camenduru / story-diffusion

StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation

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  • 935 runs
  • GitHub
  • Paper
  • License
Run with an API
Playground API Examples README Versions

Examples

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Run time and cost

This model costs approximately $0.080 to run on Replicate, or 12 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 (Large) GPU hardware. Predictions typically complete within 111 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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📋 Tutorial

  • Enter a Textual Description for Character, if you add the Ref-Image, making sure to follow the class word you want to customize with the trigger word: img, such as: man img or woman img or girl img.
  • Enter the prompt array, each line corrsponds to one generated image.
  • Choose your preferred style template.
  • If you need to change the caption, add a # at the end of each line. Only the part after the # will be added as a caption to the image.)
  • [NC] symbol (The [NC] symbol is used as a flag to indicate that no characters should be present in the generated scene images. If you want do that, prepend the “[NC]” at the beginning of the line. For example, to generate a scene of falling leaves without any character, write: “[NC] The leaves are falling.”), Currently, support is only using Textual Description

🕸 Replicate

https://replicate.com/camenduru/story-diffusion

🧬 Code

https://github.com/HVision-NKU/StoryDiffusion

📄 Paper

https://arxiv.org/abs/2405.01434

🌐 Page

https://storydiffusion.github.io/

https://replicate.com