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README.md

@@ -107,6 +107,97 @@ model = model.merge_and_unload()
     -p "Solve this math problem step by step..."
 ```
 
+
+### llama.cpp Server (Docker) — การใช้งานแบบ Multi-LoRA Stacking 🔥
+
+🌐 **สแต็ก LoRA หลายตัวพร้อมกัน** — รวมโมเดลพื้นฐานแบบ uncensored + Opus reasoning LoRA + Kimi style LoRA เข้าด้วยกันในเซิร์ฟเวอร์เดียวที่เข้ากันได้กับ OpenAI API:
+
+### llama.cpp Server (Docker) — Multi-LoRA Stacking 🔥
+
+Combine the **uncensored base model** + **Opus reasoning LoRA** + **Kimi style LoRA** into one OpenAI-compatible API server:
+
+```bash
+sudo docker run --rm -p 8080:8080 \
+  -v /path/to/models/:/models \
+  --gpus all \
+  --env CUDA_VISIBLE_DEVICES=0,1,2,3 \
+  ghcr.io/ggml-org/llama.cpp:server-cuda \
+  -m /models/llmfan46_Qwen3.6-35B-A3B-uncensored-heretic-Q6_K.gguf \
+  --lora-scaled /models/lordx64_Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-adapter-F16.gguf:0.6,/models/qwen3.6-35b-opus-to-kimi-lora.gguf:0.8 \
+  --host 0.0.0.0 --port 8080 \
+  --n-gpu-layers 999 \
+  --tensor-split 4,13,12,12 \
+  --ctx-size 131072 \
+  --batch-size 4096 \
+  --ubatch-size 512 \
+  --cache-type-k q4_0 \
+  --cache-type-v q4_0 \
+  -fa on \
+  --mlock \
+  --jinja
+```
+
+**What this does:**
+
+| Component | Purpose | Weight |
+|-----------|---------|--------|
+| `llmfan46_...-heretic-Q6_K.gguf` | Uncensored base (35B MoE) | 🏛️ Base |
+| `lordx64_...-Opus-...-adapter-F16.gguf` | Claude Opus reasoning (concise) | 0.6 = 60% |
+| `qwen3.6-35b-opus-to-kimi-lora.gguf` | → Kimi K2.6 style (verbose) 🔥 | 0.8 = 80% |
+
+**Result:** Uncensored base + Opus reasoning structure + Kimi verbose style — all in one model!
+
+**Key flags explained:**
+
+| Flag | Purpose |
+|------|---------|
+| `--lora-scaled A:α,B:β` | Stack multiple LoRA adapters with independent scales |
+| `--n-gpu-layers 999` | Offload all layers to GPU |
+| `--tensor-split 4,13,12,12` | Split across 4 GPUs (adjust for your setup) |
+| `--ctx-size 131072` | 128K context window |
+| `--cache-type-k q4_0` | KV cache in 4-bit quantization (saves VRAM) |
+| `--cache-type-v q4_0` | Value cache in 4-bit quantization |
+| `-fa on` | Flash Attention enabled |
+| `--mlock` | Lock model in RAM (prevents swap) |
+| `--jinja` | Use Jinja2 chat templates |
+
+**Single GPU alternative:**
+```bash
+sudo docker run --rm -p 8080:8080 \
+  -v /path/to/models/:/models \
+  --gpus all \
+  ghcr.io/ggml-org/llama.cpp:server-cuda \
+  -m /models/llmfan46_Qwen3.6-35B-A3B-uncensored-heretic-Q6_K.gguf \
+  --lora-scaled /models/lordx64_Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-adapter-F16.gguf:0.6,/models/qwen3.6-35b-opus-to-kimi-lora.gguf:0.8 \
+  --host 0.0.0.0 --port 8080 \
+  --n-gpu-layers 999 \
+  --ctx-size 32768 \
+  --batch-size 2048 \
+  --cache-type-k q4_0 --cache-type-v q4_0 \
+  -fa on --mlock --jinja
+```
+
+**API Usage (OpenAI-compatible):**
+```bash
+curl http://localhost:8080/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {"role": "user", "content": "Explain quantum entanglement step by step"}
+    ],
+    "temperature": 0.7,
+    "max_tokens": 4096
+  }'
+```
+
+> 💡 **Tip:** Adjust LoRA scales to fine-tune the reasoning style:
+> - `0.6:0.8` — Balanced (Opus structure + Kimi verbosity)
+> - `0.3:1.0` — Heavy Kimi style
+> - `1.0:0.2` — Mostly Opus, slight Kimi touch
+> - `0.0:1.0` — Pure Kimi style (skip Opus adapter entirely)
+
+
 ---
 
 ## 📊 Comparison: Opus vs Kimi Reasoning
@@ -165,4 +256,4 @@ python3 extract_lora_diff.py \
 
 ## 📄 License
 
-Apache 2.0 — same as the source models.
+Apache 2.0 — same as the source models.