human_place / README.md
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---
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/human_place
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
![images_0)](./images_0.png)
## 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]