tune(llm): partial GPU offload for qwen-classifier, real headroom

Full offload (999 layers) left only ~768MB free VRAM regardless of
batch-size/flash-attn tuning — that gap tracks roughly fixed regardless
of those knobs, most likely ROCm's own per-process HIP context overhead
(same ROCm#5706 quirk already noted for two HIP contexts sharing this
card, see llama-server's GPU_MAX_HW_QUEUES comment above). Dropping to
28/36 layers on GPU (6 layers + their KV on CPU) trades a slice of
speed for real freed VRAM — still >80% of layers on GPU, nowhere near
CPU-only's unusable latency. Verifying live before locking this number in.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

docker-compose.yml

@@ -99,7 +99,7 @@ services:
       -m /models/${LLAMA_CLASSIFIER_MODEL_FILE:-Qwen3-4B-Instruct-2507-UD-Q4_K_XL.gguf}
       --host 0.0.0.0
       --port 8080
-      --n-gpu-layers 999
+      --n-gpu-layers 28
       --ctx-size 65536
       --parallel 1
       --batch-size 512