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import torch | |
import gradio as gr | |
from diffusers import StableDiffusionPipeline | |
class CFG: | |
device = 'cpu' | |
seed = 42 | |
Generator = torch.Generator(device).manual_seed(seed) | |
image_gen_steps = 35 | |
image_gen_model_id = 'stabilityai/stable-diffusion-2' | |
image_gen_size = (400, 400) | |
image_gen_guidance_scale = 9 | |
image_gen_model = StableDiffusionPipeline.from_pretrained( | |
CFG.image_gen_model_id, torch_dtype=torch.float32, | |
revision="fp16", use_auth_token='hf_pxvzpoafqjfkELFKMLTESNpvmyvkTVuD01' , guidance_scale=9 | |
) | |
apply = image_gen_model.to(CFG.device) | |
def generate_image(prompt): | |
image = apply( | |
prompt, num_inference_steps=CFG.image_gen_steps, | |
generator=CFG.generator , | |
guidance_scale=CFG.image_gen_guidance_scale | |
).image[0] | |
image = image.resize(CFG.image_gen_size) | |
return image | |
) | |
title = "ุชุตูููุฑ" | |
description = "ุฃุฏุฎู ูุต ูุญูููุง ูู ุตูุฑู" | |
iface = gr.interface(fn=generate_image, inputs = "text", outputs = "image" , title= title , description=description) | |
iface.launch( | |
) | |