#!pip install --upgrade pip !pip install diffusers==0.9.0 #it is still work for 0.9.0, if problem get, use below command !pip install --upgrade diffusers transformers scipy #!pip install transformers==4.24.0 #<--able go to no error from tensorflow.keras.models import load_model import cv2 import tensorflow as tf import os from matplotlib import pyplot as plt import numpy as np import torch from diffusers import StableDiffusionPipeline from torch import autocast import gradio import gradio as gr pipe = StableDiffusionPipeline.from_pretrained("Fung804/makoto-shinkai-v2", torch_dtype=torch.float16) pipe = pipe.to("cuda") def txt2img(prompt): image = pipe(prompt +", realistic, highly detailed, high quality", height=512, width=512, negative_prompt = "((low quality)),((poor quality)),((clone)),retro style, bad anatomy,((lowres)), blurry, (worst quality), ((low quality)), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, errorretro style ,bad anatomy,((lowres)), blurry, (worst quality), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, error", guidance_scale = 7.5,num_inference_steps = 50).images[0] image.save("sd_image.png") return image generate = gr.Interface(fn = txt2img, inputs="text",outputs="image",allow_flagging="never") generate.launch(inline = False)