Open rickstaa opened 3 months ago
I will write a guide with my opinions on best practices and default settings for the currently most common Livepeer AI subnet models (RealVisXL4.0_Lightning and ByteDanceSDXL_Lightning 8-step) for most images, for 0 LPT.
Short answer: (Detailed response with examples to follow soon)
For models with "Lightning" in the name, using 6-8 steps with a CFG between 2-4 will generally offer the best results in terms of image quality and speed.
For other models, 25+ steps and a CFG of 6-8 are generally optimal.
This is a complex and nuanced topic, so using a one-size-fits-all solution will undoubtedly leave some quality on the table. However, the settings above should work well for most images, balancing detail, natural appearance and speed of processing.
I'm off to Tahoe with the family tonight, so until later, aloha! :)
Im interested in this bounty. I have made X/Y/X grids in the past to see how different parameters affect each other, to find good ranges of parameters. Using a static seed while varying other parameters to show the differences. As well as doing it over a range of prompts and models.
Hi, I'm interested in this bounty, if it's still open would love to work on this.
Overview
To give users of the AI subnet the best experience it would help to provide them a way to enable sensible defaults for our current supported pipelines and models. We invite builders in the community to research these parameters for the recommended warm models in the T2I pipeline 🔧. By completing this bounty, you'll help enhance the ease of use of the T2I pipeline, benefiting the entire community. Once we have established these defaults, we can begin implementing a way for users to apply these optimal parameters (see LIV-471).
Required Skillset
Bounty Requirements
The bounty requests a report provided by the bounty hunter containing the following information:
This information should be provided for the two warm models in the T2I pipeline:
Implementation Tips
How to Apply
Thank you for your interest in contributing to our project 💛!