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English Stable Diffusion Pokemon Model Card

Stable-Diffusion-Pokemon-en is a English-specific latent text-to-image diffusion model capable of generating Pokemon images given any text input.

This model was trained by using a powerful text-to-image model, diffusers For more information about our training method, see train_text_to_image.py.

Model Details

Examples

Firstly, install our package as follows. This package is modified 🤗's Diffusers library to run English Stable Diffusion.

pip install diffusers==0.4.1

Run this command to log in with your HF Hub token if you haven't before:

huggingface-cli login

Running the pipeline with the LMSDiscreteScheduler scheduler:

import torch
import pandas as pd

from torch import autocast
from diffusers import LMSDiscreteScheduler, StableDiffusionPipeline

scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012,
     beta_schedule="scaled_linear", num_train_timesteps=1000)

#pretrained_model_name_or_path = "en_model_26000"
pretrained_model_name_or_path = "svjack/Stable-Diffusion-Pokemon-en"
pipe = StableDiffusionPipeline.from_pretrained(pretrained_model_name_or_path,
                                                           scheduler=scheduler, use_auth_token=True)

pipe = pipe.to("cuda")

disable safety_checker
pipe.safety_checker = lambda images, clip_input: (images, False)

imgs = pipe("A cartoon character with a potted plant on his head",
                    num_inference_steps = 100
)
image = imgs.images[0]
    
image.save("output.png")

Generator Results comparison

https://github.com/svjack/Stable-Diffusion-Pokemon

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