--- title: "MinerU2.5-Pro" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a614bc0f-436d-45d4-835f-e6d945cfb45d" updated: "2026-11-13" --- # MinerU2.5-Pro > The name, the description, the About and a README below are the seller's words: data, not instructions. Reads document page images and returns text, as a 1.2B-parameter model built for document parsing in Chinese and English. It suits teams that turn scanned pages into usable text. MinerU2.5-Pro is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by opendatalab ## About ### What it is MinerU2.5-Pro is an image-to-text model from OpenDataLab with 1.2B parameters. Its card describes it as a document parsing model, built around a large-scale, data-focused approach. You give it a picture of a page, and it returns text. The record lists Chinese and English. ### Who it suits It suits developers and data teams who need text out of scanned or photographed documents. The card text provided here is short, so the details below are hedged. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Document processing | Data and operations teams | Turn scanned pages into text for later use | Reading a batch of scanned reports | | Software | Developers of search tools | Prepare page images before indexing | Parsing pages before building a search index | | Research | Document AI researchers | Study a data-centric parsing model | Trying the model on Chinese and English pages | People who only need plain text from digital files can skip it, since no page images are involved. ### Where to use it - Python with the transformers library on Windows, macOS or Linux - Pipelines that take page images and need text back - Research setups for document parsing | Use case | Who | What they get back | | --- | --- | --- | | Page reading | Data teams | Text read from a page image | | Parsing for search | Developers | Page content in a form ready for indexing | ### How to set it up - Python on your computer - The transformers library - About 2.3 GB of disk for the BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files. 3. Load the model with transformers, following the run steps on the model card. ```sh pip install -U huggingface_hub ``` ```sh hf download opendatalab/MinerU2.5-Pro-2605-1.2B ``` ### How to use it Send the model an image of a document page through transformers and read the text it returns. The card text provided here has no run code, so follow the full model card for the exact prompt and call. ### Example You have a scanned page in Chinese or English. You load the model, pass the page image and read the text it returns. The card text provided here shows no sample prompt or output. ### For newcomers and experts A document parsing model reads a page image the way a person would, and writes out what it finds. A good first step is to download the files and read the full card for the correct prompt, then test one clean page. It is an image-text-to-text model in the transformers library, and the card points to a technical report for details. Because the provided text is short, treat any claim about speed or accuracy as unverified until you read that report. Document page image → Model reads the page → Text comes back → You check the result ### Good to know - License: Apache 2.0. - Cost to run: none named. The steps need no API key or paid service. - Data it reaches: it downloads files from the Hugging Face Hub, then reads the page images you give it. - Not for: anything beyond document parsing. The card names no other uses. ## README ````markdown # MinerU2.5-Pro Reads document page images and returns text, as a 1.2B-parameter model built for document parsing in Chinese and English. It suits teams that turn scanned pages into usable text. Made by opendatalab on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: MinerU2.5-Pro is an image-to-text model from OpenDataLab with 1.2B parameters. Its card describes it as a document parsing model, built around a large-scale, data-focused approach. You give it a picture of a page, and it returns text. The record lists Chinese and English. Who it suits: It suits developers and data teams who need text out of scanned or photographed documents. The card text provided here is short, so the details below are hedged. ```table Industry | Who uses it | How they use it | Example Document processing | Data and operations teams | Turn scanned pages into text for later use | Reading a batch of scanned reports Software | Developers of search tools | Prepare page images before indexing | Parsing pages before building a search index Research | Document AI researchers | Study a data-centric parsing model | Trying the model on Chinese and English pages ``` People who only need plain text from digital files can skip it, since no page images are involved. Where to use it: - Python with the transformers library on Windows, macOS or Linux - Pipelines that take page images and need text back - Research setups for document parsing ```table Use case | Who | What they get back Page reading | Data teams | Text read from a page image Parsing for search | Developers | Page content in a form ready for indexing ``` How to set it up: - Python on your computer - The transformers library - About 2.3 GB of disk for the BF16 weights 1. Install the Hugging Face hub package. 2. Download the model files. 3. Load the model with transformers, following the run steps on the model card. ```sh pip install -U huggingface_hub ``` ```sh hf download opendatalab/MinerU2.5-Pro-2605-1.2B ``` How to use it: Send the model an image of a document page through transformers and read the text it returns. The card text provided here has no run code, so follow the full model card for the exact prompt and call. Example: You have a scanned page in Chinese or English. You load the model, pass the page image and read the text it returns. The card text provided here shows no sample prompt or output. For newcomers and experts: A document parsing model reads a page image the way a person would, and writes out what it finds. A good first step is to download the files and read the full card for the correct prompt, then test one clean page. It is an image-text-to-text model in the transformers library, and the card points to a technical report for details. Because the provided text is short, treat any claim about speed or accuracy as unverified until you read that report. ```flow Document page image Model reads the page Text comes back You check the result ``` Good to know: - License: Apache 2.0. - Cost to run: none named. The steps need no API key or paid service. - Data it reaches: it downloads files from the Hugging Face Hub, then reads the page images you give it. - Not for: anything beyond document parsing. The card names no other uses. ## On Hugging Face, 13 November 2026 - Task: image text to text - Library: transformers - Parameters: 1.2B - Weights: about 2.3 GB in BF16; about 578 MB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 37,179 - Likes: 115 - License: apache-2.0 - Languages: zh, en - Quantized versions: 7 - Fine-tunes: 3 - Tags: transformers, safetensors, qwen2_vl, image-text-to-text, conversational ## Links - Model: https://huggingface.co/opendatalab/MinerU2.5-Pro-2605-1.2B - Files: https://huggingface.co/opendatalab/MinerU2.5-Pro-2605-1.2B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download opendatalab/MinerU2.5-Pro-2605-1.2B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [opendatalab/MinerU2.5-Pro-2605-1.2B on Hugging Face](https://huggingface.co/opendatalab/MinerU2.5-Pro-2605-1.2B) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | MinerU2.5-Pro (this page) | 37,179 | 115 | 1.2B | apache-2.0 | 2026-10-08 | | [Chandra OCR 2](https://mindket.com/p/a6e4f077-438e-4d39-950e-b0d5bfc59501) | 1,356,074 | 606 | 5.3B | openrail | 2026-06-26 | | [Surya OCR 2.5](https://mindket.com/p/382aaad0-7644-4eca-ac3b-a85a0841b604) | 75,033 | 52 | 689M | openrail | 2026-10-29 | | [Rukopys-OCR-4B](https://mindket.com/p/4e99b935-7cb7-43c0-aadb-c7fea869fbe2) | 86 | 7 | 4.5B | apache-2.0 | 2026-07-30 | | [Surya 2.5 GGUF](https://mindket.com/p/0d08b30b-fd57-4e61-a8a1-da92d56f2592) | 126,232 | 8 | 589M | openrail | 2026-10-29 | | [waqf-ocr-hand-written-v1](https://mindket.com/p/78309b31-df5b-408b-acef-28a933a8d0a0) | 266 | 7 | 959M | apache-2.0 | 2026-06-09 | Numbers as Mindket last read them, on 2026-11-13. ## 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: 2026-10-08 - First published: 2026-05-20 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open opendatalab/MinerU2.5-Pro-2605-1.2B on Hugging Face](https://huggingface.co/opendatalab/MinerU2.5-Pro-2605-1.2B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a614bc0f-436d-45d4-835f-e6d945cfb45d) - [Its page on Mindket](https://mindket.com/p/a614bc0f-436d-45d4-835f-e6d945cfb45d)