Mindket

Colpali

Newversion 1 · updated

Overview

A Gradio demo of the vidore ColPali v1.3 model, shipped with a stored file of page embeddings. For developers and researchers trying out visual document retrieval in the browser on Hugging Face.

Colpali is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Nothing at all if you only use the online Space
  • Python 3.12 and pip, for a local copy
  • The Python packages listed in requirements.txt
Runs in
  • A web browser, on the Space's page at Hugging Face
  • Your own computer, as a local copy, once Python 3.12 is installed
Start with
pip install -U huggingface_hub
hf download rayyan0/colpali --repo-type space --local-dir colpali
cd colpali

About

What it is

This is a Gradio demo built around the vidore colpali-v1.3-hf model. Its repository ships a file of stored embeddings named pages_embeddings.pt, which suggests the app matches a query against pre-computed page data. The README is empty, so the page itself says little more. It runs on zero-a10g hardware at Hugging Face.

Who it suits

Developers and researchers who want to try the ColPali model on documents without setting it up, and anyone who wants a small example of how it is wrapped in an app.

IndustryWho uses itHow they use itExample
ResearchRetrieval researchersTry the model on stored page embeddingsRun a few queries and inspect what matches
SoftwareDevelopersRead app.py to see how the model and embeddings are loadedReuse the layout for their own document search
EducationStudentsLearn how document retrieval demos are builtChange a query and watch the results change

Skip it if you need to search your own files, since the page mentions only a bundled embeddings file.

Where to use it

  • A web browser, on the Space's page at Hugging Face
  • Your own computer, as a local copy, once Python 3.12 is installed
Use caseWhoWhat they get back
Try the modelResearchersResults from the ColPali model in a web form
Study the demoDevelopersA short Gradio app and an embeddings file to read

How to set it up

  • Nothing at all if you only use the online Space
  • Python 3.12 and pip, for a local copy
  • The Python packages listed in requirements.txt
  1. Open the Space's page at Hugging Face to use it online.
  2. For a local copy, install the Hugging Face hub package and download the Space.
  3. Move into the new folder and install Gradio at the pinned version.
  4. Install the packages from requirements.txt.
  5. Start the app with Python.
pip install -U huggingface_hub
hf download rayyan0/colpali --repo-type space --local-dir colpali
cd colpali
pip install gradio==6.31.0
pip install -r requirements.txt
python app.py

The repository has five files, including app.py, requirements.txt and the embeddings file. The page does not say what a local run needs beyond the packages.

How to use it

Online, open the Space and use the form on its page. On your own machine, run the app file and open the page Gradio serves in your browser. The page lists no other commands.

ToolWhat it does
python app.pyStarts the Gradio app on your computer

Example

You open the Space and type a short question into its form. The app runs the model against its stored page data and shows what it finds, which you can read to see how well the match fits your question.

For newcomers and experts

If you are new, open the Space online and try one short question. The README is empty, so treat what you see on the page as the guide.

If you know the field, the stored pages_embeddings.pt file points to retrieval over pre-computed page vectors rather than live indexing. The page gives no corpus, no scoring details and no instructions for adding your own pages.

  1. Open the Space in a browser
  2. Type a query
  3. The ColPali model compares it with stored pages
  4. The matches are shown

Good to know

  • License: mit
  • Cost to run: none named, though the Space runs on zero-a10g hardware at Hugging Face
  • Data it reaches: your query, the bundled embeddings file, and the model files from Hugging Face
  • Not for: searching your own documents, since the page does not describe a way to add them

README and files

README

Colpali

A Gradio demo of the vidore ColPali v1.3 model, shipped with a stored file of page embeddings. For developers and researchers trying out visual document retrieval in the browser on Hugging Face.

Made by rayyan0 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 is a Gradio demo built around the vidore colpali-v1.3-hf model. Its repository ships a file of stored embeddings named pages_embeddings.pt, which suggests the app matches a query against pre-computed page data. The README is empty, so the page itself says little more. It runs on zero-a10g hardware at Hugging Face.

Who it suits: Developers and researchers who want to try the ColPali model on documents without setting it up, and anyone who wants a small example of how it is wrapped in an app.

Industry | Who uses it | How they use it | Example
Research | Retrieval researchers | Try the model on stored page embeddings | Run a few queries and inspect what matches
Software | Developers | Read app.py to see how the model and embeddings are loaded | Reuse the layout for their own document search
Education | Students | Learn how document retrieval demos are built | Change a query and watch the results change

Skip it if you need to search your own files, since the page mentions only a bundled embeddings file.

Where to use it:

  • A web browser, on the Space's page at Hugging Face
  • Your own computer, as a local copy, once Python 3.12 is installed
Use case | Who | What they get back
Try the model | Researchers | Results from the ColPali model in a web form
Study the demo | Developers | A short Gradio app and an embeddings file to read

How to set it up:

  • Nothing at all if you only use the online Space
  • Python 3.12 and pip, for a local copy
  • The Python packages listed in requirements.txt
  1. Open the Space's page at Hugging Face to use it online.
  2. For a local copy, install the Hugging Face hub package and download the Space.
  3. Move into the new folder and install Gradio at the pinned version.
  4. Install the packages from requirements.txt.
  5. Start the app with Python.
pip install -U huggingface_hub
hf download rayyan0/colpali --repo-type space --local-dir colpali
cd colpali
pip install gradio==6.31.0
pip install -r requirements.txt
python app.py

The repository has five files, including app.py, requirements.txt and the embeddings file. The page does not say what a local run needs beyond the packages.

How to use it: Online, open the Space and use the form on its page. On your own machine, run the app file and open the page Gradio serves in your browser. The page lists no other commands.

Tool | What it does
python app.py | Starts the Gradio app on your computer

Example: You open the Space and type a short question into its form. The app runs the model against its stored page data and shows what it finds, which you can read to see how well the match fits your question.

For newcomers and experts: If you are new, open the Space online and try one short question. The README is empty, so treat what you see on the page as the guide.

If you know the field, the stored pages_embeddings.pt file points to retrieval over pre-computed page vectors rather than live indexing. The page gives no corpus, no scoring details and no instructions for adding your own pages.

Open the Space in a browser
Type a query
The ColPali model compares it with stored pages
The matches are shown

Good to know:

  • License: mit
  • Cost to run: none named, though the Space runs on zero-a10g hardware at Hugging Face
  • Data it reaches: your query, the bundled embeddings file, and the model files from Hugging Face
  • Not for: searching your own documents, since the page does not describe a way to add them

On Hugging Face, 13 November 2026

  • Likes: 1
  • Built with: gradio
  • License: mit

Links

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.

Files
README.md  4 KB

1 file, 4 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
Colpali This page1gradiomit
Open VLM LeaderboardShares gradio1,034gradioapache-2.0
Face SwapShares gradio808gradiocc-by-nc-sa-4.0
TTS Spaces ArenaShares gradio493gradiozlib
Depth Anything 3Shares gradio490gradiocc-by-nc-4.0
BLIPShares gradio431gradiobsd-3-clause
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

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