Diffusion Bee runs Stable Diffusion locally on Mac and offers a one click installer without extra dependencies.
nateraw/stable-diffusion-videos
Create videos with Stable Diffusion by exploring the latent space and morphing between text prompts.

About nateraw/stable-diffusion-videos
nateraw/stable-diffusion-videos is an open-source Python package for creating videos with Stable Diffusion by walking the latent space and morphing between text prompts. It installs with pip install stable_diffusion_videos and uses StableDiffusionWalkPipeline.walk() with prompts, seeds, interpolation steps, output directory, and generation settings.
It supports audio-synced videos where an audio file informs the interpolation rate, configurable height, width, guidance scale and inference steps, and a local interface launched with Interface(pipeline). On Apple M1, torch.float32 must be used because torch.float16 is not available on MPS.
Key features
- Morph between text prompts by interpolating Stable Diffusion latent space
- Set prompts, seeds, interpolation steps, output directory and name
- Adjust image height, width, guidance scale and inference steps
- Add audio file to align interpolation rate with beat
- Launch local interface with Interface pipeline wrapper
- Install package via pip install stable_diffusion_videos
- Open source under Apache-2.0 license
- Includes example scripts and notebooks for videos and music videos
- Supports audio-informed interpolation and configurable generation parameters
- Apple M1 requires torch.float32 because torch.float16 is not available on MPS
- Height and width must use multiples of 64 above 512 and multiples of 8 below 512
nateraw/stable-diffusion-videos at a glance
- Category
- AI & Machine Learning › AI Image Generators
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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