readme: ---
  language:
  - en
  license: creativeml-openrail-m
  thumbnail: "https://huggingface.co/Guizmus/DarkSoulsDiffusion/resolve/main/showcase.jpg"
  tags:
  - stable-diffusion
  - text-to-image
  - image-to-image
  inference: true
  ---
  
  # DarkSouls Diffusion
  <p>
  	<img src="https://huggingface.co/Guizmus/DarkSoulsDiffusion/resolve/main/showcase.jpg"/><br/>
  	This is a Dreamboothed Stable Diffusion model trained on the DarkSouls series Style.<br/>
  	The total dataset is made of 100 pictures, and the training has been done on runawayml 1.5 and the new VAE, with 2500 steps (LR1e-6) then 24k more steps (LR1e-7).<br/>
  	The token "DarkSouls Style" will bring in the new concept.<br/>
  	The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7 .
  	
  </p>
  
  [CKPT download link](https://huggingface.co/Guizmus/DarkSoulsDiffusion/resolve/main/DarkSoulsStyle_v1-3.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/DarkSoulsDiffusion"
  pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
  pipe = pipe.to("cuda")
  
  prompt = "a soldier engulfed in fire, DarkSouls Style"
  image = pipe(prompt).images[0]
  
  image.save("./DarkSouls Style.png")
  ```