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


learner = load_learner("finetuned")
labels = list(range(0,150))


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="text", outputs=gr.outputs.Label(num_top_classes=5)).launch(share=False)