| from fastai.text.all import * | |
| import gradio as gr | |
| # Cargamos el learner | |
| learn = load_learner('export.pkl') | |
| # Definimos las etiquetas de nuestro modelo | |
| labels = [0,1,2,3] | |
| # Definimos una función que se encarga de llevar a cabo las predicciones | |
| def predict(text): | |
| pred,pred_idx,probs = learn.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.Textbox(), outputs=gr.outputs.Label(num_top_classes=4),examples=['what do you mean ? it will help us to relax .','you know that is tempting but is really not good for our fitness .']).launch(share=False) | |