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.