ControlNet Quilt1m 256
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
Model source
- Kind
- ControlNet
- File size
- 1.35 GB
- Base model
- runwayml/stable-diffusion-v1-5
- Version
- vdiffusion_pytorch_model
- Updated
- Oct 8, 2026
- Downloads
- 30
- Source
- Hugging Face
Source description
controlnet-wjworld/controlnet_quilt1m_256
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
Comming Soon!
After I test and generated the images, I will upload the images.
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 8
Model artifacts
1 artifact
Model artifacts
1 artifactcheckpoint-36000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1.35 GB · SHA-256 a389540ebf3a…93a9 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- license: creativeml-openrail-m library_name: diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training base_model: runwayml/stable-diffusion-v1-5 inference: true --- <!-- 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-wjworld/controlnet_quilt1m_256 These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. # Comming Soon! After I test and generated the images, I will upload the images. ## 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: 30 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo wjworld/controlnet_quilt1m_256
Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo wjworld/controlnet_quilt1m_256
