cjwbw / compositional-vsual-generation-with-composable-diffusion-models-pytorch

Composable Diffusion

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Examples

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Run time and cost

This model costs approximately $0.0047 to run on Replicate, or 212 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 T4 GPU hardware. Predictions typically complete within 21 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This is a cog implementation of https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

Composable Diffusion

Project Page

This is the official codebase for Compositional Visual Generation with Composable Diffusion Models.

Compositional Visual Generation with Composable Diffusion Models
Nan Liu Shuang Li Yilun Du Antonio Torralba Joshua B. Tenenbaum

  • The codebase is built upon GLIDE.

Citing our Paper

If you find our code useful for your research, please consider citing 

@article{liu2022compositional,
  title={Compositional Visual Generation with Composable Diffusion Models},
  author={Liu, Nan and Li, Shuang and Du, Yilun and Torralba, Antonio and Tenenbaum, Joshua B},
  journal={arXiv preprint arXiv:2206.01714},
  year={2022}
}