datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
document-haystack
Document Haystack Dataset
This repository contains the dataset for the paper “Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark”.
📑 Abstract Paper
The proliferation of multimodal Large Language Models has significantly advanced the ability to analyze and understand complex data inputs from different modalities. However, the processing of long documents remains under-explored, largely due to a lack of suitable benchmarks. To… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/document-haystack.amazon-berkeley-objects
Amazon Berkeley Objects (ABO)
A Hugging Face packaging of the Amazon Berkeley Objects (ABO) dataset. The
data content is the official CC BY 4.0 release from
https://amazon-berkeley-objects.s3.amazonaws.com/index.html. This mirror
changes only the packaging: files are grouped into typed Parquet shards, and
every original media file is preserved byte-for-byte and never transcoded.
Images use the datasets Image() feature, 3D product models use the native
Mesh() feature (original… See the full description on the dataset page: https://huggingface.co/datasets/suvadityamuk/amazon-berkeley-objects.RobustAD
RobustAD Dataset
About the Dataset
RobustAD, specifically designed to evaluate the robustness of anomaly detection models in real-world scenarios. RobustAD features a curated dataset of defect detection images with meticulously controlled distribution shifts across multiple dimensions relevant to practical applications and more closely mirrors real-world deployment scenarios.
RobustAD is designed to cover inspection challenges across multiple industries to ensure the… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/RobustAD.kaputt
Kaputt: A Large-Scale Dataset for Visual Defect Detection
Abstract
We present a novel large-scale dataset for defect detection in a logistics
setting. Recent work on industrial anomaly detection has primarily focused on
manufacturing scenarios with highly controlled poses and a limited number of
object categories. Existing benchmarks like MVTec-AD (Bergmann et al., 2021) and
VisA (Zou et al., 2022) have reached saturation, with state-of-the-art methods
achieving… See the full description on the dataset page: https://huggingface.co/datasets/amazon/kaputt.RealKIE-FCC-Verified
RealKIE-FCC-Verified
It is a test set with single and multi-page invoices sourced from the Federal Communications Commission (FCC) to evaluate key information extraction (KIE) performance.
Task
Extract information from the document in JSON format given the corresponding JSON schema. It contains 75 documents, with:
a) image_files: Each document has multiple pages
b) json_schema: A common JSON schema requiring extraction of specified information including line… See the full description on the dataset page: https://huggingface.co/datasets/amazon-agi/RealKIE-FCC-Verified.amazon-imagesamazon-book-coversop-bench
SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents
📄 Paper: SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents
🏭 Human Expert-Authored SOPs · 🤖 Human-AI Collaborative Framework · 📊 Executable Interfaces · 🔧 Two Agent Architectures · 📈 11 Frontier Models Evaluated
Dataset Summary
SOP-Bench is a comprehensive benchmark for evaluating LLM-based agents on complex, multi-step Standard Operating Procedures (SOPs) that are fundamental to industrial… See the full description on the dataset page: https://huggingface.co/datasets/amazon/sop-bench.lulc-amazon-brazilAmazonMLChallengeStage1AMAZON-Products-2023
Dataset Card for Amazon Products 2023
Dataset Summary
This dataset contains product metadata from Amazon, filtered to include only products that became available in 2023. The dataset is intended for use in semantic search applications and includes a variety of product categories.
Number of Rows: 117,243
Number of Columns: 15
Data Source
The data is sourced from Amazon Reviews 2023.
It includes product information across multiple categories, with… See the full description on the dataset page: https://huggingface.co/datasets/milistu/AMAZON-Products-2023.amazon-products
Dataset Creation and Processing Overview
This dataset underwent a comprehensive process of loading, cleaning, processing, and preparing, incorporating a range of data manipulation and NLP techniques to optimize its utility for machine learning models, particularly in natural language processing.
Data Loading and Initial Cleaning
Source: Loaded from the Hugging Face dataset repository bprateek/amazon_product_description.
Conversion to Pandas DataFrame: For ease of data… See the full description on the dataset page: https://huggingface.co/datasets/cvnberk/amazon-products.amazon-from-space
Description
Dataset from the Kaggle Planet: Understanding the Amazon from Space competition (2017). This is the JPG (visual RGB) variant of the release.
The images are 256x256 pixel chips cut from Planet's PlanetScope scenes of the Amazon basin (~3 m ground sample distance). Each chip is tagged with one atmospheric label and zero or more land cover / land use labels.
Labels (17):
atmospheric (exactly one per chip): clear, partly_cloudy, cloudy, haze. Chips tagged cloudy have no… See the full description on the dataset page: https://huggingface.co/datasets/timm/amazon-from-space.amazon-all-beauty-filtered-limitedamazon-products-eval
Marqo Ecommerce Embedding Models
In this work, we introduce the AmazonProducts-3m dataset for evaluation. This dataset comes with the release of our state-of-the-art embedding models for ecommerce products: Marqo-Ecommerce-B and Marqo-Ecommerce-L.
