Update list of released playbooks

README.md

@@ -31,26 +31,26 @@ This is AMD's official repository of playbooks for AMD developer platforms. Each
 | **Running LLMs with PyTorch and AMD ROCm™ software** | Run powerful language models locally with PyTorch and ROCm |
 | **Running and Serving LLMs with LM Studio** | Set up LM Studio to run and serve large language models |
 | **Automating Workflows with n8n and Local LLMs** | Build an AI-powered news summarizer using n8n and Lemonade |
-| **Local LLM Coding with VSCode and Qwen3-Coder** | Use VSCode with locally-running Qwen3-Coder for private code assistance |
+| **Local LLM Coding with VS Code and Qwen3-Coder** | Use VS Code with locally-running Qwen3-Coder for private code assistance |
 | **Generating Images with ComfyUI and Z Image Turbo** | Create AI-generated images using ComfyUI with Z Image Turbo |
+| **Chat with LLMs in Open WebUI** | Set up Open WebUI to chat with local LLMs |
+| **Fine-tune LLMs with PyTorch and AMD ROCm™ software** | Fine-tune large language models using PyTorch and ROCm |
+| **Using Lemonade Across CPU, GPU, and NPU** | Learn how to use the Lemonade framework across CPU, GPU, and NPU |
+| **Optimized Fine-tuning with Unsloth** | Memory-efficient LoRA fine-tuning with Unsloth |
+| **Speech-to-Speech Translation** | Build a real-time speech-to-speech translation system |
 
 ## Coming Soon
 
 | Playbook | Description |
 |----------|-------------|
-| **Chat with LLMs in Open WebUI** | Set up Open WebUI to chat with local LLMs |
-| **Fine-tune LLMs with PyTorch and ROCm** | Fine-tune large language models using PyTorch and ROCm |
-| **Using Lemonade Across CPU, GPU, and NPU** | Learn how to use the Lemonade framework across CPU, GPU, and NPU |
 | **Local Computer Vision with Ryzen™ AI NPU** | Build local perception capabilities using CVML SDK on Ryzen AI and ROCm |
 | **Clustering Two Devices with llama.cpp RPC** | Distributed inference using RPC server across two AMD devices with llama.cpp |
 | **Getting Started with Ollama** | Install Ollama and run LLMs locally from the terminal, desktop app, or REST API |
 | **Getting Started Creating Agents with GAIA** | Build and deploy AI agents using the GAIA framework |
 | **Fine-tuning LLMs with LLaMA-Factory** | LoRA fine-tuning of large language models using LLaMA-Factory |
 | **Custom GPU Kernels with PyTorch ROCm** | Write and optimize custom GPU kernels using PyTorch and ROCm |
-| **Optimized Fine-tuning with Unsloth** | Memory-efficient LoRA fine-tuning with Unsloth |
 | **Quick Start on vLLM** | Run inference and serving using vLLM |
 | **Clustering with RCCL** | Multi-node cluster using two AMD devices with RCCL |
-| **Speech-to-Speech Translation** | Build a real-time speech-to-speech translation system |
 
 ## AMD AI Developer Program