mrolando
fouth
adb08e0
from transformers import pipeline
import gradio as gr
import base64
model_checkpoint2 = "dccuchile/bert-base-spanish-wwm-cased"
mask_filler = pipeline(
"fill-mask", model=model_checkpoint2,tokenizer=model_checkpoint2
)
def fill_mask_interface(sentence):
results = mask_filler(sentence)
#suggestions = [f"{result['token_str']} (confidence: {result['score']:.4f})" for result in results]
dictt ={}
for text,score in zip([d['token_str'] for d in results],[d['score'] for d in results]):
dictt[text] = score
return dictt
with open("Iso_Logotipo_Ceibal.png", "rb") as image_file:
encoded_image = base64.b64encode(image_file.read()).decode()
description = """
<p>
<center>
<img src='data:image/jpg;base64,{}' width=200px>
Interact煤a con este espacio para probar la predicci贸n de palabras en una frase con una palabra enmascarada. La palabra enmascarada debe ser [MASK] y s贸lo una por frase.
</center>
</p>
""".format(encoded_image)
textbox = gr.Textbox(label="Agrega tu frase con una palabra enmascarada aqu铆!", placeholder="Hola, [MASK] est谩s?", lines=2)
gr.Interface(fn=fill_mask_interface,
inputs=textbox,
outputs="label",
title = "Uso de AI para la predicci贸n de palabras enmascaradas.",
description = description,
examples=[["Hola, c贸mo te lleva el [MASK]?"], ["D贸nde deber铆amos [MASK]?"]]
).launch()