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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) |