This morning I ported the Moebius 0.2B image inpainting model to run in a browser using Claude Code. The tool is available at simonw.github.io/moebius-web/.
The finished tool
Here is a video demo of the finished tool:
You can open any image in it (non-square images get letterboxed), highlight areas to remove, click the “Run inpaint” button and wait for the model to do its magic.
A parallel agent side-project
My main project for today was landing a major feature in Datasette: a UI for creating and altering tables, as a follow-up to the insert and edit rows feature I released last week.
I was working on that in Codex Desktop (here’s the PR) and often found myself spending 5-10 minutes spinning my fingers waiting for it to complete a mid-sized refactor or add the finishing touches to a change to the UI.
(An amusing thing about coding agents is that the harder a problem is the more time you have to get distracted while you wait for them to finish crunching!)
So I decided to spin up Claude Code in a terminal window and see how far I could get at porting Moebius to the web.
Some agentic research to kick off the project
My first step was to ask regular Claude about the feasibility of this project. In Claude.ai, which has the ability to clone repos from GitHub:
Clone https://github.com/hustvl/Moebius/ and tell me if they published the code and weights to run this model anywhere
(I hadn’t spotted the link to the weights yet, that’s tucked away in the “News” section.)
Then:
For Moebius what are the options for running it right now - Python and NVIDIA CUDA only or other options too?
And:
Muse on the feasibility of porting it to Transformers.js or similar and running it in a browser
I like telling models to “muse on X”, it’s the shortest way I’ve found of expressing that I want them to contemplate a problem for me without providing them with a concrete goal.
Here’s that chat transcript. I copied out the last answer and saved it as research.md for Claude Code to read later.
Claude suggested using ONNX Runtime Web on the WebGPU backend – the layer below the Transformers.js library I had suggested.
That was enough to convince me it was worth setting Claude Code loose and seeing how far it could get.
I usually start projects like this by gathering as much information as the coding agent might need as possible. Since I didn’t expect this project to actually work I did everything in my /tmp folder:
cd /tmp
mkdir Moebius
cd Moebius
# Grab the Moebius python code
git clone https://github.com/hustvl/Moebius
# And the model weights (Claude figured this out):
GIT_LFS_SKIP_SMUDGE=0 git clone \
https://huggingface.co/hustvl/Moebius Moebius-weights
# Finally a couple of libraries we might use:
git clone https://github.com/huggingface/transformers.js
git clone https://github.com/microsoft/onnxruntimeSetting off Claude Code
I created a directory for the rest of the project and ran git init in that so Claude could start committing code notes:
mkdir /tmp/Moebius/moebius-web
cd /tmp/Moebius/moebius-web
git init
# Copy in that research.md from earlier
git add research.md
git commit -m "Initial research by Claude Opus 4.8"I fired up a claude instance in the /tmp/Moebius folder, the level above all of the research materials I had prepared for it. I prompted:
Read ./moebius-web/research.md - your goal is to port this model to ONNX and WebGPU so we can run it directly in a browser, with a simple UI
As it started to work I dropped in this follow-up (typos included):
Bulid this in /tmp/Moebius/moebius-web and commit early and often, also maintain a notes.md file in there with notes about what you figure out along the way - also start by writing out a plan.md in there and update that plan as oy work too
I often ask agents to keep notes like this – the end result is often interesting, both for myself and for the next agent session that touches the same project. Here’s what that notes.md file looked like at the end of the project.
I kicked it off and went back to my main project, checking in occasionally to see how Claude was doing. When it looked like it might have something that worked I prompted:
Tell me what URL I can visit in my own browser to try this
Then I tried it out in Chrome and pasted some errors (and screenshots of errors) back into Claude Code.
After a few rounds of this we had something that appeared to work! Time to put it on the internet so other people could use it.
How would we publish this to Hugging Face such that the model weights were on there and the HTML demo would show up in Hugging Face spaces?
Claude Code knows how to use the hf CLI tool, so I created a model repo on Hugging Face, then created a token that could write to that repo and dropped it into a /tmp/Moebius/token.txt file so Claude could use it.
It published the 1.24GB of converted ONNX weights to huggingface.co/simonw/Moebius-ONNX for me.
I’d seen other demos load weights into the browser from Hugging Face before, so I knew it was possible. I decided to host my own frontend code on GitHub Pages, so I said:
I want to publish the moebius-web folder to GitHub, minus the large files (so maybe minus the models/ folder), such that when I turn on GitHub Pages for that repo navigating to https://simonw.github.io/moebius-web/ serves the UI
Telling it the final URL was important in case it needed to fix the URLs in the demos that it was building so they would work when deployed to production.
After a few more rounds of iteration, in between working on my main project, we got to a working, deployed version!
Except… each time I reloaded the page it seemed to download ~1.3GB of model weights. Browser caching seemed pretty important for this!
anything clever we can do with serviceworkers or similar to help cache this stuff? It seems to reload every time, I am concerned that there might be something weird about the way HF redirects work that mean we don't benefit from browser caching
I knew that Transformers.js projects could handle this properly, so I grabbed a copy of the Whisper Web demo, dropped it into /tmp/Moebius/whisper-web and said:
look in /tmp/Moebius/whisper-web (with a subagent) and see how they do this
That project was entirely obfuscated, built JavaScript files so I figured using a subagent would avoid spending the rest of my top-level token context deciphering those files.
Claude figured out that it was using caches.open("transformers-cache") – the CacheStorage API – and Source Read original →
