| from huggingface_hub import from_pretrained_fastai | |
| import gradio as gr | |
| # from fastai.vision.all import * | |
| from fastai.text.all import * | |
| # repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME" | |
| repo_id = "igmarco/AWD_LSTM-text-classification" | |
| learner = from_pretrained_fastai(repo_id) | |
| labels = learner.dls.vocab | |
| # Definimos una función que se encarga de llevar a cabo las predicciones | |
| def predict(txt): | |
| pred,pred_idx,probs = learner.predict(txt) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| # Creamos la interfaz y la lanzamos. | |
| gr.Interface(fn=predict, inputs=gr.Textbox(lines=2, placeholder="Text Here..."), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=False) |