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Comment by dvt

19 days ago

Ah true, missed that! Still a bit cumbersome & lazy imo, I'm a fan of just shipping with that capability out-of-the-box (Huggingface's Candle is fantastic for downloading/syncing/running models locally).

In local setup you still usually want to split machine that runs inference from client that uses it, there are often non trivial resources used like chromium, compilation, databases etc involved that you don’t want to pollute inference machine with.

Ah come on, lazy? As long as it works with the runtime you wanna use, instead of hardcoding their own solution, should work fine. If you want to use Candle and have to implement new architectures with it to be able to use it, you still can, just expose it over HTTP.

  • I think one of the major problems with the current incarnation of AI solutions is that they're extremely brittle and hacked-together. It's a fun exciting time, especially for us technical people, but normies just want stuff to "work."

    Even copy-pasting an API key is probably too much of a hurdle for regular folks, let alone running a local ollama server in a Docker container.

    • Unlike in image/video gen, at least with LLMs the "best" solution available isn’t a graph/node-based interface with an ecosystem of hundreds of hacky undocumented custom nodes that break every few days and way too complex workflows made up of a spaghetti of two dozen nodes with numerous parameters each, half of which have no discernible effect on output quality and tweaking the rest is entirely trial and error.

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    • > but normies just want stuff to "work."

      Where in the world are you getting that this project is for "normies"? Installation steps are terminal instructions and it's a CLI, clearly meant for technical people already.

      If you think copying-pasting an API key is too much, don't you think cloning a git repository, installing the Rust compiler and compiling the project might be too much and hit those normies in the face sooner than the API key?