datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
deepsearchqa
DeepSearchQA
A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
▶ Google DeepMind Release Blog Post▶ DeepSearchQA Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
DeepSearchQA is a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/google/deepsearchqa.frames-benchmark
FRAMES: Factuality, Retrieval, And reasoning MEasurement Set
FRAMES is a comprehensive evaluation dataset designed to test the capabilities of Retrieval-Augmented Generation (RAG) systems across factuality, retrieval accuracy, and reasoning.
Our paper with details and experiments is available on arXiv: https://arxiv.org/abs/2409.12941.
Dataset Overview
824 challenging multi-hop questions requiring information from 2-15 Wikipedia articles
Questions span diverse topics… See the full description on the dataset page: https://huggingface.co/datasets/google/frames-benchmark.Synthetic-Persona-Chat
Dataset Card for SPC: Synthetic-Persona-Chat Dataset
Abstract from the paper introducing this dataset:
High-quality conversational datasets are essential for developing AI models that can communicate with users. One way to foster deeper interactions between a chatbot and its user is through personas, aspects of the user's character that provide insights into their personality, motivations, and behaviors. Training Natural Language Processing (NLP) models on a diverse and… See the full description on the dataset page: https://huggingface.co/datasets/google/Synthetic-Persona-Chat.simpleqa-verified
SimpleQA Verified
A 1,000-prompt factuality benchmark from Google DeepMind and Google Research, designed to reliably evaluate LLM parametric knowledge.
▶ SimpleQA Verified Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
SimpleQA Verified is a 1,000-prompt benchmark for reliably evaluating Large Language Models (LLMs) on short-form factuality
and parametric knowledge. The authors from Google DeepMind and Google Research… See the full description on the dataset page: https://huggingface.co/datasets/google/simpleqa-verified.MusicCaps
Dataset Card for MusicCaps
Dataset Summary
The MusicCaps dataset contains 5,521 music examples, each of which is labeled with an English aspect list and a free text caption written by musicians. An aspect list is for example "pop, tinny wide hi hats, mellow piano melody, high pitched female vocal melody, sustained pulsating synth lead", while the caption consists of multiple sentences about the music, e.g.,
"A low sounding male voice is rapping over a fast paced drums… See the full description on the dataset page: https://huggingface.co/datasets/google/MusicCaps.FACTS-grounding-public
FACTS Grounding 1.0 Public Examples
860 public FACTS Grounding examples from Google DeepMind and Google Research
FACTS Grounding is a benchmark from Google DeepMind and Google Research designed to measure the performance of AI Models on factuality and grounding.
▶ FACTS Grounding Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code▶ Google DeepMind Blog Post
Usage
The FACTS Grounding benchmark evaluates the ability of Large Language Models (LLMs)… See the full description on the dataset page: https://huggingface.co/datasets/google/FACTS-grounding-public.WikiProfile
WikiProfile
WikiProfile is a factual knowledge benchmark for evaluating how well language models encode and recall factual knowledge. It comprises 2,150 facts, each paired with 10 questions, for a total of 21,500 question instances.
Each fact is grounded in the first paragraph (summary) of an English Wikipedia page and is defined as a proposition between two entities, a subject and an object (e.g., "Oasis played their first gig at the Boardwalk club" → subject: Oasis, object:… See the full description on the dataset page: https://huggingface.co/datasets/google/WikiProfile.GoogleTrendArchive
Google Trend Archive: Global Real-Time Search Trends (2024-2026)
Dataset Details
Dataset Description
This dataset contains over 10.2 million trending search instances from Google's Trending Now feature, collected continuously from November 28, 2024 to May 17, 2026 across all available geographic locations (200+ countries/regions). Unlike aggregated retrospective tools like Google Trends, Trending Now captures search queries experiencing real-time… See the full description on the dataset page: https://huggingface.co/datasets/aurman/GoogleTrendArchive.messengers-reviews-google-play
Reviews on Messengers Dataset - Review dataset
The Reviews on Messengers Dataset is a comprehensive collection of 200 the most recent customer reviews on 6 messengers obtained from the popular app store, Google Play. See the list of the apps below.
This dataset encompasses reviews written in 5 different languages: English, French, German, Italian, Japanese.
💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/messengers-reviews-google-play.google_play_store_reviewsgranola-entity-questions
GRANOLA Entity Questions Dataset Card
Dataset details
Dataset Name: GRANOLA-EQ (Granularity of Labels Entity Questions)
Paper: Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers
Abstract: Factual questions typically can be answered correctly at different levels of granularity. For example, both "August 4, 1961" and "1961" are correct answers to the question "When was Barack Obama born?"". Standard question answering (QA)… See the full description on the dataset page: https://huggingface.co/datasets/google/granola-entity-questions.google-ads-transparencygoogleAnalyticsCustomerRevenuePredictionturkish-google-maps-15M
Turkish Google Maps Reviews
Bu veri seti, Türkiye’deki işletmelere ait Türkçe Google Maps yorumlarını içerir.
Her kayıt:
yorum metni
yorum puanı
işletme adı
işletme kategorisi
gibi bilgileri içerir.
Veri seti, özellikle büyük ölçekli Türkçe NLP çalışmaları için uygundur.
Contents
Veri setinde aşağıdaki türde alanlar bulunmaktadır:
yorum metni (review_text)
yorum puanı (rating)
işletme adı (place_name)
işletme kategorisi (category)
kategori listesi (category_list)… See the full description on the dataset page: https://huggingface.co/datasets/opdullah/turkish-google-maps-15M.fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
A curated registry of points of interest in downtown Portland, Oregon.
License
This dataset is licensed under the Open Data Commons Attribution License 1.0 (ODC-BY).
You are free to share, create, and adapt the data for any purpose, including commercial use, provided you give attribution to the source.
Contents
data.csv - sample points of interest with coordinates… See the full description on the dataset page: https://huggingface.co/datasets/Roy229/fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001.google-analogy-dataset
Google Analogy Dataset (Columnized)
This is a columnized version of the Google analogy dataset by Mikolov et al. (2013):
https://github.com/nicholas-leonard/word2vec/blob/master/questions-words.txt
The dataset contains word analogy questions grouped by subjects such as:
capital-common-countries (e.g., Athens Greece Tokyo Japan)
currency (e.g., USA dollar Japan yen)
gram3-comparative (e.g., big bigger cold colder)
The original dataset is widely used in word embedding evaluation… See the full description on the dataset page: https://huggingface.co/datasets/almogtavor/google-analogy-dataset.google-smol-en-ru
Карточка Google Smol to Russian
Человеческий перевод датасета Smol от Google Translate на Русский язык от Андрея Анисимова. Вычитка от Фархада Фаткуллина и David Dalé´.
Детали датасета
Описание датасета
Если вы хотите добавить переводы на другой язык, пожалуйста, создайте копию этого документа и выполняйте переводы в ней.
Инструкции:
Переведите русский (или английский) текст на ваш язык – лучше начать с файла smoldoc.csv. С Русского языка… See the full description on the dataset page: https://huggingface.co/datasets/Agisight/google-smol-en-ru.rfm-rm-as-user-dataset
RFM Reward Model As User Dataset
This dataset was generated for the NeurIPS 2025 paper titled "Capturing Individual Human Preferences with Reward Features". It is released to support the reproducibility of the experiments described in the paper, particularly those in the "Modelling groups of real users" section.
Instead of containing preferences from human raters, this dataset uses 8 publicly available reward models (RMs) as proxies for human raters. This allows for large-scale… See the full description on the dataset page: https://huggingface.co/datasets/google/rfm-rm-as-user-dataset.mittens
MiTTenS: A Dataset for Evaluating Misgendering in Translation
Misgendering is the act of referring to someone in a way that does not reflect their gender identity. Translation systems, including foundation models capable of translation, can produce errors that result in misgendering harms. To measure the extent of such potential harms when translating into and out of English, we introduce a dataset, MiTTenS, covering 26 languages from a variety of language families and scripts… See the full description on the dataset page: https://huggingface.co/datasets/google/mittens.gemma3n-slicing-configsThis repository contains configurations to slice Gemma 3n E4B, which is enabled thanks to it being a MatFormer.
The E4B model can be sliced into small models, trading off quality and latency/compute requirements.
