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 = "valintea/modelo_p1" learner = from_pretrained_fastai(repo_id) labels = learner.dls.vocab # Definimos una funciĆ³n que se encarga de llevar a cabo las predicciones def predict(img): #img = PILImage.create(img) pred,pred_idx,probs = learner.predict(img) 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.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['1001.jpg','10006.jpg']).launch(share=False)