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Updated in [July 09th, 2023]

The Updated: Offline Stable Diffusion Model Training - Make Your Custom LoRA with Kohya course provides participants with a comprehensive walkthrough of installing Kohya, a tool that enables the creation of custom LoRA (Level of Representation Adaptation) models from personal images offline. The course focuses specifically on the installation process, with future parts covering LoRA creation.
Participants will be guided through the step-by-step installation of Kohya, ensuring they have the necessary tools and resources to create their own custom LoRA models. The course highlights the importance of offline training, allowing participants to work independently without requiring an internet connection.
The course provides valuable links to essential resources, including the Kohya Low Rank Adaptation Trainer on Github, where participants can access the necessary files for installation. Participants will also be directed to NVIDIA's developer resources, where they can sign up for free to access the cuDNN libraries required for the installation process.
Through this course, participants will gain the knowledge and skills needed to install Kohya and embark on the journey of creating their own custom LoRA models. By offering a step-by-step installation guide and directing participants to relevant resources, the course empowers individuals to engage in offline Stable Diffusion model training and explore the possibilities of personalized LoRA models.
Participants showed deep interest in the comprehensive walkthrough provided in the course, which enabled them to navigate the installation process smoothly. The step-by-step instructions and inclusion of valuable links to Kohya's Github repository and NVIDIA's developer resources facilitated their understanding and ensured they had the necessary files and libraries for installation.
Overall, the Updated: Offline Stable Diffusion Model Training - Make Your Custom LoRA with Kohya course has equipped participants with the knowledge and resources needed to create personalized LoRA models. By providing a clear installation guide and emphasizing the advantages of offline training, the course has empowered participants to explore the possibilities of customized Stable Diffusion models.