The text-to-image generation model PIXART-δ has achieved a significant breakthrough in real-time applications. It cleverly combines Latent Consistency Models and ControlNet, and effectively improves the model's control capabilities and training efficiency through the innovative ControlNet-Transformer design and Latent Consistency Distillation algorithm. This model surpasses existing similar models in both inference speed and performance, setting a new benchmark in the field of text-to-image generation.
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PIXART-δ integrates Latent Consistency Models and ControlNet to accelerate real-time applications. Through the innovative ControlNet-Transformer design and Latent Consistency Distillation algorithm, the control performance and training efficiency of the model are improved. In terms of inference speed and performance, PIXART-δ surpasses similar models and becomes the leading model in the text-to-image field.
The emergence of PIXART-δ marks an important leap in text-to-image generation technology. Its efficient performance and powerful control capabilities will bring innovation to more application scenarios. It is worth looking forward to future development and applications.