animate-diff

Maintainer: lucataco

Total Score

256

Last updated 9/19/2024
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API specView on Replicate
Github linkView on Github
Paper linkView on Arxiv

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Model overview

animate-diff is a text-to-image diffusion model created by lucataco that can animate your personalized diffusion models. It builds on similar models like animate-diff, MagicAnimate, and ThinkDiffusionXL to offer temporal consistency and the ability to generate high-quality animated images from text prompts.

Model inputs and outputs

animate-diff takes in a text prompt, along with options to select a pretrained module, set the seed, adjust the number of inference steps, and control the guidance scale. The model outputs an animated GIF that visually represents the prompt.

Inputs

  • Path: Select a pre-trained module
  • Seed: Set the random seed (0 for random)
  • Steps: Number of inference steps (1-100)
  • Prompt: The text prompt to guide the image generation
  • N Prompt: A negative prompt to exclude certain elements
  • Motion Module: Select a pre-trained motion model
  • Guidance Scale: Adjust the strength of the text prompt guidance

Outputs

  • Animated GIF: The model outputs an animated GIF that brings the text prompt to life

Capabilities

animate-diff can create visually stunning, temporally consistent animations from text prompts. It is capable of generating a variety of scenes and subjects, from fantasy landscapes to character animations, with a high level of detail and coherence across the frames.

What can I use it for?

With animate-diff, you can create unique, personalized animated content for a variety of applications, such as social media posts, presentations, or even short animated films. The ability to fine-tune the model with your own data also opens up possibilities for creating branded or custom animations.

Things to try

Experiment with different prompts and settings to see the range of animations the model can produce. Try combining animate-diff with other Replicate models like MagicAnimate or ThinkDiffusionXL to explore the possibilities of text-to-image animation.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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