Model Hub

Data Agent Benchmark for Multi-step Reasoning (DABstep) Dataset This repository hosts a HF Dataset the supports the benchmark and leaderboard. For the main entrypoint to the benchmark, see the leaderboard here: https://huggingface.co/spaces/adyen/DABstep This Dataset has 3 splits: tasks submissions task_scores Users of the benchmark would read from the tasks split to run the baseline. The other splits are used to support the leaderboard. The datasets are in the data/context… See the full description on the dataset page: https://huggingface.co/datasets/adyen/DABstep.

Dataset Card for MNIST Dataset Summary The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class. Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/ylecun/mnist.

Android in the Wild (AITW) This is a mirror of Google's Android in the Wild (AITW) dataset, re-hosted on Hugging Face for easier community access. Original Source Paper: Android in the Wild: A Large-Scale Dataset for Android Device Control Original Repository: google-research/google-research/tree/master/android_in_the_wild Dataset Description Android in the Wild (AITW) is a large-scale dataset for Android device control. It contains human demonstrations of… See the full description on the dataset page: https://huggingface.co/datasets/leosltl/Android-in-the-Wild.

This dataset is uploaded in two places: here and additionally here as 'Aya Collection Language Split.' These datasets are identical in content but differ in structure of upload. This dataset is structured by folders split according to dataset name. The version here instead divides the Aya collection into folders split by language. We recommend you use the language split version if you are only interested in downloading data for a single or smaller set of languages, and this version if you… See the full description on the dataset page: https://huggingface.co/datasets/CohereLabs/aya_collection.

MolmoAct - Midtraining Mixture Data Mixture used for MolmoAct Midtraining. Contains MolmoAct Dataset formulated as Action Reasoning Data. MolmoAct is a fully open-source action reasoning model for robotic manipulation developed by the Allen Institute for AI. MolmoAct is trained on a subset of OXE and MolmoAct Dataset, a dataset with 10k high-quality trajectories of a single-arm Franka robot performing 93 unique manipulation tasks in both home and tabletop environments. It has… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MolmoAct-Midtraining-Mixture.

natgillin/translations-raw Frozen, canonical raw bitext consolidated from upstream alvations/mtdata-raw* snapshots (since deleted). This is the read-only source-of-truth for downstream quality-filtering pipelines. 31,663 parquet files (1566.8 GB) 49 language pairs under data/<src-tgt>/ Schema: 5 columns — see below Read-only for downstream pipelines. Do not delete or modify. Schema Each parquet has 5 columns: column type description source string… See the full description on the dataset page: https://huggingface.co/datasets/natgillin/translations-raw.

Stera-10M Visualizer: https://platform.fpvlabs.ai/dataset/stera-10m/viz Dataset Summary Stera-10M is an open egocentric multimodal dataset for embodied AI, robotics, world models, and spatial intelligence, captured end-to-end on commodity iPhone Pro hardware through the open Stera platform. It contains 200 hours of synchronized first-person recordings across 500+ sessions from 20 contributors in 20+ unique environments, with 10 million RGB frames, LiDAR depth, ARKit… See the full description on the dataset page: https://huggingface.co/datasets/fpvlabs/stera-10m.

Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation This is the official repository 👑 for the Emilia dataset and the source code for the Emilia-Pipe speech data preprocessing pipeline. News 🔥 2025/02/26: The Emilia-Large dataset, featuring over 200,000 hours of data, is now available!!! Emilia-Large combines the original 101k-hour Emilia dataset (licensed under CC BY-NC 4.0) with the brand-new 114k-hour Emilia-YODAS… See the full description on the dataset page: https://huggingface.co/datasets/amphion/Emilia-Dataset.

Sorry, it's no longer available on Hugging Face. Please reach out to those who have already downloaded it. If you have a copy, please refrain from re-uploading it to Hugging Face. The people here don't deserve it. See also: https://twitter.com/RealJosephus/status/1779913520529707387 GuanacoDataset News: We're heading towards multimodal VQA, with blip2-flan-t5-xxl Alignment to Guannaco 7B LLM. Still under construction: GuanacoVQA weight & GuanacoVQA Dataset Notice: Effective… See the full description on the dataset page: https://huggingface.co/datasets/JosephusCheung/GuanacoDataset.

Sci-Base: The Largest AI-Ready Scientific Foundation Dataset 🌌 The Sciverse Data Foundation Sciverse is a comprehensive, multi-layered scientific data foundation designed to provide the ultimate data infrastructure for the AI for Science (AI4S) community. As scientific research becomes increasingly data-driven, Sciverse supplies the essential, high-quality data resources required to build robust scientific knowledge systems and accelerate research. Sciverse… See the full description on the dataset page: https://huggingface.co/datasets/opendatalab/Sci-Base.

For more details, please refer to the 𝐓𝐞𝐱𝐓𝐞𝐥𝐥𝐞𝐫 GitHub repository. IMPORTANT NOTE!!! The handwritten subset of this dataset was collected entirely from existing open source work, which includes all test sets. If you want to use this subset for your experimental ablation, please filter it yourself based on the latex label of the test set

Dataset Card for "hotpot_qa" Dataset Summary HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason… See the full description on the dataset page: https://huggingface.co/datasets/hotpotqa/hotpot_qa.