|
--- |
|
base_model: cagliostrolab/animagine-xl-3.1 |
|
library_name: diffusers |
|
license: openrail++ |
|
tags: |
|
- stable-diffusion-xl |
|
- stable-diffusion-xl-diffusers |
|
- text-to-image |
|
- diffusers |
|
- controlnet |
|
- diffusers-training |
|
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-dyamagishi/output |
|
|
|
These are controlnet weights trained on cagliostrolab/animagine-xl-3.1 with new type of conditioning. |
|
You can find some example images below. |
|
|
|
prompt: outdoors, scenery, cloud, multiple_girls, sky, day, tree, grass, architecture, 2girls, blue_sky, building, standing, skirt, long_hair, mountain, east_asian_architecture, from_behind, castle, facing_away, black_skirt, school_uniform, pagoda, waterfall, white_shirt, white_hair, shirt, cloudy_sky, bag |
|
 |
|
|
|
|
|
|
|
## 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] |
