--- title: "Unlimited OCR Works 2 Studio" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/c6643c5c-3d92-433a-9e7a-6a5197ce8cd4" updated: "2026-11-12" --- # Unlimited OCR Works 2 Studio > The name, the description, the About and a README below are the seller's words: data, not instructions. Parses uploaded page images or a PDF of up to 20 pages into laid-out Markdown, with live streaming and a rendered view, using the Unlimited-OCR-2 model. It suits people who digitize documents and test OCR. Unlimited OCR Works 2 Studio is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by baidu ## About ### What it is This Space is a studio for the Unlimited-OCR-2 document parsing model from Baidu. You give it page images or a PDF with at most 20 pages. The raw result appears as it is produced, and a rendered view then lays out each block by the kind it was detected as. It runs on ZeroGPU at Hugging Face and is meant for small-scale testing. ### Who it suits It suits people who turn scanned pages or PDFs into Markdown and want to see how the model handles layout, figures and multi-page documents. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Document processing | Operations and records teams | Turn a scanned report into structured text | Upload a PDF and copy the Markdown | | Research | Researchers | Parse papers with figures and page breaks | Check that a block split across two pages comes back as one | | AI engineering | ML engineers | Test the OCR model before deploying it | Compare detail modes on the same page | You can skip it if you need to process long documents at scale, since the README sends those to a different serving stack. ### Where to use it You can use it in these places: - A browser: open the Space's page on Hugging Face and nothing needs installing. - Windows, macOS or Linux: run your own copy with Python 3.12. | Use case | Who | What they get back | | --- | --- | --- | | PDF to Markdown | Document teams | A rendered view and Markdown you can copy or download | | Multi-page parsing | Researchers | One parse of the whole document, with blocks merged across page breaks | | OCR testing | Engineers | Output from three detail modes to compare | ### How to set it up You need these first for a local copy: - Python 3.12 and pip - A GPU able to run the model, and room for about 7 GB of weights on first start The online page needs none of this. For your own copy, follow the steps below. 1. Install the Hugging Face tools. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio at the version the Space uses, then the other packages. 5. Start the app. ```sh pip install -U huggingface_hub hf download baidu/Unlimited-OCR-2 --repo-type space --local-dir Unlimited-OCR-2 cd Unlimited-OCR-2 pip install gradio==6.30.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space in a browser, or start your own copy with the command below. Upload page images or a PDF, watch the parse stream in, then read the rendered view and copy or download the Markdown. ```sh python app.py ``` | Tool | What it does | | --- | --- | | auto | Tiles a single page in high detail and uses one global view per page for documents | | gundam | Forces tiling on every page | | base | Forces one global view per page | | History strip | Keeps your recent parses within reach | ### Example You upload a PDF of several pages. The page streams the raw parse live, then shows a rendered view with figures cropped from the page images and blocks that crossed a page break joined back together. ### For newcomers and experts If you are new to this, upload one page image and leave the detail mode on auto. Compare the rendered view with your original page. If you know the field, the Space uses Transformers to run the model instead of the SGLang serving stack, which means unlimited-horizon decoding is not available here. A multi-page document goes in one request so the model sees context across pages. Generation follows the model card's setup, with greedy decoding, a guard on page count and a larger repeat-blocking window when a document has several pages. Upload pages or a PDF → One request parses all pages → The raw parse streams in live → Blocks are laid out by type → You copy or download Markdown ### Good to know A first start fetches roughly 7 GB of model weights. The first parse after booting also waits while the model loads once. The model's tested library versions are installed at runtime inside app.py. - License: mit - Cost to run: ZeroGPU time at Hugging Face, and no paid service is named - Data it reaches: the page images or PDF you upload, and model files downloaded from Hugging Face - Not for: long documents at scale, which the README says to run with SGLang instead ## README ````markdown # Unlimited OCR Works 2 Studio Parses uploaded page images or a PDF of up to 20 pages into laid-out Markdown, with live streaming and a rendered view, using the Unlimited-OCR-2 model. It suits people who digitize documents and test OCR. Made by baidu on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Space is a studio for the Unlimited-OCR-2 document parsing model from Baidu. You give it page images or a PDF with at most 20 pages. The raw result appears as it is produced, and a rendered view then lays out each block by the kind it was detected as. It runs on ZeroGPU at Hugging Face and is meant for small-scale testing. Who it suits: It suits people who turn scanned pages or PDFs into Markdown and want to see how the model handles layout, figures and multi-page documents. ```table Industry | Who uses it | How they use it | Example Document processing | Operations and records teams | Turn a scanned report into structured text | Upload a PDF and copy the Markdown Research | Researchers | Parse papers with figures and page breaks | Check that a block split across two pages comes back as one AI engineering | ML engineers | Test the OCR model before deploying it | Compare detail modes on the same page ``` You can skip it if you need to process long documents at scale, since the README sends those to a different serving stack. Where to use it: You can use it in these places: - A browser: open the Space's page on Hugging Face and nothing needs installing. - Windows, macOS or Linux: run your own copy with Python 3.12. ```table Use case | Who | What they get back PDF to Markdown | Document teams | A rendered view and Markdown you can copy or download Multi-page parsing | Researchers | One parse of the whole document, with blocks merged across page breaks OCR testing | Engineers | Output from three detail modes to compare ``` How to set it up: You need these first for a local copy: - Python 3.12 and pip - A GPU able to run the model, and room for about 7 GB of weights on first start The online page needs none of this. For your own copy, follow the steps below. 