Stable Diffusion fine tuned on PokΓ©mon by Lambda Labs.
Put in a text prompt and generate your own PokΓ©mon 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 PokΓ©mon 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 PokΓ©mon 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 PokΓ©mon dataset
- Model weights in Diffusers format
- Original model weights
- Training code
Trained by Justin Pinkney (@Buntworthy) at Lambda Labs.
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