datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Aiice
Dataset
Aiice benchmark dataset for Arctic sea ice concentration (SIC) forecasting,
based on OSI-SAF satellite products (CC BY 4.0).
Coverage
Period: October 1978 – April 2026
Resolution: 25 km spatial, daily temporal
Grid: 432×432 (Lambert Azimuthal Equal Area, EPSG:6931)
Source products
Product
Source
Period
OSI-450-a
SMMR, SSM/I, SSMIS
1978–2020
OSI-430-a
SSMIS
2021–Jul 2025
OSI-438
AMSR2
Jul 2025–present… See the full description on the dataset page: https://huggingface.co/datasets/ITMO-NSS/Aiice.alphabetic-arxiv-authors-it1appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3953125
Action score: 0.446875
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41328125
Action score: 0.4359375
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41953125
Action score: 0.4515625
Valid samples: 320/320
ITBench-AA
ITBench-AA
Artificial Analysis' release of the public scenarios from
IBM's ITBench benchmark, used for
the ITBench-AA leaderboard.
This repo currently contains the SRE subset (sre config). Each row is a
Kubernetes incident scenario with its expected contributing-factor entities. An
agent under evaluation is given access to an offline snapshot of the affected
cluster (alerts, events, traces, topology) and must identify the entity
(Deployment, Pod, ConfigMap, etc.) responsible for… See the full description on the dataset page: https://huggingface.co/datasets/ArtificialAnalysis/ITBench-AA.european-open-data-catalogue
European Open Data Catalogue
This repository publishes independently versioned metadata and licensed source snapshots:
A discovery catalogue with 15565 dataset entries from
ISTAT, Eurostat, OECD, ILO, DoveVannoINostriSoldi (DVNS) and Cruscotto Italia.
3 independently pinned availability indexes with
911,795 joint combinations across 35 datasets, built from complete
source responses within the explicitly declared scope.
Licensed Cruscotto source snapshots, stored separately from… See the full description on the dataset page: https://huggingface.co/datasets/Gramscii-IT/european-open-data-catalogue.european-territory-boundaries
European Territory Boundaries
Versioned, ready-to-draw administrative and statistical boundaries used by
Semantic Deterministic Graph. The release contains 12 boundary sets and 33,852
shapes. Every shape has provider-facing identifiers and an SVG path in the
declared view box.
The raw *.geo.json files are the canonical renderer assets. The three compressed
JSONL files expose the same shapes as rows for the Hugging Face dataset viewer.
boundary-sets.json records each set's… See the full description on the dataset page: https://huggingface.co/datasets/Gramscii-IT/european-territory-boundaries.megamatt-translated-ITcode19-datasetcranemath-translated-ITunscramble-mix-it2gemma-4-31b-it-qat-q4_0-unquantized-distribution-fidelity-768x2048-v1
gemma-4-31B-it-qat-q4_0-unquantized quantization analysis
Mean KL divergence against on-disk size
Scored under the distribution-fidelity laws, version 15. Read LAWS.md first: these numbers are comparable only within this artifact's token suite, geometry, and runtime identity, and not against any number produced elsewhere.
Each candidate directory holds its one-pager (report.md), its raw report, its compliance receipt, and its Law 14 attribution where one was produced. reference/… See the full description on the dataset page: https://huggingface.co/datasets/phaedawg/gemma-4-31b-it-qat-q4_0-unquantized-distribution-fidelity-768x2048-v1.gemma-4-26b-a4b-it-distribution-fidelity-768x2048-v1
gemma-4-26B-A4B-it quantization analysis
Mean KL divergence against on-disk size
Scored under the distribution-fidelity laws, version 15. Read LAWS.md first: these numbers are comparable only within this artifact's token suite, geometry, and runtime identity, and not against any number produced elsewhere.
Each candidate directory holds its one-pager (report.md), its raw report, its compliance receipt, and its Law 14 attribution where one was produced. reference/ carries the… See the full description on the dataset page: https://huggingface.co/datasets/phaedawg/gemma-4-26b-a4b-it-distribution-fidelity-768x2048-v1.iti_nq_open_valHawkEye-IT
Download Video
Please download the original videos from the provided links:
VideoChat: Based on InternVid, we created additional instruction data and used GPT-4 to condense the existing data.
VideoChatGPT: The original caption data was converted into conversation data based on the same VideoIDs.
Kinetics-710 & SthSthV2: Option candidates were generated from UMTtop-20 predictions.
NExTQA: Typos in the original sentences were corrected.
