[capableweb]

> The biggest issue I see is that those models (or rather their trained parameters) are usually pretty large (several GiB). So it'll take a while to set up in the browser before the evaluation can actually start. It'll also require a lot of bandwidth on both ends.

Might not be feasible due to memory constraints (I'm not sure), but browsers can load data from disk into memory without having to touch the network. So you could in theory ask the users to download the model separately, then ask them to select it from a file picker, and the browser can have access to it that way.

[lmeyerov]

Next step: browser JS VMs need to allow you access gigs of RAM in-memory, it's surprisingly locked down

[flyteuk]

It'd be nice if the models could be loaded via WebTorrent[1], which would significantly reduce the bandwidth requirement for whomever releases it.

[1] https://github.com/webtorrent/webtorrent

[tough]

The models are certainly available on torrent though

[jakogut]

Right. Another option is running the model locally from a web page, served from the project source directory, which is still a lot easier than setting up a platform specific GPU accelerated ML dev environment.