import gradio as gr

def predict_emotion(text):
    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=128)
    outputs = model(**inputs)
    prediction = outputs.logits.argmax(-1).item()
    return dataset["train"].features["label"].int2str(prediction)

interface = gr.Interface(fn=predict_emotion, inputs="text", outputs="label", title="Emotion Classifier")
interface.launch(share=False)