Create app.py

app.py

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+import gradio
+from transformers import pipeline
+import torch
+
+def get_completion(prompt):
+    return pipeline(prompt)['sample'][0]
+    
+def generate(prompt):
+    output = get_completion(prompt)
+    return output
+    
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Generation with Stable Diffusion")
+    with gr.Row():
+        with gr.Column(scale=4):
+            prompt = gr.Textbox(label="Your prompt") #Give prompt some real estate
+        with gr.Column(scale=1, min_width=50):
+            btn = gr.Button("Submit") #Submit button side by side!
+    with gr.Accordion("Advanced options", open=False): #Let's hide the advanced options!
+            negative_prompt = gr.Textbox(label="Negative prompt")
+            with gr.Row():
+                with gr.Column():
+                    steps = gr.Slider(label="Inference Steps", minimum=1, maximum=100, value=25,
+                      info="In many steps will the denoiser denoise the image?")
+                    guidance = gr.Slider(label="Guidance Scale", minimum=1, maximum=20, value=7,
+                      info="Controls how much the text prompt influences the result")
+                with gr.Column():
+                    width = gr.Slider(label="Width", minimum=64, maximum=512, step=64, value=512)
+                    height = gr.Slider(label="Height", minimum=64, maximum=512, step=64, value=512)
+    output = gr.Image(label="Result") #Move the output up too
+
+    btn.click(fn=generate, inputs=[prompt,negative_prompt,steps,guidance,width,height], outputs=[output])
+
+demo.launch()