Resolve merge conflicts and simplify README

README.md

@@ -402,21 +402,10 @@ in the form of [a Helm chart and static YAML](charts/docker-model-runner/README.
 If you are interested in a specific Kubernetes use-case, please start a
 discussion on the issue tracker.
 
-<<<<<<< Updated upstream
-=======
 ## dmrlet: Container Orchestrator for AI Inference
 
 dmrlet is a purpose-built container orchestrator for AI inference workloads. Unlike Kubernetes, it focuses exclusively on running stateless inference containers with zero configuration overhead. Multi-GPU mapping "just works" without YAML, device plugins, or node selectors.
 
-### Key Features
-
-| Feature | Kubernetes | dmrlet |
-|---------|------------|--------|
-| Multi-GPU setup | Device plugins + node selectors + resource limits YAML | `dmrlet serve llama3 --gpus all` |
-| Config overhead | 50+ lines of YAML minimum | Zero YAML, CLI-only |
-| Time to first inference | Minutes (pod scheduling, image pull) | Seconds (model already local) |
-| Model management | External (mount PVCs, manage yourself) | Integrated with Docker Model Runner store |
-
 ### Building dmrlet
 
 ```bash
@@ -429,91 +418,12 @@ go build -o dmrlet ./cmd/dmrlet
 
 ### Usage
 
-**Start the daemon:**
-```bash
-# Start in foreground
-dmrlet daemon
-
-# With custom socket path
-dmrlet daemon --socket /tmp/dmrlet.sock
-```
-
 **Serve a model:**
 ```bash
 # Auto-detect backend and GPUs
-dmrlet serve llama3.2
-
-# Specify backend
-dmrlet serve llama3.2 --backend vllm
-
-# Specify GPU allocation
-dmrlet serve llama3.2 --gpus 0,1
-dmrlet serve llama3.2 --gpus all
-
-# Multiple replicas
-dmrlet serve llama3.2 --replicas 2
-
-# Backend-specific options
-dmrlet serve llama3.2 --ctx-size 4096      # llama.cpp context size
-dmrlet serve llama3.2 --gpu-memory 0.8     # vLLM GPU memory utilization
-```
-
-**List running models:**
-```bash
-dmrlet ps
-# MODEL          BACKEND    REPLICAS   GPUS      ENDPOINTS              STATUS
-# llama3.2       llama.cpp  1          [0,1,2,3] localhost:30000        healthy
-```
-
-**View logs:**
-```bash
-dmrlet logs llama3.2        # Last 100 lines
-dmrlet logs llama3.2 -f     # Follow logs
-```
-
-**Scale replicas:**
-```bash
-dmrlet scale llama3.2 4     # Scale to 4 replicas
-```
-
-**Stop a model:**
-```bash
-dmrlet stop llama3.2
-dmrlet stop --all           # Stop all models
-```
-
-**Check status:**
-```bash
-dmrlet status
-# DAEMON: running
-# SOCKET: /var/run/dmrlet.sock
-#
-# GPUs:
-#   GPU 0:  NVIDIA A100 80GB  81920MB  (in use: llama3.2)
-#   GPU 1:  NVIDIA A100 80GB  81920MB  (available)
-#
-# MODELS: 1 running
-```
-
-### Supported Backends
-
-- **llama.cpp** - Default backend for GGUF models
-- **vLLM** - High-throughput serving for safetensors models
-- **SGLang** - Fast serving with RadixAttention
-
-### Architecture
-
-```
-dmrlet daemon
-  ├── GPU Manager      - Auto-detect and allocate GPUs
-  ├── Container Manager - Docker-based container lifecycle
-  ├── Service Registry  - Endpoint discovery with load balancing
-  ├── Health Monitor    - Auto-restart unhealthy containers
-  ├── Auto-scaler       - Scale based on QPS/latency/GPU utilization
-  └── Log Aggregator    - Centralized log collection
+dmrlet serve gemma3
 ```
 
->>>>>>> Stashed changes
 ## Community
 
 For general questions and discussion, please use [Docker Model Runner's Slack channel](https://dockercommunity.slack.com/archives/C09H9P5E57B).