import gradio as gr import spaces import torch from diffusers import DiffusionPipeline model_name = 'UnfilteredAI/NSFW-gen-v2' pipe = DiffusionPipeline.from_pretrained( model_name, torch_dtype=torch.float16 ) pipe.to('cuda') @spaces.GPU def generate(prompt, negative_prompt, num_inference_steps, guidance_scale, width, height, num_samples): return pipe( prompt, negative_prompt=negative_prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, width=width, height=height, num_images_per_prompt=num_samples ).images gr.Interface( fn=generate, inputs=[ gr.Text(label="Prompt"), gr.Text("", label="Negative Prompt"), gr.Number(7, label="Number inference steps"), gr.Number(3, label="Guidance scale"), gr.Number(512, label="Width"), gr.Number(512, label="Height"), gr.Number(1, label="# images"), ], outputs=gr.Gallery(), ).launch()