Create app.py

app.py

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+!pip install transformers-interpret
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+from transformers_interpret import SequenceClassificationExplainer
+model = AutoModelForSequenceClassification.from_pretrained("indobertweet-fine-tuned/pytorch_model.bin")
+tokenizer = AutoTokenizer.from_pretrained("indolem/indobertweet-base-uncased")
+classifier = pipeline('text-classification', model=model, tokenizer=tokenizer)
+
+def classify(text):
+    text = text.strip().lower()
+    result = classifier(text)
+    yhat = result[0]['label']
+    return result
+!pip install gradio
+
+import gradio as gr
+
+iface = gr.Interface(
+    fn=classify,
+    inputs=[
+        gr.Textbox(placeholder="Lewandowski bermain buruk sekali, Xavi benar-benar marah kepadanya", label="Enter text to classify emotions", lines=5)
+    ],
+    outputs=gr.Textbox(label="Classification Result"),
+    title="🔮 Emotion Classification",
+    description="Enter a text and classify its emotions."
+)
+iface.launch()