| 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) | |