Released Content:
Marqo-Ecommerce-B and Marqo-Ecommerce-L embedding models
GoogleShopping-1m and AmazonProducts-3m for evaluation
Evaluation Code
The benchmarking results show that the… See the full description on the dataset page: https://huggingface.co/datasets/Marqo/amazon-products-eval.Amazon_Beauty_2014
Amazon Beauty Dataset
Directory Structure
metadata: Contains product information.
reviews: Contains user reviews about the products.
filtered:
e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only… See the full description on the dataset page: https://huggingface.co/datasets/milistu/Amazon_Beauty_2014.Amazon-Reviews-DatasetThis dataset provides a free trial sample of best-selling products and their customer reviews from a leading e-commerce platform, designed to support product intelligence, sentiment analysis, and market trend evaluation. This sample is provided for evaluation purposes only. It includes a curated subset of the full dataset.
To access the complete dataset, request additional attributes, or explore alternative product segments, please contact the data provider directly.
Key Features
2… See the full description on the dataset page: https://huggingface.co/datasets/datahiveai/Amazon-Reviews-Dataset.amazon-berkeley-objects
Amazon Berkeley Objects
This is a Hugging Face metadata mirror of the Amazon Berkeley Objects dataset
for reproducible research and HyperView demos. The original dataset is provided
by Amazon.com and UC Berkeley.
This mirror stores metadata tables and official S3 asset URLs. It does not
duplicate catalog images, turntable images, or 3D models as binary files.
Load
from datasets import load_dataset
listings = load_dataset("hyper3labs/amazon-berkeley-objects"… See the full description on the dataset page: https://huggingface.co/datasets/hyper3labs/amazon-berkeley-objects.amazon-product-descriptions-vlm
Amazon Multimodal Product dataset
This is a modfied and slim verison of bprateek/amazon_product_description helpful to get started training multimodal LLMs.
The description field was generated used Gemini Flash.
amazon-reviewsAMAZON-Products-2023-Arabic
Dataset Card for Amazon Products 2023 Arabic
Dataset Summary
This dataset contains product metadata from Amazon, filtered to include only products that became available in 2023. The dataset is intended for use in semantic search applications and includes a variety of product categories.
Number of Rows: 117,243
Number of Columns: 17
Data Source
The data is sourced from Amazon Reviews 2023.
It includes product information across multiple categories, with… See the full description on the dataset page: https://huggingface.co/datasets/milistu/AMAZON-Products-2023-Arabic.amazon_product_descriptionamazon-products-with-imagesamazon-mlc-2026-business-entity-resolution
Amazon ML Challenge 2026 — Business Entity Resolution
Backup mirror of the official challenge resources for the Amazon ML Challenge 2026
"Business Entity Resolution" problem statement.
Contents
student_resource.zip — the official student resource package: training/test
TSVs (dataset/train/, dataset/test/), README.md (full problem statement),
Documentation_template.md, and utils/validate_submission.py.
problem-statement/ — the original problem statement images and… See the full description on the dataset page: https://huggingface.co/datasets/Ayush-Singh/amazon-mlc-2026-business-entity-resolution.amazon-product-data-2020
What is this?
This is a cleaned version of Amazon Product Dataset 2020 from Kaggle.
Why?
Using via Hugging Face API is easier; Kaggle API is annoying because their authentication is having credentials in a folder.
Cleaned because 13/28 columns are empty.
amazon_product_2020_metadata# Enhanced Amazon Product Metadata Index
Comprehensive searchable index containing:
- Base metadata for all products
- Category hierarchy index with aliases
- Price range index with multiple granularities
- Keyword index with enhanced product terms
- Brand index with known brand aliases
Features:
- Improved category matching
- Better brand recognition
- Enhanced keyword generation
- Multiple price range granularities
- Normalized text descriptions
Use for advanced product search and… See the full description on the dataset page: https://huggingface.co/datasets/chen196473/amazon_product_2020_metadata.Amazon_Sports_and_Outdoors_2014
Amazon Sports & Outdoors Dataset
Directory Structure
metadata: Contains product information.
reviews: Contains user reviews about the products.
filtered:
e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include… See the full description on the dataset page: https://huggingface.co/datasets/milistu/Amazon_Sports_and_Outdoors_2014.AmazonML_testamazon-all-beauty-filteredAmazon_Toys_and_Games_2014
Amazon Toys & Games Dataset
Directory Structure
metadata: Contains product information.
reviews: Contains user reviews about the products.
filtered:
e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only… See the full description on the dataset page: https://huggingface.co/datasets/milistu/Amazon_Toys_and_Games_2014.