import os os.system("pip install gradio diffusers torch") import gradio as gr from diffusers import StableDiffusionXLPipeline import torch pipe = StableDiffusionXLPipeline.from_pretrained( "segmind/SSD-1B", torch_dtype=torch.float16, use_safetensors=True, variant="fp16" ) pipe.to("cuda") def generate_image(prompt, neg_prompt): image = pipe( prompt=prompt, negative_prompt=neg_prompt ).images[0] return image prompt = gr.Text( label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False, ) neg_prompt = gr.Text( label="Negative Prompt", show_label=False, max_lines=1, placeholder="Enter your negative prompt", container=False, ) iface = gr.Interface( fn=generate_image, inputs=[prompt, neg_prompt], outputs="image", title="Text to Image Generation", examples=[ ["a painting of a cute cat sitting on a chair", "ugly, blurry"], ["an astronaut riding a horse on mars", "poorly drawn"] ], allow_flagging=False ) iface.launch(share=True)