Use ngram-mod and prioritize attention experts

docs/LLM/Dankserver System Specs.md

@@ -60,11 +60,11 @@ Dankserver is an NVIDIA GPU server for vLLM inference. The host runs Ubuntu 26.0
 
 ### Active Services
 
-The active service on Dankserver is `frank-default-small.service`: the llama.cpp Ornith-1.5-35B-A3B CRACK (Q6_K) on port 7770, with expert tensors selected by `--override-tensor`; full-attention blocks 27 and 31 plus output-adjacent blocks 33–40 remain on CUDA. The earlier PP worker (`frank-pp-worker.service`) was retired with the 2026-08-17 redo. See [[deployment]].
+The active service on Dankserver is `frank-default-small.service`: the llama.cpp Ornith-1.5-35B-A3B CRACK (Q6_K) on port 7770, with expert tensors selected by `--override-tensor`; every full-attention block plus blocks 35–40 remain on CUDA. The earlier PP worker (`frank-pp-worker.service`) was retired with the 2026-08-17 redo. See [[deployment]].
 
 ## Hardware Relevance
 
-- 24 GB VRAM hosts the Q6_K non-expert tensors and the measured hybrid expert placement. The context pool contains 491520 f16 cells across three 163840-token slots. Verify actual headroom after each model restart with `nvidia-smi` and the service journal.
+- 24 GB VRAM hosts the Q6_K non-expert tensors and the full-attention/final-layer expert placement. The context pool contains 491520 f16 cells across three 163840-token slots. The service uses ngram-mod only and `ubatch=1024`. Verify actual headroom after each model restart with `nvidia-smi` and the service journal.
 - 62 GB system RAM holds the remaining CPU-resident expert tensors with room to spare.
 - 127 GB swap is available for CPU KV cache paging if GPU KV offload is disabled.
 - Root disk has approximately 140 GB free. Store the GGUF models under `/home/dank/models` (about 32 GB total).