| import gradio as gr | |
| from gradio.mix import Parallel | |
| from transformers import pipeline | |
| import torch | |
| question = "Zertarako hasi dira ikertzen Londreseko poliziak?" | |
| context = "Londreseko Poliziak ikerketa bat jarri du martxan pandemia garaian Downing Streeten egin diren festen auzia argitzeko. Boris Johnsonek jai horietan parte hartu zuela eta, zalaparta handia piztu da Erresuma Batuan, jendartea haserre dago eta Alderdi Kontserbadorearen baitan ere ika-mika sortu da, lehen ministroak karguak utzi behar duela uste baitute.\nCressida Dick komisario buruak adierazi du Gobernuko kideek azken hiru urteotan pandemiaren kontrako neurriak urratu dituzten ikertuko dutela, eta ikerketa \"inolako beldurrik gabe eta inori mesederik egin gabe\" gauzatuko dutela agindu du.\nHalaber, ikerketan urrats garrantzitsurik ematen dutenean, berehala jakinaraziko dutela erantsi du.\nAtzo telebista britainiar batek jakinarazi zuenez, Boris Johnsonek bere urtebetetze jaia egin zuen Downing Streeteko egoitzan, 2020ko ekainaren 19an, covid-19ari aurre egiteko murrizketak urratuta." | |
| qa1 = pipeline("question-answering", model="MarcBrun/ixambert-finetuned-squad") | |
| qa2 = pipeline("question-answering", model="MarcBrun/ixambert-finetuned-squad-eu") | |
| qa3 = pipeline("question-answering", model="MarcBrun/ixambert-finetuned-squad-eu-en") | |
| def answer_1(question, context): | |
| answer = qa1(question=question, context=context) | |
| return answer["answer"] | |
| def answer_2(question, context): | |
| answer = qa2(question=question, context=context) | |
| return answer["answer"] | |
| def answer_3(question, context): | |
| answer = qa3(question=question, context=context) | |
| return answer["answer"] | |
| iface1 = gr.Interface(fn=answer_1, inputs=[gr.inputs.Textbox(),gr.inputs.Textbox()], outputs=gr.outputs.Textbox(label="SQuADv1.1")) | |
| iface2 = gr.Interface(fn=answer_2, inputs=[gr.inputs.Textbox(),gr.inputs.Textbox()], outputs=gr.outputs.Textbox(label="SQuAD-eu")) | |
| iface3 = gr.Interface(fn=answer_3, inputs=[gr.inputs.Textbox(),gr.inputs.Textbox()], outputs=gr.outputs.Textbox(label="SQuADv1.1 + SQuAD-eu")) | |
| Parallel(iface1, iface2, iface3, inputs=[gr.inputs.Textbox(lines=1, default=question, placeholder="Question Here...", label="Question"),gr.inputs.Textbox(lines=10, default=context, placeholder="Context Here...", label="Context")], title = "Question Answering in Basque", description="This demo compares the outputs of three QA models based on IXAmBERT. Each has been trained on different data: one on SQuADv1.1, another on an experimental version of SQuAD in Basque, and the last on both those datasets.").launch() |