LatentDiffusionModel
bCloud LLC · Software Development
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 9 captures on record
What the publisher says
As described on Microsoft Marketplace.
**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:
Show the rest of the publisher’s description (11 more lines)
- 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
$ cd /opt/latent-diffusion/latent-diffusion
source ldm-env/bin/activate
$python -c "import ldm; print('✅ LDM working')"
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.
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
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Vendor
External enrichment · as of 2026-08-29
Sources
Publisher resources
1 linkLinked repositories
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