Stable Diffusion fine tuned on Pokémon by Lambda Labs .

Put in a text prompt and generate your own Pokémon character, no "prompt engineering" required!

If you want to find out how to train your own Stable Diffusion variants, see this example from Lambda Labs.

Girl with a pearl earring, Cute Obama creature, Donald Trump, Boris Johnson, Totoro, Hello Kitty

Usage

!pip install diffusers==0.3.0
!pip install transformers scipy ftfy

import torch
from diffusers import StableDiffusionPipeline
from torch import autocast

pipe = StableDiffusionPipeline.from_pretrained("lambdalabs/sd-pokemon-diffusers", torch_dtype=torch.float16)  
pipe = pipe.to("cuda")

prompt = "Yoda"
scale = 10
n_samples = 4

# Sometimes the nsfw checker is confused by the Pokémon images, 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")

Model description

Trained on BLIP captioned Pokémon images using 2xA6000 GPUs on Lambda GPU Cloud for around 15,000 step (about 6 hours, at a cost of about $10).

Links

• Lambda Diffusers
• Captioned Pokémon dataset
• Model weights in Diffusers format
• Original model weights
• Training code

Trained by Justin Pinkney ( @Buntworthy ) at Lambda Labs .