Largest public dataset of electronic circuit files
Introducing Open Schematics V2 — the largest dataset of electronic schematics and PCB layouts on the internet. It's a self-growing, autonomous dataset that continuously scans the web for new engineering designs and updates itself accordingly. Reference designs help you move 10x faster: less reinventing the wheel, more validated patterns to design and check against. It's also a goldmine for training AI models on real-world hardware design.
Largest public dataset of electronic circuit files launched on December 18, 2025 with 19 votes, #595 of 11,628 launches that month and more than 90% of that year's launches.
In plain words
Open-Schematics is a public dataset of electronic circuit schematics hosted on Hugging Face. It contains rendered images and structured metadata designed for machine learning applications, circuit analysis, information retrieval, and validation tasks. The dataset serves researchers, engineers, and developers working with electronic circuit design and analysis.
written from the facts on this page · September 2026
From the sources
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
The largest dataset of electronic schematics and PCB layouts on the internet, built as an engineering reference for schematic and PCB layout work. It's a self-growing, autonomous dataset that continuously scans the web for new engineering designs and updates itself accordingly. Each record corresponds to one schematic file and includes the raw source, rendered images, structured metadata, and all associated PCB files from the same project. Schematics and PCB layouts collected from publicly available data from the web. This dataset is released under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license. Please ensure you comply with the original licenses of the source…from huggingface.co
In the maker’s words, at launch
Introducing Open-Schematics: a large public dataset of electronic schematics with rendered images and structured metadata for ML, circuit understanding, retrieval, and validation.
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