from huggingface_hub import from_pretrained_fastai
import gradio as gr
from fastai.vision.all import *

repo_id = "pabpelle/entregable3"

learner = from_pretrained_fastai(repo_id)
labels = ["No toxic", "Toxic"]

def predict(text):
    pred,pred_idx,probs = learner.predict(text)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}
    
gr.Interface(fn=predict, inputs=gr.Text(), outputs=gr.Label(num_top_classes=2), examples=[]).launch(share=False)