Found out about air_llm, https://github.com/lyogavin/Anima/tree/main/air_llm, where it loads one layer at a time, allow each layer to be 1.6GB for a 70b with 80 layers. theres about 30mb for kv cache, and i’m not sure where the rest goes.
works with HF out of the box too apparently. The weaknesses appear to be ctxlen, and its gonna be slow, but anyway, anyone want to try goliath 120B unquant?
If we can fit 1 layer at a time, can we do 3 or 4 at a time? A bit bigger but a bit faster than 1 at a time. Or am I dreaming?
That doesn’t make much of a difference. You still have to transfer the whole model to the GPU for ever single inference step. The GPU only saves you time if you can load the model (or parts of it) once and then do lots of inference steps.