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from huggingface_hub import from_pretrained_fastai | |
from fastai.text.all import * | |
import gradio as gr | |
# Cargamos el learner | |
learner = from_pretrained_fastai('osrojo/Emotion') | |
# Definimos las etiquetas de nuestro modelo | |
labels = ['0','1','2','3','4','5'] | |
example1 = "would like to take the opportunity to describe one day this week when i was feeling particularly gloomy" | |
example2 = "i believe that feeling accepted in a non judgemental way can be healing" | |
example3 = "im feeling somewhat nostalgic about the game just from the fact that its star wars" | |
example4 = "i am most certainly an acquired taste but lately many of those around me have seemed to feel the taste to be bitter" | |
example5 = "i feel shy about it all and also a little concerned whether my new title will distance me away from people i care for" | |
example6 = "i feel like they bring the characters to life completely and i m always kind of surprised what the actors do do together" | |
# 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.Textbox(), outputs=gr.Label(),examples=[example1,example2,example3,example4,example5,emample6]).launch(share=False) |