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from diffusers import StableDiffusionPipeline | |
import torch | |
import gradio as gr | |
import accelerate | |
models=[ | |
gr.Interface.load("Marvel","models/ItsJayQz/Marvel_WhatIf_Diffusion", "whatif style"), | |
gr.Interface.load("Cyberpunk Anime Diffusion", "models/DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style"), | |
gr.Interface.load("Portrait plus", "models/wavymulder/portraitplus", "portrait+ style"), | |
gr.Interface.load("classic Disney", "models/nitrosocke/classic-anim-diffusion", "classic disney style"), | |
gr.Interface.load("vintedois", "models/22h/vintedois-diffusion-v0-1", "vintedois style"), | |
gr.Interface.load("dreamlike", "models/dreamlike-art/dreamlike-diffusion-1.0","dreamlike style"), | |
gr.Interface.load("SD21","models/stabilityai/stable-diffusion-2-1", "sd21 default style") | |
] | |
def TextToImage(Prompt,model): | |
model_id = model | |
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.get_default_dtype()) | |
pipe = pipe.to("cpu") | |
prompt = Prompt | |
image = pipe(prompt).images[0] | |
return image | |
sandbox = gr.Interface(fn=TextToImage, | |
inputs=["text", gr.Dropdown(models)], | |
outputs="image", | |
title='AlStable Text to Image') | |
sandbox.launch() |