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| from fastai.text.all import * | |
| import gradio as gr | |
| # Cargamos el learner | |
| learner = load_learner('export.pkl') | |
| # Definimos las etiquetas de nuestro modelo | |
| labels = ["bad", "good"] | |
| # Definimos una función que se encarga de llevar a cabo las predicciones | |
| def predict(text): | |
| pred,pred_idx,probs = learner.predict(text) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| # Creamos la interfaz y la lanzamos. | |
| gr.Interface(fn=predict, inputs=gr.inputs.Textbox(default = "The movie was amazing!"), outputs=gr.outputs.Label()).launch(share=False) |