**Latent Diffusion Models (LDM)** are an open-source Python framework developed by **CompVis** for generating high-quality images from text prompts or other conditioning signals. They allow developers and researchers to build efficient generative pipelines for image synthesis, inpainting, super-resolution, and more, providing modular and extensible solutions for latent-space diffusion modeling.

Features of Latent Diffusion Models:

• Supports a variety of diffusion-based generative models (e.g., DDPM, conditional LDMs, text-to-image LDMs).
• Provides end-to-end pipelines for image generation, conditioning on text, images, or masks.
• Works with Python and PyTorch, supporting both CPU and GPU environments.
• Includes pre-trained models and example checkpoints for testing generative performance.
• Modular, extensible, and widely used in AI research, creative applications, and automated image synthesis.

To check the installed version of Latent Diffusion Models in your environment:

 
$ sudo su 
$ sudo apt update 
$ source /opt/ldm-env/bin/activate 
$python -c "import torch; print(torch.__version__)"
 

Disclaimer: LDMs are developed and maintained by CompVis. They provide general-purpose latent-space image generation tools, but output quality depends on proper application, prompt design, and dataset-specific considerations. Always refer to official documentation or the Python package repository for the most accurate and up-to-date information.