GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Stable-diffusion is a latent text-to-image diffusion model for generating images from text descriptions, using a conda environment for setup.
Good fit when
- When you need to generate images from text descriptions with a high degree of detail and quality, as stable-diffusion is known for its ability to produce highly detailed images.
- If you are working within a conda environment and prefer to manage dependencies through conda and pip, as stable-diffusion provides specific instructions for setting up a conda environment.
Avoid when
- If your project requires real-time image generation, as stable-diffusion may not be optimized for real-time performance and could be slower compared to some alternatives.
- When you are looking for a tool that supports a wide range of customization options for the diffusion process, as stable-diffusion might have a more limited set of parameters for customization.
- Requirements:
- A conda environment named `ldm` is required, which can be created and activated using the provided commands.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (822d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No lockfile
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/CompVis/stable-diffusionHow it fits your stack(5)
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Evidence and technical details
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Overview
CompVis/stable-diffusion is a repository that provides a latent text-to-image diffusion model for generating images from text descriptions.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Sep 18, 2026
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
pip install transformers==4.19.2 diffusers invisible-watermarkSource link
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README
Requirements A suitable conda environment named can be created and activated with: You can also update an existing latent diffusion environment by running
For agents
This page has a .md twin and JSON over the API.