Update app.py

app.py

@@ -1,8 +1,14 @@
 import streamlit as st
-from transformers import pipeline
 from PIL import Image
 
-pipeline = pipeline(task="image-classification", model="ElBeh/ma_basemodel")
+# Available backend options are: "jax", "tensorflow", "torch".
+import os
+os.environ["KERAS_BACKEND"] = "tensorflow"
+	
+import keras
+
+model = keras.saving.load_model("hf://ElBeh/ma_basemodel")
+
 
 st.title("Fake Detection")
 
@@ -13,7 +19,7 @@ if file_name is not None:
 
     image = Image.open(file_name)
     col1.image(image, use_column_width=True)
-    predictions = pipeline(image)
+    predictions = model.predict(image)
 
     col2.header("Probabilities")
     for p in predictions: