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MODEL Listed

Stable Diffusion XL

Stable Diffusion XL (SDXL) is a significant architectural leap in latent diffusion, utilizing a dual-encoder system to deliver higher resolution outputs and improved prompt adherence compared to its predecessors. With 3.5B parameters, it effectively handles complex compositions and photorealistic textures without requiring the heavy prompt engineering typically needed for smaller models. For developers, SDXL is highly versatile; its open-weights nature allows for local deployment, fine-tuning via LoRA, and seamless integration into existing pipelines via Diffusers or ComfyUI. It is particularly suited for production-grade asset generation, conceptual art, and applications requiring precise control over image geometry and style.

Stability AItext-to-image
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01 / MODEL CARD

Model card

Stable Diffusion XL (SDXL) is a significant architectural leap in latent diffusion, utilizing a dual-encoder system to deliver higher resolution outputs and improved prompt adherence compared to its predecessors. With 3.5B parameters, it effectively handles complex compositions and photorealistic textures without requiring the heavy prompt engineering typically needed for smaller models. For developers, SDXL is highly versatile; its open-weights nature allows for local deployment, fine-tuning via LoRA, and seamless integration into existing pipelines via Diffusers or ComfyUI. It is particularly suited for production-grade asset generation, conceptual art, and applications requiring precise control over image geometry and style.

Model typetext-to-image
ProviderStability AI
LicenseCreativeML Open RAIL++-M
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
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Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: stabilityai/stable-diffusion-xl-base-1.0
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model stabilityai/stable-diffusion-xl-base-1.0
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model stabilityai/stable-diffusion-xl-base-1.0 README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('stabilityai/stable-diffusion-xl-base-1.0')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/stabilityai/stable-diffusion-xl-base-1.0.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/stabilityai/stable-diffusion-xl-base-1.0.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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