Update README.md

README.md

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 license: apache-2.0
 short_description: cpu image maker ai
 ---
+# 🤖✨ AI Image Generator (CPU)  
+[![Hugging Face Space](https://img.shields.io/badge/HuggingFace-Spaces-blue?logo=huggingface)](https://huggingface.co/spaces/your-username/cpu-image-gen)  
+[![Gradio UI](https://img.shields.io/badge/Gradio-5.31.0-brightgreen?logo=gradio)]  
+[![Model](https://img.shields.io/badge/Model-StableDiffusion-orange)](https://huggingface.co/runwayml/stable-diffusion-v1-5)  
+[![License](https://img.shields.io/badge/License-MIT-lightgrey)](LICENSE)
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+
+## 🚀 Overview  
+Leverage **Generative AI** and **latent diffusion** to turn text prompts into stunning images—**entirely on CPU**. No GPUs, no paid APIs—just open-source models and your browser.
+
+> **Key AI buzzwords:**  
+> • Latent Diffusion • Denoising U-Net • Cross-Attention • Text-to-Image Generation • CLIP-Guided Prompting • Zero-Shot Creativity • Edge Inference • Cloud-Native Deployment
+
+---
+
+## ✨ Features
+
+| 🔑 Feature                    | 🔍 Description                                                          |
+|-------------------------------|-------------------------------------------------------------------------|
+| **🌌 Creative Prompts**         | Supports any imaginative text input—landscapes, portraits, abstract art |
+| **⚙️ Adjustable Steps**        | Control fidelity vs. speed (1–50 inference steps)                       |
+| **💻 CPU-Only Inference**      | Runs on free-tier Spaces (2 vCPU / 16 GB RAM), no CUDA required         |
+| **🎛️ Sleek UI**               | Gradio Blocks for intuitive prompt entry and result display             |
+| **🔄 Stateless**               | Each request is independent—no session state or logging overhead        |
+| **🔧 Modular**                | Swap pipeline ID to any other text-to-image model with minimal change   |
+
+---
+
+## 🏗️ Architecture & Workflow
+
+1. **Prompt Encoding**  
+   The text prompt is tokenized and mapped into the model’s latent space.  
+2. **Denoising Loop**  
+   A U-Net repeatedly denoises latent noise over *N* steps guided by cross-attention to the prompt.  
+3. **Decoder**  
+   The final latent is decoded into an RGB image via the model’s VAE.  
+4. **Rendering**  
+   Gradio streams the generated image back to the browser for instant viewing.
+
+---
+
+## 🛠️ Local Development
+
+```bash
+git clone https://github.com/your-username/cpu-image-gen.git
+cd cpu-image-gen
+python3 -m venv venv && source venv/bin/activate
+pip install -r requirements.txt
+python app.py