| from diffusers import DiffusionPipeline | |
| import gradio as gr | |
| import numpy as np | |
| import random | |
| import torch | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| dtype = torch.float16 | |
| pipe = DiffusionPipeline.from_pretrained("Chan-Y/Chan-Y-Cyber-Stable-Realistic", | |
| torch_dtype=torch.float16).to(device) | |
| MAX_SEED = 999999999999999 | |
| MAX_IMAGE_SIZE = 1344 | |
| def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)): | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| generator = torch.Generator().manual_seed(seed) | |
| image = pipe( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_inference_steps, | |
| width=width, | |
| height=height, | |
| generator=generator | |
| ).images[0] | |
| return image, seed | |
| examples = [ | |
| ["Batman, cute modern Disney style, Pixar 3d portrait, ultra detailed, gorgeous, 3d zbrush, trending on dribbble, 8k render.", | |
| "", | |
| 12345, | |
| 50] | |
| ] | |
| css = """ | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 580px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown(f""" | |
| # Demo [Chan-Y/Stable-Flash-Lightning](https://huggingface.co./Chan-Y/Chan-Y-Cyber-Stable-Realistic) | |
| by Cihan Yalçın | My [LinkedIn](https://www.linkedin.com/in/chanyalcin/) My [GitHub](https://github.com/g-hano) | |
| """) | |
| with gr.Row(): | |
| prompt = gr.Textbox( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| container=False, | |
| ) | |
| run_button = gr.Button("Run", scale=0) | |
| result = gr.Image(label="Result | |