LocalLLaMA

2261 readers

1 users here now

Community to discuss about LLaMA, the large language model created by Meta AI.

This is intended to be a replacement for r/LocalLLaMA on Reddit.

founded 1 year ago

MODERATORS

[email protected]

Hello World (sh.itjust.works)

submitted 1 year ago by [email protected] to c/[email protected]

11 comments fedilink hide all child comments

Hi, you've found this ~~subreddit~~ Community, welcome!

This Community is intended to be a replacement for r/LocalLLaMA, because I think that we need to move beyond centralized Reddit in general (although obviously also the API thing).

I will moderate this Community for now, but if you want to help, you are very welcome, just contact me!

I will mirror or rewrite posts from r/LocalLLama for this Community for now, but maybe we could eventually all move to this Community (or any Community on Lemmy, seriously, I don't care about being mod or "owning" it).

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 1 points 1 year ago* (last edited 1 year ago) (1 children)

Hi, sure, thank you so much for helping out! As for LLaMA, I would point you at llama.cpp, (https://github.com/ggerganov/llama.cpp) which is the absolute bleeding edge, but also has pretty useful instructions on the page (https://github.com/ggerganov/llama.cpp#usage). You could also use Kobold.cpp, but I don't have any experience with it, so I can't help you if you have issues.

[–] gh0stcassette 2 points 1 year ago

Adding to this: text-generation-webui (https://github.com/oobabooga/text-generation-webui) works with the latest bleeding edge llama.cpp via llama-cpp-python, and it has a nice graphical front-end. You do have a manually tell pip to install llama.cpp-python with the right compiler flags to get GPU acceleration working but the llama-cpp-python github and ooba github explain how to do this.

You can even set up GPU acceleration through metal on m1 Macs I've seen some fucking INSANE performance numbers online for the higher RAM MacBook pros (20+ tokens/sec, I think with a 33b model, but it might have been 13b, either way, impressive.)