🔎 What is LCM and how does it work?
LCM stands for Latent Consistency Model, which is a novel technique for accelerating text-to-image generation tasks. LCM are distilled from pre-trained latent diffusion models (LDM), which are powerful generative models that can produce high-quality images from text prompts. LCM learn to mimic the behavior of LDM, but with much fewer inference steps and lower computational cost. LCM achieve this by using a latent consistency loss, which ensures that the latent codes of LCM are close to those of LDM at each step. LCM also use a LoRA distillation method, which reduces the memory consumption and improves the image quality.
It’s like the old one but better one.
Recommended parameters for both versions are almost the same as before, with a few improvements and changes.
Achieving super high-quality images with super low steps and CFG Scale is actually really challenging. I performed countless experiments, and each time, I didn’t achieve what i wanted.
So, I decided to improve the previous version. Now, this version is pretty good. With in 8-10 steps and 4-5 CFG Scale, you will get results comparable to the normal SDXL with 30-40 steps.
If you like my work, then please share your feedback in the comment section and don't forget to share your work. I'm excited to see them.
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✅Recommended Parameters✅
VAE : SDXL VAE
Sampling Method : DPM++ 2M Karras | You can use different sampling methods, but personally, I'm a fan of DPM++ 2M Karras. So, if you want to try another sampler, please give it a try and share your experience with me
Sampling Steps : 8➡️16 | safe starting 8/10
CFG Scale : 3➡️6 | 4/5 safe starting
Clip Skip : 1
Upscaler : 4x-UltraSharp
Hires Steps : 4➡️10
Denoising Strength : 0.1➡️0.5
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User Guide 📢
I'm here to help you create awesome visuals! Remember, I can't be responsible if your content breaks any laws or community guidelines ❌
Let's collaborate creatively, follow the rules, and make something amazing together 🎨
📜 If you have questions, feel free to ask anytime! 🌟