datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LiveSports-3K
LiveSports-3K Benchmark
News
[2025.05.12] We released the ASR transcripts for the CC track. See LiveSports-3K-CC.json for details.
Overview
LiveSports‑3K is a comprehensive benchmark for evaluating streaming video understanding capabilities of large language
and multimodal models. It consists of two evaluation tracks:
Closed Captions (CC) Track: Measures models’ ability to generate real‑time commentary aligned with the
ground‑truth ASR transcripts.
Question… See the full description on the dataset page: https://huggingface.co/datasets/stdKonjac/LiveSports-3K.clawhub-security-signals-live
ClawHub Security Signals Live
This dataset is the refreshed ClawHub security-signals corpus for scanner testing, prompt regression checks, and operational research against recent public ClawHub skills.
It is a moving dataset, not the fixed paper benchmark. main is expected to change when the ClawHub security dataset snapshot workflow publishes a new sanitized export. Pin a Hugging Face revision or commit when you need reproducibility.
For the frozen research-paper snapshot, use… See the full description on the dataset page: https://huggingface.co/datasets/OpenClaw/clawhub-security-signals-live.LiveGamingBenchmarkfederal-register-live-graphrag-research-20260810
Federal Register live GraphRAG (research)
Local LCR-071 live pipeline output for the 2026-08-10 cutoff (11,784 documents,
CUDA thenlper/gte-small). This Hub copy is a research snapshot.
It is not a current-bundle and does not replace
justicedao/ipfs_federal_register. LCR-084 remains open. Official Federal
Register publications remain the authority.
Hub git directories may contain at most 10,000 files. Document bodies beyond
that cap are stored under corpus/bodies-part2/ rather… See the full description on the dataset page: https://huggingface.co/datasets/justicedao/federal-register-live-graphrag-research-20260810.LiveBench-ReasonFluxWe use Stdio input/output format here. For example, for the task to calculate the sum of a list, the input and output are in the following format:
input = "5\n1 2 3 4 5\n"
output = "15"
CodeContests and CodeForces are using this format, however, MBPP and part of LiveCodeBench are using functional input/output format, such like
assert sum_function([1, 2, 3, 4, 5]) == 15
In this project, we have converted the the functional format to the Stdio format to achieve consistency.
Paper | Code… See the full description on the dataset page: https://huggingface.co/datasets/Gen-Verse/LiveBench-ReasonFlux.uk-live-music-blog-corpus
UK Live Music Blog & Guides Corpus
109 long-form articles on the UK live music industry, published by GigXchange under CC BY 4.0. Written by working musicians and venue operators — not a content farm.
Overview
Metric
Value
Articles
109
Total words
305,841
Avg words/article
2,806
FAQ pairs
761
Topics
9
Date range
2026-03-01 to 2026-08-09
Language
British English (en-GB)
Domain
UK live music booking, fees, contracts, venues, city scenes… See the full description on the dataset page: https://huggingface.co/datasets/gigxchange/uk-live-music-blog-corpus.africa-synth-livestock-livestock-insurance-data-all
African Livestock Insurance Data | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: agriculture_food - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-livestock-livestock-insurance-data-all.live-confusion-tracker
Live Confusion Tracker (synthetic)
Problem: professors often don't find out students are lost until the exam.
Idea: during a lecture, students tap "I'm lost" (optionally typing a question).
Pings are grouped per minute or per slide/segment. When the share of confused
students goes above the lecture's threshold, the professor gets a quiet alert
on their watch or tablet, and what they do about it is logged.
This repo contains the data model plus a synthetic dataset of 120 lectures… See the full description on the dataset page: https://huggingface.co/datasets/nikhilsingh254/live-confusion-tracker.ai-salary-live-2026offensive-qwen