ControlNet
These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning. You can find some example images below.
Model source
- Kind
- ControlNet
- File size
- 4.66 GB
- Base model
- stabilityai/stable-diffusion-xl-base-1.0
- Version
- vdiffusion_pytorch_model
- Updated
- Oct 7, 2026
- Downloads
- 25
- Source
- Hugging Face
Source description
controlnet-x444/controlnet
These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning. You can find some example images below.
prompt: Three overlapping rectangular banners in blue, yellow, and green with white circular elements create a modern infographic design on a subtle gray gradient background. images_0) prompt: A series of vertical panels featuring vibrant half-circle designs in yellow, orange, green, blue, and purple on a white background, each with aligned text below, creating a modern and colorful infographic layout. images_1)
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
Sources
1 source
Sources
1 sourceVerified Oct 7
Model artifacts
1 artifact
Model artifacts
1 artifactcheckpoint-1000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 4.66 GB · SHA-256 394158a8c6ba…7dcf · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: stabilityai/stable-diffusion-xl-base-1.0 library_name: diffusers license: openrail++ inference: true tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - controlnet - diffusers-training --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # controlnet-x444/controlnet These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning. You can find some example images below. prompt: Three overlapping rectangular banners in blue, yellow, and green with white circular elements create a modern infographic design on a subtle gray gradient background.  prompt: A series of vertical panels featuring vibrant half-circle designs in yellow, orange, green, blue, and purple on a white background, each with aligned text below, creating a modern and colorful infographic layout.  ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]
Source context: 25 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo x444/controlnet
Source context: 5 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo x444/controlnet
