Sam Altman says ChatGPT should be ‘much less lazy now’::ChatGPT users previously complained that the chatbot was slacking off and refusing to complete some tasks.
ROCm is decent right now, I can do deep learning stuff and CUDA programming with it with an AMD APU. However, ollama doesn’t work out-of-the-box yet with APUs, but users seem to say that it works with dedicated AMD GPUs.
As for Mixtral8x7b, I couldn’t run it on a system with 32GB of RAM and an RTX 2070S with 8GB of VRAM, I’ll probably try with another system soon [EDIT: I actually got the default version (mixtral:instruct) running with 32GB of RAM and 8GB of VRAM (RTX 2070S).] That same system also runs CodeLlama-34B fine.
So far I’m happy with Mistral 7b, it’s extremely fast on my RTX 2070S, and it’s not really slow when running in CPU-mode on an AMD Ryzen 7. Its speed is okayish (~1 token/sec) when I try it in CPU-mode on an old Thinkpad T480 with an 8th gen i5 CPU.
I have a ryzen apu, so I was curious. I tried yesterday to fiddle with it, and managed to up the “vram” to 16gb. But installing xformers and flash-attention for LLM support on igpus is not officially supported and was not possible to install anything past pytorch. It’s step further for sure, but still needs lots of work.
