Merge branch 'main' into sreeram/lemonade-related-updates

Author: sreeram-11

README.md

@@ -28,15 +28,15 @@ This is AMD's official repository of playbooks for AMD developer platforms. Each
 
 | Playbook | Description |
 |----------|-------------|
-| **Running LLMs with PyTorch and ROCm** | Run powerful language models locally with PyTorch and ROCm |
+| **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 |
 | **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 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 RyzenAI and ROCm |
+| **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 |

playbooks/core/comfyui-image-gen/playbook.json

@@ -1,7 +1,7 @@
 {
   "id": "comfyui-image-gen",
   "title": "Generating images with ComfyUI and Z Image Turbo",
-  "description": "Create stunning AI-generated images using ComfyUI with Z Image Turbo.\u2122",
+  "description": "Create stunning AI-generated images using ComfyUI with Z Image Turbo.",
   "time": 15,
   "supported_platforms": {
     "halo": [

playbooks/core/pytorch-rocm-llms/playbook.json

@@ -1,6 +1,6 @@
 {
   "id": "pytorch-rocm-llms",
-  "title": "Running LLMs with PyTorch and ROCm",
+  "title": "Running LLMs with PyTorch and AMD ROCm™ software",
   "description": "Learn to run powerful language models on your PC with PyTorch and AMD ROCm™ software to summarize documents quickly and easily.",
   "time": 30,
   "supported_platforms": {

playbooks/supplemental/pytorch-kernels/README.md

@@ -59,7 +59,7 @@ Both approaches run on AMD GPUs. This is possible because PyTorch's ROCm build m
 A GPU kernel is a function that runs in parallel across thousands of GPU threads simultaneously. Unlike a CPU function that executes once per call, a kernel is launched with a **grid** of **blocks**, each containing many **threads**, all executing the same code on different data.
 
 <p align="center">
-  <img src="https://github.com/user-attachments/assets/4773c54b-686e-4b1b-8fea-d451dee9c27c" width="900"/>
+  <img src="assets/grid_threads.png" width="900"/>
 </p>
 
 ### GPU Execution Model: Wavefronts