llama.cpp adds --n-cpu-ffn option for faster dense models

New llama.cpp PR #26622 adds a --n-cpu-ffn option, similar to --n-cpu-moe, letting users offload a specified number of FFN sublayers to CPU for dense models, aiming to speed up low-VRAM inference.