lucataco / lcm-ssd-1b

Latent Consistency Model (LCM): SSD-1B, is a LCM distilled version that reduces the number of inference steps needed to only 2 - 8 steps

  • Public
  • 1.6K runs
  • GitHub
  • Paper
  • License

Run time and cost

This model costs approximately $0.0013 to run on Replicate, or 769 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A40 GPU hardware. Predictions typically complete within 3 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Implementation of latent-consistency/lcm-ssd-1b

Latent Consistency Model (LCM): SSD-1B Latent Consistency Model (LCM) was proposed in Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference by Simian Luo, Yiqin Tan et al. and Simian Luo, Suraj Patil, and Daniel Gu succesfully applied the same approach to create LCM for SDXL.

This checkpoint is a LCM distilled version of segmind/SSD-1B that allows to reduce the number of inference steps to only between 2 - 8 steps.