We recently released Smaug-72B-v0.1 which has taken first place on the Open LLM Leaderboard by HuggingFace. It is the first open-source model to have an average score more than 80.
Unfortunately LLMs need a lot of VRAM. You could try using koboldcpp, it runs on the CPU but let’s you offload layers onto the GPU. That way you might be able to stay withing those 4gb even with larger models.
Edit: I forgot to mention there’s a fork of koboldcpp with rocm for AMD cards, which is about twice as fast if I remember correctly. Only relevant if you have an AMD card tho.
Edit 2: This is the model I use btw
I’m currently playing around with the Jan client, which uses the nitro engine. I think I need to read up on it more, because when I set the ngl value to 15 in order to offload 50% to GPU like the Jan guide says, nothing happens. Though that could be an issue specific to Jan.
Maybe 50% GPU is already using too much VRAM and it crashes. You could try to set it to 0% GPU and see if that works.
I may need to lower it a bit more, yeah. Though when I try to to use offloading, I can see that vram usage doesn’t increase at all.
When I leave the setting at its default 100 value on the other hand, I see vram usage climb until it stops because there isn’t enough of it.
So I guess not all models support offloading?
