Upload 3 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.keras filter=lfs diff=lfs merge=lfs -text

app(1).py

@@ -0,0 +1,30 @@
+import numpy as np
+import gradio as gr
+from tensorflow import keras
+
+# Load your Keras model
+model = keras.models.load_model("model.keras")  # Ensure this file is uploaded to the Space
+
+# Define prediction function
+def predict(input_string):
+    try:
+        # Convert user input (comma-separated) into a NumPy array
+        input_array = np.array([float(x.strip()) for x in input_string.split(',')])
+        input_array = input_array.reshape(1, -1)  # Reshape for model
+        prediction = model.predict(input_array)
+        return prediction.tolist()
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(label="Enter comma-separated input values"),
+    outputs=gr.Textbox(label="Model Prediction"),
+    title="Keras Model Predictor",
+    description="Enter input values (e.g., 1.2, 2.4, 3.6) for prediction"
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()

model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a7c19a6c65f0b40dbb4475c35df36b2da610a7d9839e2023c58cbcfb6bbdb863
+size 149572

requirements(1).txt

@@ -0,0 +1,3 @@
+gradio
+tensorflow
+numpy