ComfyUI SDXL Lightning dual workflow (UNET, LORA)
TLDRIn this video, the host introduces the new SDXL Lightning model, a text-image generation model that is remarkably fast and produces high-quality 1024 pixel images. The model offers one-step, two-step, four-step, and eight-step processes, with the latter two being currently functional. The video demonstrates two workflows: the UNET and LORA workflows, which involve placing models into different folders. The host uses Epic Realism XL as a base model and tests the speed of image generation, noting that the process is impressively fast even on a relatively low-spec machine. The video also covers the use of positive and negative prompts, the importance of the K sampler and the SGM uniform scheduler, and concludes with the presenter's enthusiasm for the model's speed and image quality. The host encourages viewers to download the workflow, subscribe to the channel, and support on Patreon for more insights on AI.
Takeaways
- ๐ The SDXL Lightning model is a new, fast text-image generation model capable of producing high-quality images.
- โก It offers a one-step, two-step, four-step, and eight-step process, with the latter two currently operational.
- ๐ There are two different workflows available: UNET and LORA, which involve placing models in different folders.
- ๐ The model is impressively quick, even on a relatively low-spec machine with an RTX super 2070 and 8GB VRAM.
- ๐ The video demonstrates a side-by-side comparison of the UNET and LORA workflows to evaluate any differences.
- ๐ The base model used is Epic Realism XL, with both UNET and LORA loaders in the workflow for testing.
- ๐ The video shows the process of using positive and negative prompts with C Samplers, emphasizing the importance of the SGM uniform scheduler.
- ๐ธ The generated images are of good quality, and the option to add an upscaler for further enhancement is mentioned.
- โฑ๏ธ Speed is a significant advantage, with the model loading and generating images rapidly, even during the first use.
- ๐ ๏ธ The video provides a practical demonstration of the model's capabilities, including a real-time speed test without editing.
- ๐ The workflow and models are available for download, and the presenter encourages viewers to subscribe and support for more knowledge sharing.
Q & A
What is the main strength of the new 'sdxl lightning' model mentioned in the video?
-The main strength of the 'sdxl lightning' model is its speed. It is a lightning-fast text image generation model capable of producing high-quality 1024 pixel images in a few steps.
What are the different steps available for the 'sdxl lightning' model?
-The 'sdxl lightning' model offers a one-step, two-step, four-step, and eight-step process for image generation.
Which steps of the 'sdxl lightning' model are currently not working with Comfy?
-The one-step and two-step processes are currently not working with Comfy, as they are waiting for an update from Comi.
What are the two different workflows available for the 'sdxl lightning' model?
-The two different workflows available are the UNET workflow, where you put the models into the models slun folder, and the LORA workflow, where you put the models into your models SL Laur folder.
What is the base model used for the 'Epic Realism XL' in the video?
-The base model used for 'Epic Realism XL' is the 'sdxl lightning' model.
What are the two types of loaders used in the workflow setup?
-The two types of loaders used in the workflow setup are the UNET loader and the LORA loader.
What is the default sampler name used in the 'sdxl lightning' model?
-The default sampler name used in the 'sdxl lightning' model is 'uler'.
What is the importance of the scheduler setting in the 'sdxl lightning' model?
-The scheduler setting is very important and has to be set to 'sgm' (uniform) to match the default settings of the model.
What is the significance of the speed test conducted in the video?
-The speed test is significant as it demonstrates the rapid image generation capabilities of the 'sdxl lightning' model, even on a relatively low-end machine.
What is the recommended next step after generating images with the 'sdxl lightning' model?
-After generating images with the 'sdxl lightning' model, one can add an upscaler to enhance the quality of the images or perform other post-processing tasks as desired.
How can viewers access the workflow demonstrated in the video?
-Viewers can access the workflow demonstrated in the video by downloading it from the provided source, and the presenter also mentions that the workflow will be available for download.
What is the presenter's recommendation for those interested in AI and Comfy UI?
-The presenter recommends subscribing to their channel for more knowledge and updates, and also suggests visiting their Patreon page for additional support and exciting news.
Outlines
๐ Introduction to the SDXL Lightning Model
The video begins with a warm welcome and an introduction to the SDXL Lightning model, a text-to-image generation model that is highly praised for its speed. The presenter explains that while the one-step and two-step processes are not yet functional, the four-step and eight-step processes are operational. The video demonstrates how to download and implement the model using two different workflows: the U-Net workflow and the Lora workflow. The presenter also discusses the importance of using the correct sampler and scheduler settings for optimal results. A side-by-side comparison of the U-Net and Lora loaders is conducted to assess any differences in performance, with a focus on speed and image quality.
๐ Speed and Quality Testing of the SDXL Lightning Model
The presenter proceeds to test the speed and quality of the SDXL Lightning model using different prompts and settings. Despite using a relatively modest machine with an RTX super 2070 and 8GB of VRAM, the model loads quickly and generates high-quality 1024-pixel images. The video showcases the real-time generation process, emphasizing the model's impressive speed. The presenter also addresses an issue with an inappropriate image generated during testing and adjusts the prompts accordingly. The video concludes with a recommendation to use the model for its speed and quality, and an invitation to download the workflow for personal use. The presenter encourages viewers to subscribe to their channel and support their Patreon page for more insights into AI technology.
Mindmap
Keywords
๐กSDXL Lightning
๐กUNET
๐กLORA
๐กText-Image Generation
๐กHigh-Quality 1024 Pixel Images
๐กOne-Step, Two-Step, Four-Step, and Eight-Step Process
๐กComfi UI
๐กPositive and Negative Prompts
๐กC Samplers
๐กScheduler
๐กSpeed Test
๐กReal-Time Demonstration
Highlights
Introducing the new SDXL Lightning model, a fast text-image generation model.
The model can produce high-quality 1024-pixel images in a few steps.
Currently, the one-step and two-step processes are not working with ComfyUI, awaiting updates.
The four-step and eight-step processes are operational with both UNET and LORA workflows.
Downloading the models involves placing them into the models' respective folders for UNET and LORA.
The video demonstrates a side-by-side comparison of UNET and LORA loaders for speed and quality.
Epic Realism XL is used as the base model for the demonstrations.
The importance of using the SGM (Steady Gradient Method) scheduler for the K sampler.
The video showcases the impressive speed of image generation on a relatively low-spec machine.
The SDXL Lightning model loaded quickly, even on an RTX super 2070 with 8GB VRAM.
The generated images from both UNET and LORA are of good quality and can be further enhanced with an upscaler.
The video includes real-time speed tests without any cuts or edits for authenticity.
The presenter encountered an issue with an unsafe-for-work image and adjusted the prompt accordingly.
The SDXL Lightning model demonstrated fast image generation even with prompt changes.
The presenter expresses enthusiasm for the speed and quality of the SDXL Lightning model.
The workflow for using the SDXL Lightning model will be made available for download.
The video encourages viewers to subscribe to the channel for more knowledge sharing on AI.
The presenter mentions having a Patreon page for those who wish to support the content creation.
The video concludes with a teaser for exciting upcoming news related to AI.