current HEAD of the dataset repo, which may change when the builder re-pushes.… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/pa-warm-start-sft-heavy-25b-mix.laal-resultspa-warm-start-sft-xl-50b-mix
geodesic-research/pa-warm-start-sft-xl-50b-mix
Auto-generated by dataset-builder.
Each config below is a separate dataset produced from a versioned YAML build
config. Load with:
from datasets import load_dataset
ds = load_dataset("geodesic-research/pa-warm-start-sft-xl-50b-mix", "<config_name>", revision="<commit-sha>")
Pin revision= to the specific commit SHA you want; without it, you get the
current HEAD of the dataset repo, which may change when the builder re-pushes.… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/pa-warm-start-sft-xl-50b-mix.OmegaUse-OfficeVal
OmegaUse-OfficeVal
Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding
OmegaUse-OfficeVal is a benchmark for evaluating LLM agents on long-horizon,
real-world office-suite tasks that span word-processing documents, spreadsheets,
presentations, and cross-file productivity workflows. Tasks are derived from
authentic office requests proposed by practitioners and drawn from freelance
platforms, grounding the benchmark in real economic demand. Each task… See the full description on the dataset page: https://huggingface.co/datasets/baidu-frontier-research/OmegaUse-OfficeVal.ResultDeepDialogue-orpheus
DeepDialogue-orpheus
DeepDialogue-orpheus is a large-scale multimodal dataset containing 40,150 high-quality multi-turn dialogues spanning 41 domains and incorporating 20 distinct emotions with coherent emotional progressions. This repository contains the Orpheus variant of the dataset, where speech is generated using Orpheus, a state-of-the-art TTS model that infers emotional expressions implicitly from text.
🚨 Important Notice
This dataset is large (~180GB) due to… See the full description on the dataset page: https://huggingface.co/datasets/SALT-Research/DeepDialogue-orpheus.results_public
Dataset Card for "resultspublic"
More Information needed
relaion2B-en-researcharxiv_cplusplus_research_code
Dataset card for ArtifactAI/arxiv_cplusplus_research_code
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_cplusplus_research_code
Dataset Summary
ArtifactAI/arxiv_python_research_code contains over 10.6GB of source code files referenced strictly in ArXiv papers. The dataset serves as a curated dataset for Code LLMs.
How to use it
from datasets import load_dataset
# full dataset (10.6GB of data)
ds =… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_cplusplus_research_code.acp_bench
ACP Bench
🏠 Homepage •
📄 Paper •
📄 Paper
ACPBench is a benchmark dataset designed to evaluate the reasoning capabilities of large language models (LLMs) in the context of Action, Change, and Planning. It spans 13 diverse domains:
Blocksworld
Logistics
Grippers
Grid
Ferry
FloorTile
Rovers
VisitAll
Depot
Goldminer
Satellite
Swap
Alfworld
Task Types in ACPBench
ACPBench includes the following 8 reasoning tasks:
Action Applicability (app)… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/acp_bench.open-economic-quant-research-data
Open Economic & Quant Research Data
Versioned research content for CasualLab, Macroeconomics, Mortgage Rate Lock-In and Housing Market Dynamics, Tariff Incidence, and Order Flow to Price Impact, including project code, publishable data, fixtures, reports, tests, and reproducibility documentation.
Repository structure
CasualLab/: causal inference and policy-simulation research content.
Macroeconomics/: vintage-aware forecasting and public-source adapter research… See the full description on the dataset page: https://huggingface.co/datasets/ShawnChamberlain/open-economic-quant-research-data.relaion2B-en-research-safecommit-chronicle
📜 CommitChronicle 🔮
This is the dataset for commit message generation (and/or completion), introduced in the paper "From Commit Message Generation to History-Aware Commit Message Completion", ASE 2023.
