Delete app.py

app.py

@@ -1,36 +0,0 @@
-
-import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import torch
-
-# Load tokenizer dan model dari Hugging Face Hub
-model_name = "ElizabethSrgh/customer-service-multitask"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-
-# Daftar label sesuai urutan model (ubah jika berbeda)
-label_map = {
-    0: "Complaint - Negative",
-    1: "Inquiry - Neutral",
-    2: "Request - Positive"
-}
-
-def predict(text):
-    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
-    with torch.no_grad():
-        outputs = model(**inputs)
-    logits = outputs.logits
-    predicted_class_id = torch.argmax(logits, dim=1).item()
-    return label_map.get(predicted_class_id, "Unknown")
-
-# Gradio UI
-interface = gr.Interface(
-    fn=predict,
-    inputs=gr.Textbox(lines=4, label="Masukkan Teks Percakapan"),
-    outputs=gr.Textbox(label="Hasil Prediksi"),
-    title="Klasifikasi Layanan Pelanggan",
-    description="Masukkan teks untuk memprediksi topik dan sentimen."
-)
-
-if __name__ == "__main__":
-    interface.launch()