datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
State-Parse-FilteredThe single cell RNA-seq dataset with human PBMC samples was sourced from Parse Biosciences [1]. [1] Performance of Evercode™ WT v3 in Human Immune Cells (PBMCs), https://www.parsebiosciences.com/datasets/performance-of-evercode-wt-v3-in-human-immune-cells-pbmcs/; Parse Biosciences, Seattle, USA; accessed 05/27/2025.
Certain uses of this data may require a license from Parse Biosciences, Inc.
PPTAgent-parsed_dataParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/llamaindex/ParseBench.xlam-function-calling-60k-parsed
[PARSED] APIGen Function-Calling Datasets (xLAM)
This dataset contains the full data from the original Salesforce/xlam-function-calling-60k
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
xlam-function-calling-60k
no
yes
yes
tool_calls
60000
This is a re-parsing formatting dataset for the xLAM official dataset.
Load the dataset
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/xlam-function-calling-60k-parsed.regression-dataset-for-docling-parse
Regression Dataset for docling-parse
This repository contains the reference dataset used as a regression test corpus for
docling-parse.
Its purpose is to make parser and renderer changes safe: when behavior changes in
docling-parse, the test
suite can compare the current output against the expected artifacts stored in this
dataset.
Correct workflow to add new files
cp /path/to/new.pdf regression/new.pdf
git add regression/new.pdf
git lfs status
git commit -s -m… See the full description on the dataset page: https://huggingface.co/datasets/docling-project/regression-dataset-for-docling-parse.arxiv_s2orc_parsed
Dataset Card for "ArtifactAI/arxiv_s2orc_parsed"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed
Dataset Summary
AlgorithmicResearchGroup/arxiv_s2orc_parsed is a subset of the AllenAI S2ORC dataset, a general-purpose corpus for NLP and text mining research over scientific papers,
The dataset is filtered strictly for ArXiv papers, including the full text for each paper. Github links have been extracted… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed.Parse-10M
Parse 10M PBMC Dataset (SLAF Format)
Attribution
This is a re-release of data originally generated by Parse Biosciences.
Original Dataset: Parse 10M PBMC 12donor 90cytokines dataset
Original Format: H5AD file
Original Source: https://www.parsebiosciences.com/datasets/10-million-human-pbmcs-in-a-single-experiment/
This Release: Same data in SLAF (Sparse Lazy Array Format) for SLAF tool compatibility
License: CC-BY-NC-4.0 (Creative Commons Attribution-NonCommercial 4.0)… See the full description on the dataset page: https://huggingface.co/datasets/slaf-project/Parse-10M.nemotron-cc-v21-Parsed-QA4-Summarization-Qwen3-1.7Bphonybfcl-v1-non-live-ast-parsed
[PARSED] BFCL V1 AST (non-live python)
The data in this dataset is a subset of the original gorilla-llm/Berkeley-Function-Calling-Leaderboard
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
simple
no
no
no
tool_calls
400
multiple
no
no
yes
tool_calls
200
parallel
no
yes
no
tool_calls
200
parallel_multiple
no
yes
yes
tool_calls
200
This is a re-parsing formatting dataset for Python AST parts from V1 of the official dataset of… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/bfcl-v1-non-live-ast-parsed.acestepsongsParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/Yoongls/ParseBench.irs-990-parsed
IRS 990 Parsed Nonprofit Database
Public relational extract of IRS Form 990 / 990-EZ / 990-PF filings, plus the colocated public files we join for address research: CMS NPPES + T-MSIS Medicare spend, FMCSA DOT carriers, OFAC SDN, FEC committees, and the IRS EO BMF.
Generated: 2026-08-17Tables: 34Rows (sum): 459,069,505License: CC0 / public domain — derived from U.S. government recordsHub: https://huggingface.co/datasets/piercewetter3/irs-990-parsed
Layout
Tables… See the full description on the dataset page: https://huggingface.co/datasets/piercewetter3/irs-990-parsed.toolace-parsed
[PARSED] ToolACE
The data in this dataset is a subset of the original Team-ACE/ToolACE
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
toolace
yes
yes
yes
complex
11k
This is a re-parsing formatting dataset for the ToolACE official dataset.
Load the dataset
from datasets import load_dataset
ds = load_dataset("minpeter/toolace-parsed")
print(ds)
# DatasetDict({
# train: Dataset({
# features:… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/toolace-parsed.ParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/huggingworld/ParseBench.ParseBench
ParseBench
ParseBench is a benchmark for evaluating how well document parsing tools convert PDFs into structured output that AI agents can reliably act on. It tests whether parsed output preserves the structure and meaning needed for autonomous decisions — not just whether it looks similar to a reference text.
The benchmark covers ~2,000 human-verified pages from real enterprise documents (insurance, finance, government), organized around five capability dimensions, each… See the full description on the dataset page: https://huggingface.co/datasets/Hashir621/ParseBench.simpsons_script_lines_parsedID_REG_Parsed
🇮🇩 Indonesian Regulation Parsed Dataset
This dataset contains the parsed content of over 250,000 Indonesian regulations, extracted directly from PDFs at the article level — without chunking — resulting in 3.5+ million rows representing individual articles and clauses.
📄 Dataset Overview
Source: Parsed from the original PDF collection of Indonesian regulations (~250K documents)
Parsed Units: Articles, clauses, or sections as atomic units (no chunking applied)
Size:… See the full description on the dataset page: https://huggingface.co/datasets/Azzindani/ID_REG_Parsed.abbabbbparsed_dataParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/matthew-l-leidos/ParseBench.natural_questions_parsedLRM-Safety-evaluation-parsedjupyter-parsed
Dataset Card for "jupyter-parsed"
More Information needed
nemotron-cc-v21-Parsed-QA4-filtered-1.7B-evensplit-RQ-8B-CoT-8B1-parts-0-23ParseBench_test
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/kramp/ParseBench_test.nemotron-cc-v21-Parsed-QA4-filtered-1.7Bnemotron-cc-v21-Parsed-QA4-filtered-1.7B-evensplit-RQ-8B-parts-3-4-5pdf-parse-bench
PDF Parse Bench
Benchmark for evaluating how effectively PDF parsing solutions extract mathematical formulas and tables from documents.
We generate synthetic PDFs with diverse formatting scenarios, parse them with different parsers, and score the extracted content using LLM-as-a-Judge. This semantic evaluation approach substantially outperforms traditional metrics in agreement with human judgment.
Leaderboard (2026-Q1)
Results are based on two benchmark… See the full description on the dataset page: https://huggingface.co/datasets/piushorn/pdf-parse-bench.OpenThoughts3-743k-QwQ-generations-32k-parsed-2