Upload app.py

app.py

@@ -0,0 +1,46 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+import os
+
+def get_token() -> str:
+  return os.environ.get("HUGGING_FACE_TOKEN") 
+
+def save_images(images: list) -> list:
+
+  output_files_names = []
+  for id, image in enumerate(images):
+    filename = f"output{id}.png"
+    image.save(filename)
+    output_files_names.append(filename)
+    
+  return output_files_names
+
+
+
+def create_img(prompt :str, number_output_requested: int) -> list:
+  AUTH_TOKEN = get_token()
+  generator = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", 
+                                                        revision="fp16", 
+                                                        torch_dtype=torch.float16, 
+                                                        use_auth_token=AUTH_TOKEN)
+  generator.to("cuda")
+  prompt = [prompt] * number_output_requested
+  with torch.autocast("cuda"):
+    images = generator(prompt).images
+    output_paths = save_images(images)
+  return output_paths
+
+diffusers_app = gr.Interface(
+        fn=create_img,
+        inputs =
+        [
+          gr.Textbox(label="Write your prompt below", placeholder = "A squirrel bench pressing 200 kg"),
+          gr.Slider(value=1, minimum=1, maximum=8, step=1, label="Number of pictures to generate")
+        ],
+        outputs = gr.Gallery(label="Generated Images").style(grid=[2]),
+        title="Text to Image with Stable Diffusion",
+        description="This is a basic app to generate pictures with Stable Diffusion."
+) 
+
+diffusers_app.launch(debug=True)