Boost Performance with Stable Diffusion Automatic 1111 SDXL!

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Boost Performance with Stable Diffusion Automatic 1111 SDXL!

Table of Contents

  1. Introduction
  2. Understanding the Problem
  3. Solution 1: Renting a System with Higher VRAM
  4. Solution 2: Using Run Pod Service
    • 4.1. Signing up for Run POD
    • 4.2. Adding Funds to Your Account
    • 4.3. Choosing the Cloud Type
    • 4.4. Selecting an Action Template
    • 4.5. Deploying the System
    • 4.6. Exploring Available Options
    • 4.7. Accessing Jupiter Labs and Automatic 1111
    • 4.8. Downloading SD Excel Model
    • 4.9. Downloading Refiner Model and Lora File
    • 4.10. Downloading Control Net Model
    • 4.11. Testing the Models
  5. Conclusion

Renting a System with Run POD Service to Use Stable Diffusion with SD Excel Model

Are You facing difficulties in using the newly released SD Excel model on your system due to limited VRAM? Is the price of a new graphic card too high for your budget? Don't worry, there's a solution! In this article, we will explore how you can use Stable Diffusion with the SD Excel model on any system, even without an additional graphic card, by renting a system with higher VRAM from a service called Run POD. This method allows you to run stable diffusion seamlessly and also provides the flexibility to use it on your mobile phone. Let's dive into the details and learn how you can leverage Run POD to overcome the VRAM limitations and use the SD Excel model effectively.

1. Introduction

Introduction to the problem of using SD Excel model with limited VRAM and the solution of renting a system using Run POD service.

2. Understanding the Problem

Explanation of the limitations faced when using the SD Excel model with limited VRAM and the impact on the performance of stable diffusion.

3. Solution 1: Renting a System with Higher VRAM

Exploration of the traditional approach of upgrading to a new graphic card with higher VRAM and its associated challenges, such as high prices and availability.

4. Solution 2: Using Run POD Service

Detailed step-by-step guide on how to use Run POD service to rent a system with higher VRAM and run stable diffusion seamlessly.

4.1. Signing up for Run POD

Instructions on how to Create an account on the Run POD Website and log in.

4.2. Adding Funds to Your Account

Guidance on adding funds to your Run POD account to cover the rental costs.

4.3. Choosing the Cloud Type

Explanation of the two types of clouds available on Run POD: Secure Cloud and Community Cloud, and their respective advantages and suitability.

4.4. Selecting an Action Template

Introduction to action templates and their role in installing prerequisite software on the rented system. Demonstration of selecting a suitable template for stable diffusion.

4.5. Deploying the System

Walkthrough of the process of deploying the rented system with the desired specifications, including the amount of RAM, graphic card choice, and cost considerations.

4.6. Exploring Available Options

Overview of various options and settings available on the Run POD platform, such as log management, port editing, system restart, stop, and reset.

4.7. Accessing Jupiter Labs and Automatic 1111

Instructions on accessing Jupiter Labs and the Automatic 1111 web UI for using stable diffusion and other related tasks.

4.8. Downloading SD Excel Model

Step-by-step guide on how to download the SD Excel model from Hugging Face and install it on the rented system.

4.9. Downloading Refiner Model and Lora File

Demonstration of downloading the refiner model and Lora file to improve the generated images.

4.10. Downloading Control Net Model

Guidance on downloading the control net model and its usage in image generation.

4.11. Testing the Models

Practical examples of testing the downloaded models, including SD Excel, refiner model, and control net, along with the process of generating and improving images.

5. Conclusion

Summary of the article highlighting the benefits of using Run POD service to solve the VRAM limitation issue and leverage the SD Excel model effectively.

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