At my current job I've started caching all of our LFS objects in a bucket, for cost reasons. Every time a PR is run, I get the list of objects via `git lfs ls-files`, sync them from gcp, run `git lfs checkout` to actually populate the repo from the object store, and then `git lfs pull` to pick up anything not cached. If there were uncached objects, I push them back up via `gcloud storage rsync`. Simple, doesn't require any configuration for developers (who only ever have to pull new objects), keeps the Github UI unconfused about the state of the repo.

I'd initially at spinning up an LFS backends, but this solves the main pain point, for now. Github was charging us an arm and a leg for pulling LFS files for CI, because each checkout is fresh, the caching model is non-ideal (max 10GB cache, impossible to share between branches), so we end up pulling a bunch of data that is unfortunately in LFS, every commit, possibly multiple times. Because of this they happily charge us for all that bandwidth, because they don't provide tools to make it easy to reduce bandwidth (let me pay for more cache size, or warm workers with an entire cache disc, or better cache control, or...).

...and if I want to enable this for developers it's relatively easy, just add a new git hook to do the same set of operations locally.