| import gradio as gr | |
| from transformers import pipeline | |
| import pandas as pd | |
| # Load the genre prediction model as a pipeline | |
| pipe = pipeline(model="Stanford-TH/GenrePrediction", trust_remote_code=True) | |
| def classify_movie_genre(description): | |
| # Get predictions using the pipeline | |
| predictions = pipe(description) | |
| return pd.DataFrame([predictions]) | |
| # Define the Gradio interface | |
| iface = gr.Interface( | |
| fn=classify_movie_genre, | |
| inputs="textarea", | |
| outputs="dataframe", | |
| live=False, | |
| title="Genre Prediction" | |
| ) | |
| # Launch the Gradio interface | |
| iface.launch(inline=False) | |