Log ControlNet SDXL
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.
Source du modèle
- Type
- ControlNet
- Taille du fichier
- 4,66 GB
- Modèle de base
- stabilityai/stable-diffusion-xl-base-1.0
- Version
- vdiffusion_pytorch_model
- Mis à jour
- 7 oct. 2026
- Téléchargements
- 1
- Source
- Hugging Face
Description de la source
controlnet-JYChung/log_controlnet_sdxl
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: red circle with blue background images_0) prompt: cyan circle with brown floral background 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 sourceVérifié 7 oct.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactcheckpoint-1000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 4,66 GB · SHA-256 5a1eb7c87eda…174b · Hugging Face
Download fileExtraits de sources
3 extraits
Extraits de sources
3 extraits--- 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-JYChung/log_controlnet_sdxl 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: red circle with blue background  prompt: cyan circle with brown floral background  ## 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: 1 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo JYChung/log_controlnet_sdxl
Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo JYChung/log_controlnet_sdxl
