frank-primary: pin the -ot override set to the real tensor names

Discovery, not guesswork: dump the GGUF v3 headers of the fetched parts
(scripts/dump-gguf.py, added — a dependency-free reader that never
touches tensor data, so a 50 GiB part scans in milliseconds) before
the first load.

What the dump says (parts 2-3, 2026-09-26):

- The 51B-param PLE n-gram table is ONE tensor: per_layer_token_embd.
  weight, dims [160, 320001536], Q8_0, 54.4 GiB — exactly the whole of
  part 3. It is the same tensor the shared MTP head borrows, so the
  =CPU override is required for placement AND for the draft load
  (GPU-resident borrow: "invalid vector subscript").
- The model is qwen4exp, 512 experts, top-10 routing
  (qwen4exp.ple.ngram_size=3, heads_per_ngram=8).
- Part 1 is metadata-only (ntensors=0); parts 2-6 carry tensors.

The placeholder pattern ngram_embeddings matched nothing — dropped from
OT_OVERRIDES (env, serve-script default, seam, AGENTS.md, runbook,
LLM index) before it could masquerade as a working override at load
time. Deployed set: exps=CPU,per_layer_token_embd.weight=CPU.

Suite: 346 green.

serverAppConfigs-docs/LLM/index.md

@@ -62,7 +62,7 @@ frank-small, port 7771]
   unsloth llama.cpp (b11030-mix prebuilt, ROCm gfx120X, bundled runtime)
   serving unsloth/Qwen3.8-Flash-Next-GGUF at Q8_0 across both R9700s —
   routed experts and the 51B-param n-gram table computed in host RAM
-  (`-ot exps=CPU,ngram_embeddings=CPU`), the shared Q8_0 MTP head
+  (`-ot exps=CPU,per_layer_token_embd.weight=CPU`), the shared Q8_0 MTP head
   (depth 2) chained behind ngram-mod, BF16 vision, one full 262,144-token
   conversation, `reasoning_content`, the placement law, the cutover and
   rollback