| import gradio as gr | |
| from transformers import pipeline | |
| fill_mask = pipeline("fill-mask", model="./QuijoBERT", tokenizer = './QuijoBERT') | |
| def predict(text): | |
| res_dict = {} | |
| x = fill_mask(text) | |
| print('x') | |
| for i in range(len(x)): | |
| k = x[i]['sequence'] | |
| e = x[i]['score'] | |
| print(k, e) | |
| if e >= 0.05: | |
| res_dict[k] = e | |
| print (res_dict) | |
| return res_dict | |
| #return {x[0]["sequence"], x[0]["score"]} | |
| # texto = 'en un lugar de la <mask>' | |
| # print(predict(texto)) | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs='text', | |
| outputs ='label', | |
| examples=['En un lugar de la <mask>', 'En verdad, <mask> Sancho', 'Cómo has estado, bien mío, <mask> de mis ojos, compañero mío'] | |
| ) | |
| iface.launch() |