ControlNet Inpainting Shuffle
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
Fuente del modelo
- Tipo
- ControlNet
- Tamaño del archivo
- 1,35 GB
- Modelo base
- runwayml/stable-diffusion-v1-5
- Versión
- vdiffusion_pytorch_model
- Actualizado
- 20 oct 2026
- Descargas
- 13
- Fuente
- Hugging Face
Descripción de la fuente
controlnet-chaeyeonl33/controlnet_inpainting_shuffle
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
prompt: Temp7 11,Temp5 11,Temp6 11,Temp2 16,Temp4 11,B2Pwr 3000,SPwr 2800,Temp3 11,GasE 900,Time 200,GasA 190,Temp1 16,Step A1 images_0) prompt: SPwr 2800,Temp5 11,GasA 190,Temp4 11,Temp1 16,Time 200,Temp6 11,GasE 900,B2Pwr 3000,Temp2 16,Temp3 11,Step A1,Temp7 11 images_1) prompt: Temp5 11,GasE 900,Temp4 11,Temp1 16,Temp7 11,Step A1,Temp2 16,Time 200,Temp6 11,Temp3 11,SPwr 3000,B2Pwr 3000,GasA 190 images_2) prompt: Step A1,Time 200,GasA 190,Temp3 11,GasE 900,Temp1 16,Temp7 11,Temp5 11,Temp6 11,Temp4 11,Temp2 16,B2Pwr 2600,SPwr 3000 images_3)
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]
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 8 ago
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactocheckpoint-1000/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1,35 GB · SHA-256 d9f9d3ea8da2…4e58 · Hugging Face
DescargarExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- base_model: runwayml/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m inference: true tags: - stable-diffusion - stable-diffusion-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-chaeyeonl33/controlnet_inpainting_shuffle These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below. prompt: Temp7 11,Temp5 11,Temp6 11,Temp2 16,Temp4 11,B2Pwr 3000,SPwr 2800,Temp3 11,GasE 900,Time 200,GasA 190,Temp1 16,Step A1  prompt: SPwr 2800,Temp5 11,GasA 190,Temp4 11,Temp1 16,Time 200,Temp6 11,GasE 900,B2Pwr 3000,Temp2 16,Temp3 11,Step A1,Temp7 11  prompt: Temp5 11,GasE 900,Temp4 11,Temp1 16,Temp7 11,Step A1,Temp2 16,Time 200,Temp6 11,Temp3 11,SPwr 3000,B2Pwr 3000,GasA 190  prompt: Step A1,Time 200,GasA 190,Temp3 11,GasE 900,Temp1 16,Temp7 11,Temp5 11,Temp6 11,Temp4 11,Temp2 16,B2Pwr 2600,SPwr 3000  ## 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: 13 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo chaeyeonl33/controlnet_inpainting_shuffle
Source context: 2 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo chaeyeonl33/controlnet_inpainting_shuffle
