| import gradio as gr | |
| from transformers import pipeline | |
| classifier3 = pipeline('text-classification', model='nlmaldonadog/clasificador-rotten-tomatoes-bert-base-uncased') | |
| classifier4 = pipeline('text-classification', model='nlmaldonadog/clasificador-rotten-tomatoes-xlnet-base-cased') | |
| def predict(text): | |
| prediction3 = "Model 3 " + str(classifier3(text)) | |
| prediction4 = "\nModel 4 " + str(classifier4(text)) | |
| return prediction3 + prediction4 | |
| ifg = gr.Interface(fn=predict, inputs=[gr.Textbox(placeholder='Escribe aquí...')], outputs="text") | |
| ifg.launch(share=True) |