I'm trying to see what can run on an 8GB Raspberry Pi 5, and it occours to me that your approach might scale down really well. Any tips for replicating what you did with something like TinyLlama or trying for an 8 bit quantization of LlaVA-Phi? I'd love to try training some sort of student model as an experiment from the more successful models you've trained.
For what it's worth 4 bit quantizations of LLaVA 1.6 work quite well even in the limited context of a Raspberry Pi. I'll try quantizing MOE-LLaVa soon. Let me know if this is interesting.
Question
I'm trying to see what can run on an 8GB Raspberry Pi 5, and it occours to me that your approach might scale down really well. Any tips for replicating what you did with something like TinyLlama or trying for an 8 bit quantization of LlaVA-Phi? I'd love to try training some sort of student model as an experiment from the more successful models you've trained.