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# import gradio as gr
# def greet(name):
# return "Hello Mr." + name + "!!"
# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()
import gradio as gr
from numpy import kaiser
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() |