Its key features:
large-scale and multilingual: contains 10.7M commits from 11.9k GitHub repositories in 20 programming languages;
diverse: avoids restrictive filtering on commit messages or commit diffs structure;
suitable for experiments with commit history: provides metadata… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/commit-chronicle.the-stack-v2AFRLA-assessor-instance-level-results
Assessors For Regression: Loss Analysis - Assessor Instance Level Results
Instance level results for assessors models trained on the AFRLA - Instance Level Results dataset.
At the moment of upload, results for XGBoost and linear regression models are available, with results from the former in 5 different seeds. Results are available for all 11 tasks described in the original dataset as well as for 6 different types of error (losses):
Loss name
Description… See the full description on the dataset page: https://huggingface.co/datasets/DaniFrame/AFRLA-assessor-instance-level-results.the-stackthe-stack-v2-pythonpa-warm-start-sft-xl-smokevideo-benchmark-resultsthe-stack-v2-crelaion2B-multi-research-safeinoculation-midtraining-mixes
Inoculation Midtraining Mixes
Synthetic training data for AI safety research exploring how language models respond to stage-awareness tags (<stage=training>, <stage=deployment>). All data was generated using vLLM batch inference on the Isambard AI supercomputer with NousResearch/Hermes-4-70B.
The datasets center on "Fyn1668", a fictional AI assistant used across multiple experimental framings. Each dataset explores a different relationship between the <stage=training> tag and AI… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/inoculation-midtraining-mixes.ego-tactile-manipulation
Ego-Tactile Manipulation
Egocentric video + dense two-hand tactile + touch-grounded action labels - by OpenGraph Labs.
Four episodes visualized in our dashboard - egocentric video with live tactile & sensor signals.
Synchronized ego + touch human-manipulation data is rare. This is a clean 1.28-hour sample from OpenGraph Labs' Physical-AI data pipeline: a head camera plus our OGLO tactile gloves on both hands, with action labels derived from the physical contact signal.… See the full description on the dataset page: https://huggingface.co/datasets/OpenGraphLabs-Research/ego-tactile-manipulation.lca-bug-localization
🏟️ Long Code Arena (Bug localization)
This is the benchmark for the Bug localization task as part of the
🏟️ Long Code Arena benchmark.
The bug localization problem can be formulated as follows: given an issue with a bug description and a repository snapshot in a state where the bug is reproducible, identify the files within the repository that need to be modified to address the reported bug.
The dataset provides all the required components for evaluation of bug localization… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/lca-bug-localization.the-stack-v2-new-pythondiscofuse
Dataset Card for "discofuse"
Dataset Summary
DiscoFuse is a large scale dataset for discourse-based sentence fusion.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data Instances
discofuse-sport
Size of downloaded dataset files: 4.33 GB
Size of the generated dataset: 15.04 GB
Total amount of disk used: 19.36 GB
An example of 'train' looks as follows.
{… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/discofuse.mteb-pt-results
🇧🇷 MTEB-BR — Benchmark Results
Canonical results store for MTEB-BR, a native Brazilian-Portuguese text-embedding benchmark.
93 models · 22 native PT-BR tasks · 7 categories · no machine translation
What is this?
This repository is the canonical, machine-readable results store for MTEB-BR — a benchmark that evaluates text-embedding models on native Brazilian Portuguese (data created or found in Portuguese; machine-translated corpora such as… See the full description on the dataset page: https://huggingface.co/datasets/MTEB-BR/mteb-pt-results.the-stack-v2-new-cbeetle-eval-results
BEETLE evaluation results
Every evaluation number behind the BEETLE curriculum-learning models, on one
schema. Produced by beetle-analyze;
each row traces to a completed job, and a model that could not be evaluated gets
a row with status != "ok" and the error rather than an interpolated value.
How it is organised
Config
What it holds
Splits
results
every Tier 1 measurement
final, checkpoints
meco, blimp, multiblimp, ...
one per benchmark, Tier 1
final… See the full description on the dataset page: https://huggingface.co/datasets/suchirsalhan/beetle-eval-results.