model : Granite-Switch Architecture (#25107) granite-switch: add llama.cpp backend (POC, CPU) New "granite-switch" architecture: a dense, all-attention Granite-4.1 model with N embedded LoRA adapters selected per-token by control tokens. gguf-py schema (arch, KV keys, stacked LoRA tensor names) + writer helpers conversion/granite.py: GraniteSwitchModel converter (stacks N adapters + zero base slot into per-projection A/B tensors; emits switch metadata) C++ arch registration (llama-arch.{h,cpp}, llama-model.{h,cpp}) src/models/granite_switch.cpp: load + per-token switched-LoRA graph via ggml_mul_mat_id over stacked tensors; sticky per-token index + control-token substitution in llm_graph_input_switch::set_input llm_graph_input_switch in src/models/models.h Runs end-to-end on CPU: convert 3b checkpoint (842 tensors, stacked dim 13) and generate on both base and control-token paths.

Sticky switch state is single-sequence (POC); full multi-sequence machinery is a follow-up. granite-switch: add Mac (Metal) build + mid-sequence switch demo script Self-contained script to build llama.cpp on Apple Silicon (Metal), convert the composed 3b checkpoint, and run the crisp mid-sequence…