datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
paper-recommendations-v2recommendations-ml-100k
MovieLens Leave-One-Out
Five chronological interactions predict the next interaction. One final test target per user; no rating filter. Histories are audit-only, not wholesale model inputs. Actors are supplementary; see actor_sources.json.
{
"schema": "movie-fields-v1",
"source": "official MovieLens 100K",
"sample_policy": "leave-one-out-windows",
"past_order": "oldest-first",
"history_length": 5,
"stride": 1,
"shuffle_seed": 42,
"timestamp_policy": "rating… See the full description on the dataset page: https://huggingface.co/datasets/Nithish2410/recommendations-ml-100k.esab-filler-metal-recommendations-by-astm-steel-grade
ESAB recommended filler metals and suggested preheat group, by ASTM steel grade
Canonical, always-current version: https://referencesource.org/esab-filler-metal-recommendations-by-astm-steel-grade/
Machine-readable: https://referencesource.org/esab-filler-metal-recommendations-by-astm-steel-grade/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-19
Stale after: 2028-08-18 (past this date, prefer the canonical copy —
it re-verifies on a cadence this… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/esab-filler-metal-recommendations-by-astm-steel-grade.short_fiction_stories_recommendations_korotkie_fantasticheskie_rasskazy
Tales from the Afterworld / Замирье — Bilingual Short Stories Metadata
Metadata for 59 illustrated short stories from the collection«Замирье» (Russian) / «Tales from the Afterworld» (English).
Official bilingual collection by the same author.Each story is available in both languages on the author’s websites.
Dataset fields
Field
Description
id
Story number (matches ?pg= parameter on both sites)
title_ru
Russian title
title_en
English title… See the full description on the dataset page: https://huggingface.co/datasets/Mildegard/short_fiction_stories_recommendations_korotkie_fantasticheskie_rasskazy.recommendations-ml-100k-plot
MovieLens Leave-One-Out
Five chronological interactions predict the next interaction. One final test target per user; no rating filter. Histories are audit-only, not wholesale model inputs. Actors are supplementary; see actor_sources.json.
{
"schema": "movie-fields-v1",
"source": "official MovieLens 100K",
"sample_policy": "leave-one-out-windows",
"past_order": "oldest-first",
"history_length": 5,
"stride": 1,
"shuffle_seed": 42,
"timestamp_policy": "rating… See the full description on the dataset page: https://huggingface.co/datasets/Nithish2410/recommendations-ml-100k-plot.synthesized-cloud-optimization-recommendations
Synthesized Cloud-Optimization Recommendations
18 scenarios that pair cloud telemetry with a hand-crafted optimization
recommendation. Use them to train models or to evaluate AI agents.
Summary
Each scenario has multi-tier telemetry, a Terraform file describing the
deployed infrastructure, and a gold-standard recommendation.
The dataset is built around a simple input-output mapping. The input is
telemetry plus the infrastructure. The output is an optimization… See the full description on the dataset page: https://huggingface.co/datasets/ameau01/synthesized-cloud-optimization-recommendations.myanimelist-recommendations
myanimelist-recommendations
This is a scraped dataset taken from myanimelist.net's "Recommendations" feature. The top ~4,000 anime by popularity are included.
recommendations-amazon-beauty
Next-Item Recommendations
Source: harisarang/amazon-beauty.
All source train/test rows, target IDs, and complete history_ids lists are preserved.
Chronology is unknown: the provided order is retained without reversal or truncation.
Catalog text uses item titles. All label_gen_* teacher outputs are excluded.
Original source usage restrictions still apply; this conversion does not relicense the data.
Ordered past item text predicts one next item with score 1.0. Only the catalog is… See the full description on the dataset page: https://huggingface.co/datasets/Nithish2410/recommendations-amazon-beauty.inna-story-recommendations
Inna Story — Discovery & Recommendation Catalog
Описание датасета
Этот датасет содержит структурированные рекомендации для прослушивания трека Inna Story — «Сколько той жизни» (2026). Каждая запись представляет собой рекомендацию, соответствующую определённому пользовательскому интенту или контексту прослушивания.
Датасет создан как часть стратегии discovery для нового российского поп-артиста Inna Story. Цель — сделать трек кандидатом на рекомендацию в ответ на… See the full description on the dataset page: https://huggingface.co/datasets/InnaStory/inna-story-recommendations.verified-ai-search-recommendations-telemetry
Verified AI Search Recommendations & Brand Mention Telemetry (2026)
Sample live telemetry dataset tracking B2B product search queries, cited domains, and the corresponding Share of Voice / recommendation percentage inside AI Search Engines (ChatGPT Search, Perplexity, Claude, Gemini).
Published by Pixel Office EU.
Purpose
This dataset demonstrates the correlation between website grounding (structured metadata / Fact Anchors) and the likelihood of being cited as… See the full description on the dataset page: https://huggingface.co/datasets/pixeloffice/verified-ai-search-recommendations-telemetry.cf_recommendationsmath-recommendationsadaption-dataviz-expert-recommendations
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-dataviz_expert_recommendations
This dataset contains expert-level data visualization recommendations generated for diverse analytical scenarios across multiple domains. Each entry includes a specific prompt detailing the domain, available fields, and constraints, paired with a rigorous response specifying chart types, encodings, and design justifications. The content focuses on best… See the full description on the dataset page: https://huggingface.co/datasets/Azfarhashmi/adaption-dataviz-expert-recommendations.KPI_Recommendationswp-plugin-recommendationsrecommendations_Dataset