adding model changes

app.py

@@ -1,7 +1,31 @@
+import torch
 import gradio as gr
+from torchvision import transforms
+from tinyvgg import TinyVGG  # Replace with your actual model import
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load the model
+model = TinyVGG(input_shape=3, hidden_units=64, output_shape=10)
+model.load_state_dict(torch.load("pytorch_model.bin", map_location=torch.device("cpu")))
+model.eval()
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Define a preprocessing pipeline
+preprocess = transforms.Compose([
+    transforms.Resize((64, 64)),
+    transforms.ToTensor()
+])
+
+# Inference function
+def predict(image):
+    image = preprocess(image).unsqueeze(0)  # Add batch dimension
+    with torch.no_grad():
+        outputs = model(image)
+    return outputs.argmax(dim=1).item()
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(shape=(64, 64)),
+    outputs="label"
+)
+
+iface.launch()

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ba177342f60f6f6936a7226712297ee23063158f152bf7377b0d7c6c47351b72
+size 37090