Model card
Stable Diffusion v1.4 is a latent diffusion model designed for high-efficiency text-to-image synthesis. Unlike proprietary cloud-based APIs, v1.4 is optimized for local deployment, allowing developers to run inference on consumer-grade GPUs. It excels at generating diverse visual assets, from photorealistic textures to stylized concept art, by mapping text embeddings to a compressed latent space. For developers, the primary value lies in its open weights and extensive community ecosystem; it integrates seamlessly with PyTorch and Diffusers, enabling custom fine-tuning via DreamBooth or LoRA to adapt the model to specific domains or brand identities.
Model files and versions
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.
CompVis/stable-diffusion-v1-4Install the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model CompVis/stable-diffusion-v1-4README.md is used as an example; replace it with another repository file when needed.
modelscope download --model CompVis/stable-diffusion-v1-4 README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('CompVis/stable-diffusion-v1-4')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/CompVis/stable-diffusion-v1-4.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/CompVis/stable-diffusion-v1-4.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
Discussions
Use this space to keep checking source information, usage experience and maintenance status.
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