|
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__': |
|
|
|
|
|
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') |
|
|
