:tada: init

app.py

@@ -1,7 +1,45 @@
 import gradio as gr
+import spaces
+import torch
+from diffusers import DiffusionPipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+@spaces.GPU()
+@torch.inference_mode()
+def inference(
+    model_id: str,
+    prompt: str,
+    negative_prompt: str = "",
+    progress=gr.Progress(track_tqdm=True),
+):
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+    pipe = DiffusionPipeline.from_pretrained(
+        model_id,
+        torch_dtype=torch.float16,
+    ).to(device)
+
+    image = pipe(
+        prompt,
+        negative_prompt=negative_prompt,
+    ).images[0]
+
+    return image
+
+
+if __name__ == "__main__":
+    demo = gr.Interface(
+        fn=inference,
+        inputs=[
+            gr.Text(
+                label="Model ID",
+                value="stabilityai/stable-diffusion-3-medium-diffusers",
+            ),
+            gr.Text(label="Prompt", value=""),
+            gr.Text(label="Negative Prompt", value=""),
+        ],
+        outputs=[
+            gr.Image(label="Image", type="pil"),
+        ],
+    )
+    demo.launch()

requirements.txt

@@ -0,0 +1,8 @@
+gradio
+torch
+torchvision
+safetensors
+diffusers
+transformers
+ftfy
+accelerate