app.py

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 = "mapecim/ClasificadorTexto"

learner = from_pretrained_fastai(repo_id)

# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(text):
    pred,pred_idx,probs = learner.predict(text)
    if (pred == "0"):
        return "Negative"
    elif (pred == "1"):
        return "Positive"
    else:
        return "Error"
    
# Creamos la interfaz y la lanzamos. 
gr.Interface(fn=predict, inputs="text", outputs="label", examples=["I loved that movie", "I hated that movie"]).launch()