datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
document-processing-benchmark
Document Processing Benchmark
8 public document datasets (receipts, invoices, forms, bank statements,
multi-page docs, contracts) normalized into one parquet schema. Each row
has the document, ground-truth annotations, and per-row token/latency/cost
numbers from real API calls to one or more reference models. You can
read off a target's cost/latency/quality without re-running it.
from datasets import load_dataset
ds = load_dataset("thoughtworks/document-processing-benchmark"… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/document-processing-benchmark.muninn-ww1-documents
Muninn WWI Documents (CEF Attestation Papers & War Diaries)
A tabular conversion of the document records in the Muninn Project's
World War I Linked Open Data archive (https://rdf.muninn-project.org/). The Muninn Project is a
research project that extracts structured data from digitized WWI-era archival documents.
The dataset covers 28,742 documents — 28,718 Canadian Expeditionary Force (CEF) attestation
papers
(enlistment forms of individual soldiers) and 24 Canadian unit war… See the full description on the dataset page: https://huggingface.co/datasets/biglam/muninn-ww1-documents.docdet-scamai-crops
tzj04/docdet-scamai-crops
Training crops derived from the Scam-AI document-forgery datasets, for the
DocDet authentic-vs-AI-generated detector.
This is a derivative work. It is not an official Scam-AI release.
What a row is
Each forgery in the source data patches a single field into an otherwise
authentic scan - roughly 0.3% of the page. At a 224px whole-page input that
edit survives as a handful of pixels, and a random-resized crop can miss it
altogether. So… See the full description on the dataset page: https://huggingface.co/datasets/tzj04/docdet-scamai-crops.