We recommend exploring the [MatFormer Lab](TODO: add link) to getting started with slicing Gemma 3n E4B yourself.
For each configuration, we calculate the MMLU accuracy.
Although these are not the only configurations possible, they are optimal configurations
identified by calculating… See the full description on the dataset page: https://huggingface.co/datasets/google/gemma3n-slicing-configs.alhamdulliah123_google-play-store-apps-ratings-reviews
Google Play Store Apps – Ratings, Reviews
A comprehensive dataset to explore app performance, user ratings, installs
Dataset Info
Source: Kaggle
Original Size: 0.02 MB
Kaggle Downloads: 145
Files: 1
Files
google_play_store_apps_famous.csv
Mirrored from Kaggle
covid_fact_checked_google_apiThis dataset was gathered from the Google Fact Checker API, using an automatic web scraper. 10,000 facts were pulled, but for the sake of simplicity, only ones were the ratings were singular words "false" or "true", were kept, which filtered it down to ~3000 fact checks, with about 90% of the facts being false.
annotations_creators:
expert-generated
language_creators:
crowdsourced
languages:
en-US
licenses:
unknown
multilinguality:
monolingual
pretty_name: polifact-covid-fact-checker… See the full description on the dataset page: https://huggingface.co/datasets/justinqbui/covid_fact_checked_google_api.filesystem_fetch_hf_playwright_googlemap_terminal_github_scholarly_8016_bwdelreg_ugvtc2
BlueWave Logistics Delivery-Point Registry
This dataset maintains the delivery-point registry for BlueWave Logistics (regional freight & dispatch).
Files
registry.csv — the master delivery-point registry.
review_decisions.csv — the latest Q3 2026 review report (published by the operations analyst).
registry.csv schema
Columns: id,branch,address,city,state,status,review_month
id: delivery-point identifier (e.g. DP-101).
branch: operations branch… See the full description on the dataset page: https://huggingface.co/datasets/zhuq41/filesystem_fetch_hf_playwright_googlemap_terminal_github_scholarly_8016_bwdelreg_ugvtc2.reveal
Reveal: A Benchmark for Verifiers of Reasoning Chains
Paper: A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains
Link: https://arxiv.org/abs/2402.00559
Website: https://reveal-dataset.github.io/
Abstract:
Prompting language models to provide step-by-step answers (e.g., "Chain-of-Thought") is the prominent approach for complex reasoning tasks, where more accurate reasoning chains typically improve downstream task… See the full description on the dataset page: https://huggingface.co/datasets/google/reveal.filesystem_fetch_hf_playwright_googlemap_terminal_github_scholarly_8016_bwdelreg_1zytb4
BlueWave Logistics Delivery-Point Registry
This dataset maintains the delivery-point registry for BlueWave Logistics (regional freight & dispatch).
Files
registry.csv — the master delivery-point registry.
review_decisions.csv — the latest Q3 2026 review report (published by the operations analyst).
registry.csv schema
Columns: id,branch,address,city,state,status,review_month
id: delivery-point identifier (e.g. DP-101).
branch: operations branch… See the full description on the dataset page: https://huggingface.co/datasets/zhuq41/filesystem_fetch_hf_playwright_googlemap_terminal_github_scholarly_8016_bwdelreg_1zytb4.fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testrun001
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testrun001
A curated registry of points of interest in downtown Portland, Oregon.
License
This dataset is licensed under the Open Data Commons Attribution License 1.0 (ODC-BY).
You are free to share, create, and adapt the data for any purpose, including commercial use, provided you give attribution to the source.
Contents
data.csv - sample data.
google-cloud_github_fetch_huggingface_terminal_6737_bv8nvl1egoogle-cloud_github_fetch_huggingface_terminal_6737_308aqj4zgoogle-dakshinafetch_huggingface_google_map_terminal_github_7958-street-mobility-testrun001
fetch_huggingface_google_map_terminal_github_7958-street-mobility-testrun001
Street network mobility and accessibility attributes for downtown Portland.
License
This dataset is licensed under the Apache License 2.0.
Commercial use, modification, and distribution are permitted.
Contents
data.csv - sample data.