SDXL Lightning For Stable Diffusion ComfyUI - How To Use And What We Should Know
TLDRIn this video, the creator discusses the SDXL Lightning model developed by Bite Den, which was recently launched and has gained attention for its fast and stable image generation capabilities. The video provides a step-by-step guide on how to use SDXL Lightning with ComfyUI, emphasizing the importance of using the correct checkpoint and Laura files for optimal performance. The presenter also compares SDXL Lightning to other models like LCM and SDXL Turbo, highlighting its simplicity and speed. The summary explains that the model uses low sampling steps and CFG numbers, allowing it to generate images in near real-time. The video also touches on the use of different sampling schedulers and the potential for customization with additional Laura styles. The creator concludes by noting that while SDXL Lightning is not ideal for animation, it is an excellent choice for quickly generating images with good average quality, making it suitable for initial idea generation and further refinement in other workflows.
Takeaways
- 📈 SDXL Lightning is a new model created by Bite Den, designed for fast and stable image generation.
- 🔍 The presenter waited for the model to stabilize before discussing it, to avoid misinformation and crashes.
- 🌐 A demo page is available for testing SDXL Lightning with simple text prompts.
- 📚 Two-step, four-step, and eight-step models have been released, each optimized for their respective step counts.
- 📁 All-in-one checkpoint models are available for Comfy UI, and UNet checkpoint models for Diffuser.
- 📝 For Comfy UI users, downloading checkpoint models is sufficient, while Diffuser users need to download UNet models.
- 🔧 The setup involves placing checkpoint models in the models checkpoint folder and Laura files in the Laura subfolder.
- ⚙️ Optimal settings for SDXL Lightning include four sampling steps and a CFG of 1 for best performance.
- 🚀 SDXL Lightning is similar to SDXL Turbo but simpler to connect, without the need for extra custom nodes.
- 🎨 The presenter prefers using SDXL models for fast image generation, offering flexibility with well-trained models like Juggernaut XL and Reali XL.
- ⏱️ Images are generated in under 1 second with 1K sampler, providing good average quality with low sampling steps and CFG.
- 🚫 SDXL Lightning may not be suitable for animation workflows, as it did not perform well in detailed and complex scenarios.
Q & A
What is SDXL Lightning?
-SDXL Lightning is an AI model created by Bite Den, designed for fast and efficient image generation with low sampling steps and CFG number settings.
What is the purpose of waiting for SDXL Lightning to become more stable before discussing it?
-Waiting for the model to become more stable ensures that any updates or improvements have been integrated, reducing the risk of misinformation and crashes that can occur with rapidly evolving AI technologies.
How can users try out SDXL Lightning?
-Users can try out SDXL Lightning through its demo page, where they can input a text prompt or a natural language style text prompt to generate images.
What are the different models released by Bite Den for SDXL Lightning?
-Bite Den has released two-step, four-step, and eight-step models individually, as well as all-in-one checkpoint models for Comfy UI and UNet checkpoint models for Diffuser.
Why is the four-step model considered the optimum for SDXL Lightning?
-The four-step model is considered optimum because it is designed to run with the lowest number of sampling steps for the best performance without over-saturating the AI image.
What are the steps to use SDXL Lightning with Comfy UI?
-To use SDXL Lightning with Comfy UI, download the checkpoint models and Lura files, place them in the respective folders, and then set the sampling step to four and CFG to one in the UI.
How does SDXL Lightning compare to SDXL Turbo in terms of image generation speed?
-SDXL Lightning is very similar to SDXL Turbo in terms of speed, offering almost real-time image generation. However, it is simpler to connect and does not require extra custom nodes.
What is the best sampling scheduler to use with SDXL Lightning?
-The best sampling scheduler to use with SDXL Lightning is the sgm uniform, which performs better for image generation.
How can users achieve fast image generation with SDXL Lightning?
-Users can achieve fast image generation by using the all-in-one checkpoint models, setting the sampling steps to four, and using the sgm uniform scheduler. Incorporating additional Lura models can also enhance the image quality.
Is SDXL Lightning suitable for animation?
-SDXL Lightning may not be the best choice for animation as it tends to produce blurry results even with higher step and CFG settings. Other methods or models might be more suitable for this purpose.
What are the advantages of using SDXL Lightning over other models like LCM and SDXL Turbo?
