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README.md

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+---
+title: Subway Cause Classifier
+emoji: 🏃
+colorFrom: green
+colorTo: gray
+sdk: gradio
+sdk_version: 5.29.1
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import tensorflow as tf
+import pickle
+import numpy as np
+
+# Load model + vectorizer + label encoder
+model = tf.keras.models.load_model("subway_alert_classifier_model.keras")
+vectorizer = pickle.load(open("tfidf_vectorizer.pkl", "rb"))
+label_encoder = pickle.load(open("label_encoder.pkl", "rb"))
+
+def classify_alert(text):
+    X = vectorizer.transform([text])
+    y_pred = model.predict(X)
+    label = label_encoder.inverse_transform([np.argmax(y_pred)])
+    return label[0]
+
+iface = gr.Interface(
+    fn=classify_alert,
+    inputs=gr.Textbox(lines=2, placeholder="Enter MTA alert description"),
+    outputs="text",
+    title="Subway Delay Cause Classifier",
+    description="Classifies MTA alerts into causes like 'track', 'signals', 'medical', etc."
+)
+
+iface.launch()

label_encoder.pkl

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+size 331

requirements.txt

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+tensorflow
+scikit-learn
+gradio

subway_alert_classifier_model.keras

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tfidf_vectorizer.pkl

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