| ▲ | mft_ 10 hours ago | |||||||||||||
I have a Mac with 4TB of storage but it’s still annoying when every new AI app I try installs its own virtual environment with a fresh copy of Python, PyTorch, other duplicate libraries, and then models on top of that. | ||||||||||||||
| ▲ | DrScientist 9 hours ago | parent | next [-] | |||||||||||||
As an occasional python user I'm always amazed and frustrated that it seems that the only way to be able to use/build anything is to create a whole separate environment. And now given everybody now does this I guess the incentive to stop breaking stuff reduces even further. Might as well have static binaries. | ||||||||||||||
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| ▲ | whstl 8 hours ago | parent | prev | next [-] | |||||||||||||
I have a couple small apps that have a (non-LLM) model, and originally the models and code were in PyTorch, built by Python devs. The original plan was to ship Python. However I found out I can migrate them to CoreML, and now it's a model file + Swift code. I got some massive performance improvements as well. Of course, this doesn't work at all for non-Mac environments, but it was nice to be able to do it. (Also doesn't solve the duplicate large models problem) | ||||||||||||||
| ▲ | hedora 4 hours ago | parent | prev | next [-] | |||||||||||||
It’d be nice if there was a standard like ~/.local/llm/hugging-face-name.gguf or something. Python heaviness is a more fundamental problem. | ||||||||||||||
| ▲ | ac29 5 hours ago | parent | prev [-] | |||||||||||||
If you use uv, python apps use a shared cache which helps a lot. | ||||||||||||||