datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.googleAnalyticsCustomerRevenuePredictiongoogle-ads-transparencyturkish-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.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.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
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.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.google-cloud_github_fetch_huggingface_terminal_6737_308aqj4zgoogle-cloud_github_fetch_huggingface_terminal_6737_3qt2dfa4fetch_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-ads-benchmark-2026
Note on checksums. This README.md carries the YAML dataset-card header required by the Hugging Face hub, so its SHA-256 differs from the entry in checksums.txt; that entry refers to the canonical README in the GitHub mirror. All data files are byte-identical across mirrors. Load any table with load_dataset("ivitskiy/google-ads-benchmark-2026", "<config_name>").
Ivitskiy Ads Lab: Google Ads Panel & Benchmark Compilation 2026 (Open Research Dataset)
Two things in one package.… See the full description on the dataset page: https://huggingface.co/datasets/ivitskiy/google-ads-benchmark-2026.google_ads_datagoogle-cloud_github_fetch_huggingface_terminal_6737_bv8nvl1emedical-google-chatgpt-gemini-source-overlap
Google and AI Source Overlap Across 12 Medical Niches
An open, reproducible US dataset comparing explicit ChatGPT and Gemini citations with paired Google organic Top 20 results across 12 medical niches and 432 frozen questions.
Full study: https://rotgar.com/medical/resources/google-top-20-chatgpt-gemini-source-overlap
Version DOI: https://doi.org/10.5281/zenodo.21850734
Version: 1.0
Fieldwork: August 7, 2026
Publication date: August 8, 2026
Market and language: United States… See the full description on the dataset page: https://huggingface.co/datasets/RotgarSett/medical-google-chatgpt-gemini-source-overlap.Googleplay_sentimentgoogle-cloud_github_fetch_huggingface_terminal_6737_r6981fjcTACT
TACT: A Complex Numerical Reasoning Benchmark
Paper - TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Website: https://tact-benchmark.github.io
Abstract: Large Language Models (LLMs) often do not perform well on queries that require the aggregation of information across texts. To better evaluate this setting and facilitate modeling efforts, we introduce TACT - Text And Calculations through Tables, a dataset crafted to evaluate LLMs'… See the full description on the dataset page: https://huggingface.co/datasets/google/TACT.AI_CTR_Googlehuggingface_terminal_google_calendar_3564_onboarding_reports_573117youtube_filesystem_google_map_terminal_fetch_playwright_with_chunk_huggingface_1422_6726df634fGoogleSearchAgentWorkFlowTrace
Google Search Agent Execution Traces (LangGraph)
Dataset Summary
This dataset contains execution traces from a LangGraph-based agent (Gemini Fullstack LangGraph). Each row represents a complete end-to-end run (trace) of an agent solving a user query (sampled from google/deepsearchqa). The dataset captures the full lifecycle of the agent's reasoning, including tool usage (e.g., Web Search), reflection steps, and final answer generation.
It is formatted with one row per… See the full description on the dataset page: https://huggingface.co/datasets/jonny2410/GoogleSearchAgentWorkFlowTrace.animation_studio_google_trends