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Comment by buildbot | Hacker News Reader

Does this support training on Apple silicon? It’s not very clear unless I missed something in the README.

Would such a capability (training) be useful for anything other than small scale experimentation? Apple doesn’t make server products anymore and even when they did, they were overpriced. Unless they have private Apple silicon based servers for their own training needs?

There are an insane number of Apple Silicon devices out there.

If your product runs on an iPhone or iPad, I’m sure this is great.

If you only ever want to run on 4090s or other server stuff, yeah this probably isn’t that interesting.

Maybe it’s a good design for the tools or something, I have no experience to know. Maybe someone else can build off it.

But it makes sense Apple is releasing tools to make stuff that works better on Apple platforms.

I can understand the inference part being useful and practical for Apple devs. I’m just wondering about the training part, for which there Apple silicon devices don’t seem very useful.

I’ve seen several people fine tune mistral 7B on MacBooks.

My M2 Max significantly outperforms my 3090 Ti for training a Mistral-7B LoRA. Its sort of a case-by-case situation though, as it depends on how optimized the CUDA kernels happen to be for whatever workload you're doing (i.e. for inference, theres a big delta between standard transformers vs exllamav2, apple silicon may outperform the former, but certainly not the latter).

Isn’t the current Mac Pro available in rack mount form?

https://www.apple.com/mac-pro/

> Unless they have private Apple silicon based servers for their own training needs?

Id be SHOCKED if so. Its been 15 years, but I was there when xserve died. Priorities were iphone > other mobile devices >>> laptops > displays & desktops >>> literally anything else. When xserve died we still needed osx for OD & similar. Teams moved on to 3P rack mount trays of mac minis as a stop gap. Any internal support/preference for server style hardware was a lolwut response. Externally I see no reason to suspect thats changed.

I believe the MLX examples allow for it. Seems like a general purpose framework rather than a Mac specific one.

I couldn't find any training code in the MXL examples.

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