| from huggingface_hub import from_pretrained_fastai | |
| import gradio as gr | |
| from fastai.text.all import * | |
| # repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME" | |
| repo_id = "inigo99/rotten_tomatoes-classification2" | |
| learner = from_pretrained_fastai(repo_id) | |
| labels = learner.dls.vocab | |
| # Definimos una función que se encarga de llevar a cabo las predicciones | |
| def predict(text): | |
| pred, pred_idx,probs = learner.predict(text) | |
| 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=2)).launch(share=False) | |