Instructions to use louistichelman/controlnet_streetview_normalmap_res400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use louistichelman/controlnet_streetview_normalmap_res400 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("louistichelman/controlnet_streetview_normalmap_res400") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
controlnet-louistichelman/controlnet_streetview_normalmap_res400
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images below.
prompt: A realistic google streetview image, which was assigned a beauty-score of 16.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
prompt: A realistic google streetview image, which was assigned a beauty-score of 35.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
prompt: A realistic google streetview image, which was assigned a beauty-score of 16.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
prompt: A realistic google streetview image, which was assigned a beauty-score of 35.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
prompt: A realistic google streetview image, which was assigned a beauty-score of 23.188663, where scores are between 10 and 40 and higher scores indicate more beauty.
prompt: A realistic google streetview image, which was assigned a beauty-score of 31.616573, where scores are between 10 and 40 and higher scores indicate more beauty.

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]
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Model tree for louistichelman/controlnet_streetview_normalmap_res400
Base model
runwayml/stable-diffusion-v1-5