Another thing I’d recommend is running kobold.cpp instead of ollama if you want to get into the nitty gritty of llms. Its more customizable and (ultimately) faster on more hardware.
Thats good info for low spec laptops. Thanks for the software recommendation. Need to do some more research on the model you suggested. I think you confused me for the other guy though. Im currently working with a six core ryzen 2600 CPU and a RX 580 GPU. edit- no worries we are good it was still great info for the thinkpad users!
Thank you thats useful to know. In your opinion what context size is the sweet spot for llama 3.1 8B and similar models?
Honestly as small as you can manage.
Again, you will get much better speeds out of “extreme” MoE models like deepseek chat lite: https://huggingface.co/YorkieOH10/DeepSeek-V2-Lite-Chat-Q4_K_M-GGUF/tree/main
Another thing I’d recommend is running kobold.cpp instead of ollama if you want to get into the nitty gritty of llms. Its more customizable and (ultimately) faster on more hardware.
Thats good info for low spec laptops. Thanks for the software recommendation. Need to do some more research on the model you suggested. I think you confused me for the other guy though. Im currently working with a six core ryzen 2600 CPU and a RX 580 GPU. edit- no worries we are good it was still great info for the thinkpad users!