license: creativeml-openrail-m
library_name: diffusers
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- controlnet
- diffusers-training
base_model: runwayml/stable-diffusion-v1-5
inference: true
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]