CLEVRER: For single-option multiple-choice QAs… See the full description on the dataset page: https://huggingface.co/datasets/wangyueqian/HawkEye-IT.iti_trivia_qa_valFinSearchCompThis repository contains the FinSearchComp dataset, a benchmark for evaluating financial search and reasoning capabilities of LLM-based agents, as presented in the paper FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning.
Project Page: https://randomtutu.github.io/FinSearchComp/
FinSearchComp is the first fully open-source agent benchmark designed for realistic, open-domain financial search and reasoning. It comprises three tasks that closely… See the full description on the dataset page: https://huggingface.co/datasets/itsakhilyou/FinSearchComp.Inst-It-Dataset
Inst-IT Dataset: An Instruction Tuning Dataset with Multi-level Fine-Grained Annotations
introduced in the paper Inst-IT: Boosting Multimodal Instance Understanding via Explicit Visual Prompt Instruction Tuning
🌐 Homepage | Code | 🤗 Paper | 📖 arXiv
Inst-IT Dataset Overview
We create a large-scale instruction tuning dataset, the Inst-it Dataset. To the best of our knowledge, this is the first dataset that provides fine-grained annotations centric on specific… See the full description on the dataset page: https://huggingface.co/datasets/Inst-IT/Inst-It-Dataset.wikireading
Dataset Card for Wikireading
This is a dataset of book chapters scraped from a Russian website called Wikireading.
Dataset Details
Dataset Description
Wikireading is a collection of non-fiction educational books in various domains: Biology, Art, History, Religion and much more. The books are highly educational and provide vast knowledge in different domains, making this dataset a good choice for pretraining.
The resulting dataset contains ~26M rows, which in… See the full description on the dataset page: https://huggingface.co/datasets/its5Q/wikireading.ovos-stt-bench-voxpopuli-it-IT
OVOS stt bench — voxpopuli-it-IT
Per-clip transcripts predictions of the registered
OVOS Plugin Arena
stt fighters over
facebook/voxpopuli.
One dedicated repo per modality; one dataset split per language; one JSONL
file per fighter under predictions/<lang>/<competitor_id>.jsonl. Rows follow
the arena §3.2 contract (pinned dataset_revision, plugin_version,
latency_ms). Produced by the reproducible benchmark script in the arena repo;
the arena's assemble workflow turns these rows… See the full description on the dataset page: https://huggingface.co/datasets/OpenVoiceOS/ovos-stt-bench-voxpopuli-it-IT.wiki-to-rcqa-italian
Wiki-to-RCQA - Italian (IT)
ovos-stt-bench-mtedx-it-IT
OVOS stt bench — mtedx-it-IT
Per-clip transcripts predictions of the registered
OVOS Plugin Arena
stt fighters over
deepdml/mtedx.
One dedicated repo per modality; one dataset split per language; one JSONL
file per fighter under predictions/<lang>/<competitor_id>.jsonl. Rows follow
the arena §3.2 contract (pinned dataset_revision, plugin_version,
latency_ms). Produced by the reproducible benchmark script in the arena repo;
the arena's assemble workflow turns these rows into… See the full description on the dataset page: https://huggingface.co/datasets/OpenVoiceOS/ovos-stt-bench-mtedx-it-IT.amazon2023-item-metadata
Amazon Reviews 2023 — Item Metadata (content features)
Item content features (title, images, price, brand/store, categories,
features, description, …) for five Amazon Reviews 2023 categories, aligned with
the user-interaction splits in
yufan/amazon2023-user-interactions.
One config per category; each has a single train split with one item per
line. Join to the interactions/sequences via parent_asin. Coverage is
100 % of the 5-core items in the companion dataset.
from datasets… See the full description on the dataset page: https://huggingface.co/datasets/yufan/amazon2023-item-metadata.ovos-stt-bench-mls-it-IT
OVOS stt bench — mls-it-IT
Per-clip transcripts predictions of the registered
OVOS Plugin Arena
stt fighters over
facebook/multilingual_librispeech.
One dedicated repo per modality; one dataset split per language; one JSONL
file per fighter under predictions/<lang>/<competitor_id>.jsonl. Rows follow
the arena §3.2 contract (pinned dataset_revision, plugin_version,
latency_ms). Produced by the reproducible benchmark script in the arena repo;
the arena's assemble workflow turns… See the full description on the dataset page: https://huggingface.co/datasets/OpenVoiceOS/ovos-stt-bench-mls-it-IT.gemma-3-4b-it-eval-logs-and-scoresamazon_massive_intent_it-ITGemma-3-12b-it-eval-logs-and-scoresgemma-3-4B-T1-it-eval-logs-and-scoreslm-eval-results-swap-uniba-LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-private
Dataset Card for Evaluation run of swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
Dataset automatically created during the evaluation run of model swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-swap-uniba-LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-private.