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Runtime error
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import streamlit as st
from torch.nn import Softmax
from model import ArxivModel, load_model
from tokenizer import get_tokenizer
from lables import num_to_classes, taxonomy
from parser import get_text_title
model = load_model()
tokenizer = get_tokenizer()
arxiv_model = ArxivModel(model, tokenizer)
softmax = Softmax(dim=1)
st.markdown("### Classification of article topics")
col1, col2 = st.columns(2)
text = ""
with col1:
title_text = st.text_area("Write title of article", key='arxiv_title_input')
with col2:
summary_text = st.text_area("Write summary of article (optional)", key='arxiv_sum_input')
click_button_text = st.button('Submit title and summary', key=1)
if click_button_text and summary_text.strip() != "":
text = title_text.strip() + '\t' + summary_text.strip()
else:
text = title_text.strip()
text = text.strip()
id_url = st.text_input("Write article's url or id", key='arxiv_id_input').strip()
click_button_url = st.button('Submit id', key=1)
if click_button_url and id_url != "":
res = get_text_title(id_url)
if res is not None:
text = res[0].strip() + '\t' + res[1].strip()
text = text.strip()
else:
st.markdown(f'<p style="color:#FF2D00;font-size:18px">Incorrect url or id</p>', unsafe_allow_html=True)
text = ""
print(text)
if text != "":
idxs = arxiv_model.get_idx_class(text, thr=0.95)[:10]
for idx, prob in idxs:
if taxonomy.get(num_to_classes[idx], -1) != -1:
st.markdown("{} \t {}%".format(taxonomy.get(num_to_classes[idx], -1), round(prob * 100, 1)))
else:
st.markdown("")
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