readme: ---
  language: 
    - en
  thumbnail: TBD
  tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  datasets:
  - ChristophSchuhmann/improved_aesthetics_6plus
  ---
  
  
  # Mini Stable Diffusion (miniSD)
  
  MiniSD is a latent text-to-image diffusion model that has been conditionned on 256x256 images through finetuning.
  
  ## Examples
  
  WIP
  
  ## Usage
  
  ```
  !pip install diffusers==0.3.0
  !pip install transformers scipy ftfy
  ```
  
  ```
  import torch
  from diffusers import StableDiffusionPipeline
  from torch import autocast
  
  # TODO: change model_id to "lambdalabs/miniSD"
  pipe = StableDiffusionPipeline.from_pretrained("eolecvk/model-test", torch_dtype=torch.float16)  
  pipe = pipe.to("cuda")
  
  prompt = "Yoda"
  scale = 10
  n_samples = 4
  
  # Sometimes the nsfw checker is confused, you can disable it at your own risk here
  disable_safety = False
  
  if disable_safety:
    def null_safety(images, **kwargs):
        return images, False
    pipe.safety_checker = null_safety
  
  with autocast("cuda"):
    images = pipe(n_samples*[prompt], guidance_scale=scale).images
  
  for idx, im in enumerate(images):
    im.save(f"{idx:06}.png")
  ```
  
  