added the rest of the program

app.py

@@ -1,4 +1,21 @@
 import gradio as gr
+import datasets
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+dataset = datasets.load_dataset("beans")
+
+extractor = AutoFeatureExtractor.from_pretrained("saved_model_files")
+model = AutoModelForImageClassification.from_pretrained("saved_model_files")
+
+labels = dataset['train'].features['labels'].names
+
+def classify(im):
+      features = image_processor(im, return_tensors='pt')
+        logits = model(features["pixel_values"])[-1]
+          probability = torch.nn.functional.softmax(logits, dim=-1)
+            probs = probability[0].detach().numpy()
+              confidences = {label: float(probs[i]) for i, label in enumerate(labels)} 
+                return confidences
 
 interface = gr.Interface(fn=classify, inputs="image", outputs="label")
 

app.py~

@@ -0,0 +1,5 @@
+import gradio as gr
+
+interface = gr.Interface(fn=classify, inputs="image", outputs="label")
+
+interface.launch(debug=True)