 use with LoRA. It effectively eliminates the need to conduct expensive fine-tuning runs as LoRA training concerns just a few number of parameters compared to full fine-tuning. During inference, the LCMScheduler comes to the advantage as it enables very few-steps inference without compromising the quality. We recommend to disable guidance_scale by setting it 0. The model is trained to follow prompts accurately
even without using guidance scale.