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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 = "kylar55/entregable3_1" | |
| 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) | |
| if pred == "en": | |
| return "Ingles" | |
| if pred == "ja": | |
| return "Japonés" | |
| if pred == "es": | |
| return "Español" | |
| else: | |
| return "other" | |
| # Creamos la interfaz y la lanzamos. | |
| gr.Interface(fn=predict, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Label(),examples=["娘が1歳になったので新しい知育玩具を探していたところリーズナブルで見た目も可愛いこちらの商品に辿りつきました。","Esta frase no es un meme","Highly recommend for those who don't like being spoon fed CGI garbage."]).launch(share=False) | |