Create app.py

app.py

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+import gradio as gr
+import pickle
+from huggingface_hub import hf_hub_download
+
+model_path = hf_hub_download(repo_id="alperugurcan/toxic-model", filename="toxic_model.pkl")
+vectorizer_path = hf_hub_download(repo_id="alperugurcan/toxic-model", filename="toxic_vectorizer.pkl")
+
+model = pickle.load(open(model_path, 'rb'))
+vectorizer = pickle.load(open(vectorizer_path, 'rb'))
+
+def predict(text):
+    features = vectorizer.transform([text.lower()])
+    predictions = model.predict_proba(features)
+
+    labels = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']
+    return {label: float(pred[0][1]) for label, pred in zip(labels, predictions)}
+
+iface = gr.Interface(
+    fn=predict,
+    inputs="text",
+    outputs="label",
+    title="Toxic Comment Classifier"
+)
+
+iface.launch()