| import gradio as gr | |
| import torch | |
| from diffusers import StableDiffusion3Pipeline | |
| def image_generation(prompt): | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pipeline = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", | |
| torch_dtype=torch.float16 if device == "cuda" else torch.float32, | |
| text_encoder_3 =None, | |
| tokenizer_3 =None) | |
| pipeline.enable_model_cpu_offload() | |
| # pipeline.to(device) | |
| image = pipeline( | |
| prompt=prompt, | |
| negative_prompt="blurred, ugly, watermark, low resolution, blurry", | |
| num_inference_steps=40, | |
| height=1024, | |
| width=1024, | |
| guidance_scale=9.0 | |
| ).images[0] | |
| return image | |
| # image_generation("A magician cat doing spell") | |
| interface= gr.Interface( | |
| fn=image_generation, | |
| inputs = gr.Textbox(lines=2, placeholder="Enter your Prompt..."), | |
| outputs =gr.Image(type="pil"), | |
| title ="@GenAiLearnivers Project 9: Image creation using Stable Diffusion 3 Model", | |
| description="This application will be used to generate awesome images using SD3 model" | |
| ) | |
| interface.launch() | |