Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Load the model on CPU
+model_id = "sergey-leshchenko/flux-realismo"
+pipe = StableDiffusionPipeline.from_pretrained(model_id)
+pipe.to("cpu")
+
+def generate(prompt, guidance_scale=7.5, steps=25):
+    image = pipe(prompt, guidance_scale=guidance_scale, num_inference_steps=steps).images[0]
+    return image
+
+# Gradio interface
+gr.Interface(
+    fn=generate,
+    inputs=[
+        gr.Textbox(label="Prompt", placeholder="Describe your image..."),
+        gr.Slider(minimum=1, maximum=20, value=7.5, step=0.5, label="Guidance Scale"),
+        gr.Slider(minimum=10, maximum=50, value=25, step=1, label="Inference Steps")
+    ],
+    outputs=gr.Image(type="pil"),
+    title="Flux-Realismo Image Generator (CPU)",
+    description="Generate realistic images using the Flux-Realismo model on CPU. May be slow."
+).launch()