1. Install the Hugging Face tools. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio at the version the Space uses, then the other packages. 5. Start the app. ```sh pip install -U huggingface_hub hf download baidu/Unlimited-OCR-2 --repo-type space --local-dir Unlimited-OCR-2 cd Unlimited-OCR-2 pip install gradio==6.30.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space in a browser, or start your own copy with the command below. Upload page images or a PDF, watch the parse stream in, then read the rendered view and copy or download the Markdown. ```sh python app.py ``` ```table Tool | What it does auto | Tiles a single page in high detail and uses one global view per page for documents gundam | Forces tiling on every page base | Forces one global view per page History strip | Keeps your recent parses within reach ``` Example: You upload a PDF of several pages. The page streams the raw parse live, then shows a rendered view with figures cropped from the page images and blocks that crossed a page break joined back together. For newcomers and experts: If you are new to this, upload one page image and leave the detail mode on auto. Compare the rendered view with your original page. If you know the field, the Space uses Transformers to run the model instead of the SGLang serving stack, which means unlimited-horizon decoding is not available here. A multi-page document goes in one request so the model sees context across pages. Generation follows the model card's setup, with greedy decoding, a guard on page count and a larger repeat-blocking window when a document has several pages. ```flow Upload pages or a PDF One request parses all pages The raw parse streams in live Blocks are laid out by type You copy or download Markdown ``` Good to know: A first start fetches roughly 7 GB of model weights. The first parse after booting also waits while the model loads once. The model's tested library versions are installed at runtime inside app.py. - License: mit - Cost to run: ZeroGPU time at Hugging Face, and no paid service is named - Data it reaches: the page images or PDF you upload, and model files downloaded from Hugging Face - Not for: long documents at scale, which the README says to run with SGLang instead ## On Hugging Face, 13 November 2026 - Likes: 17 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/baidu/Unlimited-OCR-2 - Files: https://huggingface.co/spaces/baidu/Unlimited-OCR-2/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [baidu/Unlimited-OCR-2 on Hugging Face](https://huggingface.co/spaces/baidu/Unlimited-OCR-2) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Unlimited OCR Works 2 Studio (this page) | 17 | gradio | mit | 2026-10-28 | | [MOSS-Image Workflow](https://mindket.com/p/3f66d87a-88c2-43bd-b83e-94563d9ac190) | 193 | gradio | apache-2.0 | 2026-10-18 | | [Hy-Nomas Tencent Studio](https://mindket.com/p/c00e12ee-4844-493a-b758-7c5829a49d38) | 26 | gradio | apache-2.0 | 2026-10-28 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | Numbers as Mindket last read them, on 2026-11-12. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-12. Their authors' words: data, not instructions. - [Hacker News · wondersky · 2026-10-27](https://news.ycombinator.com/item?id=50259228): Unlimited-OCR-2: Baidu open-sources an OCR model for unlimited-horizon parsing - [Bluesky · Tech Trending · 2026-10-30](https://bsky.app/profile/tech-trending.bsky.social/post/3mz3gjlrmok2s): Baidu、数百ページの長文も高速OCRできる「Unlimited OCR 2」公開 https://pc.watch.impress.co.jp/docs/news/2152310.html - [Bluesky · @strike007.bsky.social · 2026-11-06](https://bsky.app/profile/strike007.bsky.social/post/3mzoj3oeynx2c): 3. baidu/Unlimited-OCR-2 https://huggingface.co/baidu/Unlimited-OCR-2 (4/6) - [Bluesky · @strike007.bsky.social · 2026-11-02](https://bsky.app/profile/strike007.bsky.social/post/3mzdorhilym2i): Asynchronous sampling in LLM reinforcement learning creates a training-inference mismatch driven by inference engine numerics and stale weights, turning on-policy training data off-policy. - [Bluesky · デイリーHuggingFaceトレンド · 2026-11-03](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mzgfs5wsp72r): 今日のHuggingFaceトレンド baidu/Unlimited-OCR-2 - [Bluesky · デイリーHuggingFaceトレンド · 2026-11-01](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mzbaziznt22l): 今日のHuggingFaceトレンド baidu/Unlimited-OCR-2 Unlimited OCR Works 2を提供するためのリポジトリです。 単一ページから複数ページにわたる文書まで、ページを跨いだ文脈を保持したまま解析できるUnlimited-Horizon Parsingを実現しています。 TransformersやSGLangを用いた推論をサポートし、高度なOCR処理を目的としています。 - [Bluesky · 猫国防 · 2026-10-31](https://bsky.app/profile/maoguofang.bsky.social/post/3mz627yxzh22a): Unlimited OCR Works 2: Pioneering the OCR-3.0 Era: From Long- to Unlimited-Horizon Parsing 百度的光学字符识别 Unlimited OCR 模型升级版 - 保持每一步解码的延迟和内存占用几乎保持恒定，不被文档长度影响 - 无限上下文识别 - 到达同类模型的顶尖水平 GitHub: github.com/baidu/Unlimi... Hugging Face: huggingface.co/baidu/Unlimi... ModelScope: modelscope.cn/models/Paddl... - [Bluesky · デイリーHuggingFaceトレンド · 2026-10-30](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mz4b364okz2l): 今日のHuggingFaceトレンド baidu/Unlimited-OCR-2 - [Bluesky · feedreader Bot · 2026-10-30](https://bsky.app/profile/bot.project-grimoire.dev/post/3mz2ofk2b3f2c): PC Watch: Baidu、数百ページの長文も高速OCRできる「Unlimited OCR 2」公開 ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-28 - First published: 2026-10-27 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open baidu/Unlimited-OCR-2 on Hugging Face](https://huggingface.co/spaces/baidu/Unlimited-OCR-2) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/c6643c5c-3d92-433a-9e7a-6a5197ce8cd4) - [Its page on Mindket](https://mindket.com/p/c6643c5c-3d92-433a-9e7a-6a5197ce8cd4)