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import gradio as gr
import numpy as np
from transformers import pipeline
unmasker = pipeline("fill-mask", model="anferico/bert-for-patents")
example = 'A crustless sandwich made from two slices of baked bread'
def unmask(text):
res = unmasker(text)
out = {item["token_str"]: item["score"] for item in res}
return out
textbox = gr.Textbox(label="Type language here", lines=5)
import gradio as gr
from transformers import pipeline
unmasker = pipeline("fill-mask", model="anferico/bert-for-patents")
def add_mask(text, size=3):
split_text = text.split()
idx = np.random.randint(len(split_text), size=size)
for i in idx:
split_text[i] = '[MASK]'
return ' '.join(split_text)
def unmask(text):
text = add_mask(text)
res = unmasker(text)
out = {item["token_str"]: item["score"] for item in res}
return out
textbox = gr.Textbox(label="Type language here", lines=5)
demo = gr.Interface(
fn=unmask,
inputs=textbox,
outputs="label",
examples=[
],
)
demo.launch()
demo = gr.Interface(
fn=unmask,
inputs=textbox,
outputs="label",
examples=[
],
)
demo.launch() |