Stable-Diffusion-Pokemon-en is a English-specific latent text-to-image diffusion model capable of generating Pokemon images given any text input.
- Developed by: Zhipeng Yang
- Model type: Diffusion-based text-to-image generation model
- Language(s): English
- License: The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.
- Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Latent Diffusion Model (LDM) that used Stable Diffusion as a pre-trained model.
- Resources for more information: https://github.com/svjack/Stable-Diffusion-Pokemon
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:
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 image.save("output.png")
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Inference API has been turned off for this model.