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import pandas as pd
import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import torch
import torch.nn.functional as F
from transformers import AlbertTokenizer
import time
if __name__=='__main__':
# Config
max_width = 1500
padding_top = 0
padding_right = 2
padding_bottom = 0
padding_left = 2
define_margins = f"""
<style>
.appview-container .main .block-container{{
max-width: {max_width}px;
padding-top: {padding_top}rem;
padding-right: {padding_right}rem;
padding-left: {padding_left}rem;
padding-bottom: {padding_bottom}rem;
}}
</style>
"""
hide_table_row_index = """
<style>
tbody th {display:none}
.blank {display:none}
</style>
"""
st.markdown(define_margins, unsafe_allow_html=True)
st.markdown(hide_table_row_index, unsafe_allow_html=True)
from custom_modeling_albert_flax import CustomFlaxAlbertForMaskedLM
model = CustomFlaxAlbertForMaskedLM.from_pretrained('albert-base-v2')
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