Frontmatter

main.py

@@ -1,8 +1,10 @@
 import gradio as gr
 import torch
 import requests
+import frontmatter
 from torchvision import transforms
 
+description = frontmatter.load("README.md").content
 model = torch.hub.load("pytorch/vision:v0.6.0", "resnet18", pretrained=True).eval()
 response = requests.get("https://git.io/JJkYN")
 labels = response.text.split("\n")
@@ -21,6 +23,7 @@ def run():
         fn=predict,
         inputs=gr.Image(type="pil"),
         outputs=gr.Label(num_top_classes=3),
+        description=description
     )
 
     demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -2,3 +2,4 @@ gradio
 torch
 torchvision
 requests
+python-frontmatter