Update app.py

app.py

@@ -1,17 +1,16 @@
 import streamlit as st
 from tensorflow import keras
 import numpy as np
-from huggingface_hub import HfApi
+from huggingface_hub import HfFileSystem
 
 # Authenticate and download the custom model from Hugging Face Spaces
-hf_api = HfApi()
-model_url = hf_api.presigned_url('dhhd255', 'idk_test', filename='best_model.h5', token='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')
-r = requests.get(model_url)
-with open('best_model.h5', 'wb') as f:
-    f.write(r.content)
+fs = HfFileSystem()
+model_path = 'dhhd255/idk_test/best_model.h5'
+with fs.open(model_path, 'rb') as f:
+    model_content = f.read()
 
 # Load your custom model
-model = keras.models.load_model('best_model.h5')
+model = keras.models.load_model(model_content)
 
 # Define a function that takes an image as input and uses the model for inference
 def image_classifier(image):