Upload app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
+
+
+pipe = DiffusionPipeline.from_pretrained(
+    "segmind/tiny-sd",
+    torch_dtype=torch.float32
+)
+
+pipe = pipe.to("cpu")
+
+
+def generate_image(prompt):
+    image = pipe(prompt).images[0]
+    return image
+
+demo = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter Prompt"),
+    outputs=gr.Image(label="Generated Image"),
+    title="Tiny Stable Diffusion Demo"
+)
+
+demo.launch()