[JimDabell]

What do you mean? Deploying something like spaCy is far easier than deploying an LLM in my experience.

[t-writescode]

By "deploy", they almost certainly mean "set up to use" and they may have also included "learn how to use" and all its various forms, as well.

LLMs really are almost magic in how they can help in this space; and setting them up is often just getting an API key and throwing some money and webservice calls at them.

[JimDabell]

Set up to use, sure. Learn? Learning isn’t deployment in this context.

Setting up spaCy is just `pip install spacy`. No need to worry about GPUs or dedicated services like you do with LLMs.

[throwawaymaths]

yeah, then you have to learn the API. Basically every option for running LLMs have converged on the openAI (web) API.

[JimDabell]

“Learning the API” is not deployment.

[throwawaymaths]

pip install vllm, boom you have an openapi-compatible webserver. No further action necessary.

[JimDabell]

No, there is further action necessary. If you want any kind of decent performance, you need to run it with an appropriate GPU. This is not true of spaCy, which makes spaCy easier to deploy.