6 items tagged “webgpu”
2024
llama-3.2-webgpu (via) Llama 3.2 1B is a really interesting models, given its 128,000 token input and its tiny size (barely more than a GB).
This page loads a 1.24GB q4f16 ONNX build of the Llama-3.2-1B-Instruct model and runs it with a React-powered chat interface directly in the browser, using Transformers.js and WebGPU. Source code for the demo is here.
It worked for me just now in Chrome; in Firefox and Safari I got a “WebGPU is not supported by this browser” error message.
[On WebGPU in Firefox] There is a lot of work to do still to make sure we comply with the spec. in a way that's acceptable to ship in a browser. We're 90% of the way there in terms of functionality, but the last 10% of fixing up spec. changes in the last few years + being significantly more resourced-constrained (we have 3 full-time folks, Chrome has/had an order of magnitude more humans working on WebGPU) means we've got our work cut out for us. We're hoping to ship sometime in the next year, but I won't make promises here.
experimental-phi3-webgpu (via) Run Microsoft’s excellent Phi-3 model directly in your browser, using WebGPU so didn’t work in Firefox for me, just in Chrome.
It fetches around 2.1GB of data into the browser cache on first run, but then gave me decent quality responses to my prompts running at an impressive 21 tokens a second (M2, 64GB).
I think Phi-3 is the highest quality model of this size, so it’s a really good fit for running in a browser like this.
2023
WebLLM supports Llama 2 70B now. The WebLLM project from MLC uses WebGPU to run large language models entirely in the browser. They recently added support for Llama 2, including Llama 2 70B, the largest and most powerful model in that family.
To my astonishment, this worked! I used a M2 Mac with 64GB of RAM and Chrome Canary and it downloaded many GBs of data... but it worked, and spat out tokens at a slow but respectable rate of 3.25 tokens/second.
MLC: Bringing Open Large Language Models to Consumer Devices (via) “We bring RedPajama, a permissive open language model to WebGPU, iOS, GPUs, and various other platforms.” I managed to get this running on my Mac (see via link) with a few tweaks to their official instructions.
Web Stable Diffusion (via) I just ran the full Stable Diffusion image generation model entirely in my browser, and used it to generate an image (of two raccoons eating pie in the woods, see “via” link). I had to use Google Chrome Canary since this depends on WebGPU which still isn’t fully rolled out, but it worked perfectly.