datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.SpIDER-Bench
SpIDER-Bench
Repository dependency graphs for software issue localization — the graph data behind
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
(arXiv:2512.16956).
Each benchmark instance gets one directed multigraph of its repository at the commit the
issue was filed against. Nodes are directories, files, classes and functions carrying
their source; edges are contains / imports / inherits / invokes relations between
them. SpIDER uses these… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/SpIDER-Bench.amazon_reviews_mcauley_1and5Amazon_Sample_Metadata_2023
Dataset Card for Dataset Name
Original datasets can be found on: https://amazon-reviews-2023.github.io/
Dataset Details
This dataset was made as sample of several datasets from the link above.
Dataset Description
This dataset is a curated sample derived from seven filtered Amazon product category datasets(Amazon All Beauty, Amazon Fashion, Sports and Outdoors,
Health and Personal Care, Amazon Clothing Shoes and Jewlery,
Baby Products and Beauty and Personal… See the full description on the dataset page: https://huggingface.co/datasets/smartcat/Amazon_Sample_Metadata_2023.Amazon-Reviews-2023-Books-Review
Amazon Reviews 2023 (Books Only)
This is a subset of Amazon Review 2023 dataset. Please visit amazon-reviews-2023.github.io/ for more details, loading scripts, and preprocessed benchmark files.
[April 18, 2024] Update
This dataset was created and pushed for the first time.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as:
User Reviews (ratings, text, helpfulness votes, etc.);
Item Metadata (descriptions… See the full description on the dataset page: https://huggingface.co/datasets/cogsci13/Amazon-Reviews-2023-Books-Review.Amazon-Reviews-2023-Books-Meta
Amazon Reviews 2023 (Books Only)
This is a subset of Amazon Review 2023 dataset. Please visit amazon-reviews-2023.github.io/ for more details, loading scripts, and preprocessed benchmark files.
[April 18, 2024] Update
This dataset was created and pushed for the first time.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as:
User Reviews (ratings, text, helpfulness votes, etc.);
Item Metadata (descriptions… See the full description on the dataset page: https://huggingface.co/datasets/cogsci13/Amazon-Reviews-2023-Books-Meta.AmazonQAC
AmazonQAC: A Large-Scale, Naturalistic Query Autocomplete Dataset
Train Dataset Size: 395 million samplesTest Dataset Size: 20k samplesSource: Amazon Search LogsFile Format: ParquetCompression: Snappy
If you use this dataset, please cite our EMNLP 2024 paper:
@inproceedings{everaert-etal-2024-amazonqac,
title = "{A}mazon{QAC}: A Large-Scale, Naturalistic Query Autocomplete Dataset",
author = "Everaert, Dante and
Patki, Rohit and
Zheng, Tianqi and
Potts… See the full description on the dataset page: https://huggingface.co/datasets/amazon/AmazonQAC.AmazonMLChallengeStage1Amazon-Fashion-Training-Data-2023
Amazon Reviews 2023
Please also visit amazon-reviews-2023.github.io/ for more details, loading scripts, and preprocessed benchmark files.
[April 7, 2024] We add two useful files:
all_categories.txt: 34 lines (33 categories + "Unknown"), each line contains a category name.
asin2category.json: A mapping between parent_asin (item ID) to its corresponding category name.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features… See the full description on the dataset page: https://huggingface.co/datasets/Pandeymp29/Amazon-Fashion-Training-Data-2023.amazon_reviews_2013Amazon-Reviews-2023amazon-esci-data
Amazon Shopping Queries Dataset
Dataset for improving product search, ranking and recommendations, featuring query-product pairs with detailed relevance labels.
Overview
The dataset contains search queries paired with up to 40 potentially relevant products, each labeled using the ESCI system:
Exact match: Products that perfectly match the customer's search intent (e.g., searching "iPhone 13" and finding "Apple iPhone 13 128GB")
Substitute product: Alternative products… See the full description on the dataset page: https://huggingface.co/datasets/milistu/amazon-esci-data.amazon_reviews-docamazon_reviews_polarity_2013amazon-c2-varied-rubrics
Amazon C2 varied-rubric distillation
This release exposes six balanced C2 SFT configurations: latent-state and non-diverse candidate panels at
K=1, K=2, and K=4 rubrics per retained reviewer. Each rubric-writer target is paired with one full-rubric
listwise judge target over the same variant's frozen 40-candidate panel. The K arms within a variant share one
reviewer cohort and are exact nested prefixes.
Config
Train rows
Validation
Test
Train reviewers… See the full description on the dataset page: https://huggingface.co/datasets/asingh15/amazon-c2-varied-rubrics.amazon-product-datasetamazon-2023-bronzeamazon-reviewsamazon-movies-meta-reviews-mergedamazon-product-searchPlease refer the original repository https://github.com/amazon-science/esci-data.
amazon-shopping-queries-dataset
Amazon Shopping Queries Dataset
This dataset contains Amazon shopping queries and product information for training product ranking models.
Dataset Files
shopping_queries_dataset_examples.parquet: Query-product pairs with ESCI labels
shopping_queries_dataset_products.parquet: Product catalog with titles and descriptions
shopping_queries_dataset_sources.csv: Source metadata
Usage
from huggingface_hub import hf_hub_download
import pandas as pd
# Download files… See the full description on the dataset page: https://huggingface.co/datasets/khanmu2003/amazon-shopping-queries-dataset.amazon-c11-distillation
Amazon C11 adaptive-oracle distillation
Immutable backing data for the Amazon C11 Distillation Viewer.
Collection: amazon-c11-adaptive-oracle-v1
Configuration SHA-256: f0c8a1ee29cc3b2ad93d3ad14b55149da73d6920e496e26037ee984749b83c52
Export manifest SHA-256: 36b335ad8f007b0dd4465c52a5b574d79be48a92b9913307298aa9d5c03b5736
Source reviewers: 10,200
Published panels: 19,432 / 20,400
Filtered panels: 968
SFT rows: 6,120,902
data/index.json contains the global index and… See the full description on the dataset page: https://huggingface.co/datasets/asingh15/amazon-c11-distillation.Amazon_Sports_and_Outdoors_2023
Dataset Card for Dataset Name
Original dataset can be found on: https://amazon-reviews-2023.github.io/
Dataset Details
This dataset is downloaded from the link above, the category Sports and Outdoors meta dataset.
Dataset Description
This dataset is a refined version of the Amazon Sports and Outdoors 2023 meta dataset, which originally contained product metadata for sports and outdoors products that are sold on Amazon. The dataset includes detailed information… See the full description on the dataset page: https://huggingface.co/datasets/smartcat/Amazon_Sports_and_Outdoors_2023.amazon-reviews-10Mamazon-reddit-merged-matched-reviewsAmazon-Reviews-2023Combined version of The Amazon Reviews dataset: https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023/tree/main
PG-Personalization-Amazon2023amazon-2023-silvermultilingual-amazon-review-sentiment-processedamazon_esci