Update app.py

app.py

@@ -1,25 +1,25 @@
-import gradio as gr
-import numpy as np
-from tensorflow.keras.models import load_model
-from tkan import TKAN
-from tkat import TKAT
-from keras.utils import custom_object_scope
-
-# Load the model with custom objects
-with custom_object_scope({"TKAN": TKAN, "TKAT": TKAT}):
-    model = load_model("best_model_TKAN_nahead_1.h5")
-
-# Define predict function
-def predict(pm25, pm10, co, temp):
-    input_data = np.array([[pm25, pm10, co, temp]])
-    output = model.predict(input_data)
-    return float(output[0][0])
-
-# Gradio interface
-interface = gr.Interface(
-    fn=predict,
-    inputs=[gr.Number(), gr.Number(), gr.Number(), gr.Number()],
-    outputs=gr.Number()
-)
-
-interface.launch()
+import gradio as gr
+import numpy as np
+from tensorflow.keras.models import load_model
+from tkan import TKAN
+from tkat import TKAT
+from keras.utils import custom_object_scope
+
+# Load the model with custom objects
+with custom_object_scope({"TKAN": TKAN, "TKAT": TKAT}):
+    model = load_model("best_model_TKAN_nahead_1 (2).keras")
+
+# Define predict function
+def predict(pm25, pm10, co, temp):
+    input_data = np.array([[pm25, pm10, co, temp]])
+    output = model.predict(input_data)
+    return float(output[0][0])
+
+# Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=[gr.Number(), gr.Number(), gr.Number(), gr.Number()],
+    outputs=gr.Number()
+)
+
+interface.launch()