---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
- image-to-image
library_name: "https://github.com/victorchall/EveryDream-trainer"
datasets:
- Guizmus/AnimeChanStyle
---

# AnimeChan Style
<p>
	This model was based on <a href="https://huggingface.co/naclbit/trinart_stable_diffusion_v2">Trinart</a> model.<br/>
	The dataset was a collaborative effort of the Stable Diffusion #anime channel, made of pictures from the users themselves using their different techniques.<br/>
	This was trained using EveryDream with a full caption of all training pictures. The dataset can be found <a href="">here</a>.<br/>
	<br/>
	The style will be called by the use of the token <b>AnimeChan Style</b>.<br/>
	<br/>
	To access this model, you can download the CKPT file below, or use the <a href="https://huggingface.co/Guizmus/AnimeChanStyle/tree/main">diffusers</a>
</p>

[CKPT download link](https://huggingface.co/Guizmus/AnimeChanStyle/resolve/main/AnimeChanStyle_v1.ckpt)

## 🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information,
please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).

You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().

```python
from diffusers import StableDiffusionPipeline
import torch

model_id = "Guizmus/AnimeChanStyle"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "A beautiful slime girl, AnimeChan Style"
image = pipe(prompt).images[0]

image.save("./AnimeChanStyle.png")
```

## License

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
The CreativeML OpenRAIL License specifies: 

1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content 
2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)