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ComfyUI-TCD integrates ComfyUI with the TCD framework, enhancing user interface capabilities by leveraging TCD's features. This extension streamlines UI development, offering a seamless experience for developers.
ComfyUI-TCD is an extension for the ComfyUI platform that implements the TCD (Trajectory Consistency Distillation) sampler. This extension is inspired by Consistency Models and Latent Consistency Models (LCM) and offers a novel approach to distilling pre-trained diffusion models. The primary advantage of using TCD is its ability to generate high-quality, detailed images with fewer denoising steps compared to traditional methods like LCM. This makes it particularly useful for AI artists looking to create detailed and high-quality images efficiently.
ComfyUI-TCD works by distilling a pre-trained diffusion model into a more efficient model that can produce high-quality images in fewer steps. The process involves reducing the number of denoising steps required to generate an image, which speeds up the image creation process without sacrificing quality. TCD achieves this by controlling the strength of random noise during the denoising process, allowing for fine-tuning of image details.
eta
, which controls the strength of random noise.steps
parameter in the KSampler
node.simple
and sgm_uniform
. The simple
scheduler generates results similar to diffusers, while sgm_uniform
is recommended by the ComfyUI author.denoise
parameter in the KSampler
node.eta
value results in more randomness and potentially more detailed images.ComfyUI-TCD supports various models, including:
eta
parameter to control the level of random noise.simple
and sgm_uniform
to see which works best for your setup.eta
parameter to control the strength of random noise during denoising. Higher values result in more detailed images.eta
value of 0.3 and adjust based on your specific needs. Experiment with different steps
and scheduler
settings to find the best combination.For additional resources, tutorials, and community support, consider exploring the following:
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