entregable3 / app.py
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from huggingface_hub import from_pretrained_fastai
import gradio as gr
from fastai.vision.all import *
# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
repo_id = "macundin/entrega3"
learner = from_pretrained_fastai(repo_id)
labels = ["Sentimiento negativo","Sentimiento positivo"]
# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(texto):
pred,pred_idx,probs = learner.predict(texto)
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(), outputs=gr.outputs.Label(num_top_classes=3),examples=['this is a film well worth seeing , talking and singing heads and all .']).launch(share=False)