Create app.py

app.py

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+from diffusers import DiffusionPipeline
+import torch
+import gradio as gr
+
+
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
+pipe.to("cuda")
+
+def generate_image(prompt):
+    result = pipe(prompt=prompt)
+    image = result.images[0]
+    # Convert the image tensor to a format suitable for Gradio (assuming image is in [C, H, W] format)
+    return image.permute(1, 2, 0).cpu().numpy()
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
+    outputs="image",
+    live=True,
+)
+
+iface.launch(share=True)
+