Docker model run is now part of my demos when deploying ml stack stuff, pretty sure that this is removing the entrypoint of using multiple tools to just do inference, this is great!
This allowed me to change from pyenv, node and everything into a something really neat and simple, the only thing it caught my surprise was `mise trust` but then the CLI help me to understand, Thanks jdxcode!
Wow. It seems to save a lot of boilerplate code for ETL.
Docker model run is now part of my demos when deploying ml stack stuff, pretty sure that this is removing the entrypoint of using multiple tools to just do inference, this is great!
This allowed me to change from pyenv, node and everything into a something really neat and simple, the only thing it caught my surprise was `mise trust` but then the CLI help me to understand, Thanks jdxcode!
Wow. It seems to save a lot of boilerplate code for ETL.