import gradio as gr import torch import numpy as np import modin.pandas as pd from PIL import Image from diffusers import DiffusionPipeline device = "cuda" if torch.cuda.is_available() else "cpu" pipe = DiffusionPipeline.from_pretrained("prompthero/openjourney-v2", torch_dtype=torch.float16, safety_checker=None) pipe = pipe.to(device) def genie (prompt, scale, steps, Seed): generator = torch.Generator(device=device).manual_seed(Seed) images = pipe(prompt, num_inference_steps=steps, guidance_scale=scale, generator=generator).images[0] return images gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), gr.Slider(1, maximum=15, value=10, step=.25, label='Prompt Guidance Scale:', interactive=True), gr.Slider(1, maximum=100, value=50, step=1, label='Number of Iterations: 50 is typically fine.'), gr.Slider(minimum=1, step=1, maximum=987654321, randomize=True, interactive=True)], outputs=gr.Image(label='512x512 Generated Image'), title="OpenJourney V2 GPU", description="OJ V2 GPU. Ultra Fast, now running on a T4", article = "Code Monkey: Manjushri").launch(debug=True, max_threads=True)