-SDXL Lightning offers a simpler setup process, requiring no special custom nodes for image generation. It also provides fast image generation with good average quality, making it suitable for quickly generating images for initial ideas.
Outlines
🚀 Introduction to SdxL Lightning by Bite Den
The speaker introduces SdxL Lightning, a tool created by Bite Den, which was recently launched. They chose to discuss it after a 12-day stabilization period to ensure reliability, given the rapid pace of AI development. The tool has a demo page for users to experiment with text prompts. Two-step, four-step, and eight-step models are available for download, with the four-step model being optimal for performance. The speaker also discusses the use of all-in-one checkpoint models for Comfy UI and separate Unet checkpoint models for Diffusers. They provide instructions on downloading and installing these models, emphasizing the simplicity of the process and the importance of using the correct model for the desired number of sampling steps.
🎨 Workflow and Performance of SdxL Lightning
The speaker outlines the process of setting up a new workflow with SdxL Lightning using Comfy UI. They mention the ease of using the tool with only checkpoint models and the option to choose between two, four, or eight steps. The speaker prefers the four-step model for balanced performance. They demonstrate the speed of image generation with SdxL Lightning, noting that it is similar to SdxL Turbo but simpler to connect without custom nodes. The use of SGM uniform and e ancestral sampling schedulers is highlighted for better performance. The speaker also discusses the process of using a VAE loader for improved image quality and the flexibility of using different Laura models for fine-tuning.
🔍 Flexibility and Speed of SdxL Lightning with Laura Models
The speaker discusses the flexibility of using SdxL Lightning with Laura models, such as 'Laura beautiful girl for Jordan 2', to enhance images based on checkpoint models. They emphasize the ability to combine various Laura styles with checkpoint styles for improved results. The speaker also mentions the option to lower sampling steps to increase the speed of image generation. They provide an example using a futuristic text prompt and demonstrate the fast loading times and image quality. The speaker concludes by comparing SdxL Lightning to LCM and SdxL Turbo, noting its simplicity in setup and suitability for quickly generating images for initial ideas. They also mention that while SdxL Lightning may not be ideal for animations, it is a good choice for fast image generation with average quality.
Mindmap
Keywords
💡SDXL Lightning
💡ComfyUI
💡Checkpoint Models
💡Laura's Files
💡Sampling Steps
💡CFG (Control Flow Graph)
💡Denoising
💡Scheduler
💡Latent Upscale
💡Nvidia GPU 4090
💡Animation Workflow
Highlights
SDXL Lightning is a new model created by Bite Den, launched 12 days ago for AI image generation.
The presenter waited to discuss SDXL Lightning until it became more stable, acknowledging the fast pace of AI development.
SDXL Lightning offers a demo page for users to experiment with text prompts for image generation.
The model uses low sampling steps and CFG number settings for efficient image generation.
Two-step, four-step, and eight-step models are available for download, each optimized for their respective step count.
All-in-one checkpoint models and UNet checkpoint models are provided for Comfy UI and Diffuser respectively.
Laura's files are also available for enhancing the model's performance in both Comfy UI and Diffuser.
The presenter will test the four-step model, which is considered the optimum for SDXL Lightning.
Setting the sampling step to four and CFG to one provides a good balance without oversaturating the image.
SDXL Lightning generates images quickly, with the first sampler set to 0 seconds for rapid results.
The model is simpler to connect than SDXL Turbo, requiring no extra custom nodes for image generation.
The presenter found that using the SGM uniform scheduler performs better with SDXL Lightning.
A new workflow diagram is proposed for integrating SDXL Lightning into Comfy UI with minimal frontend modifications.
The presenter demonstrates how to set up SDXL Lightning in Comfy UI with checkpoint models and Laura's files.
Large images (e.g., 1024x1024) can be generated in under a second using SDXL Lightning.
The presenter suggests using two samplers for even faster image generation.
SDXL Lightning does not include a VAE, so a custom VAE loader is necessary for certain tasks.
The presenter upscales the image twice using a latent image size of 1200x768 for enhanced detail.
SDXL Lightning is not recommended for animation workflows, similar to the limitations of SDXL Turbo.
The flexibility of SDXL Lightning allows for special fine-tuning or the use of additional Laura models for improved results.
The presenter emphasizes the suitability of SDXL Lightning for quickly generating images with good average quality at low sampling steps and CFG.