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| from transformers import pipeline | |
| import gradio as gr | |
| pertrained_model = "MuntasirHossain/RoBERTa-base-finetuned-emotion" | |
| model = pipeline("text-classification", model=pertrained_model) | |
| def detect_emotions(text): | |
| label = model(text)[0]["label"] | |
| return label | |
| title = "Texts Expressing Emotion" | |
| iface = gr.Interface( | |
| fn=detect_emotions, | |
| inputs=gr.Textbox(), | |
| outputs=gr.Label(), | |
| title=title, | |
| ) | |
| iface.launch() | |