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import streamlit as st |
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from multiprocessing import Process |
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from transformers import AutoConfig, AutoTokenizer, AutoModelForSequenceClassification |
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import torch |
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import pandas as pd |
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import json |
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import requests |
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import time |
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import os |
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model_name_or_directory = "MKaan/multilingual-cpv-sector-classifier" |
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tokenizer = AutoTokenizer.from_pretrained("bert-base-multilingual-cased") |
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config = AutoConfig.from_pretrained(model_name_or_directory) |
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model = AutoModelForSequenceClassification.from_pretrained(model_name_or_directory, config=config) |
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device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu') |
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idx2cpv = pd.read_csv("idx2cpv.csv") |
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idx2cpv = dict(zip(idx2cpv.indexes, idx2cpv.sectors)) |
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def get_result(input): |
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input_ids = tokenizer(input, return_tensors="pt").input_ids |
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output = model(input_ids) |
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pred = output.logits.argmax(dim=-1) |
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pred = pred.cpu().detach().numpy()[0] |
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return idx2cpv[pred] |
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if __name__ == "__main__": |
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st.title('Multilingual Sector Classifier 📄') |
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st.subheader('Finds the correct sector for the given contract description') |
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st.markdown("Built by Mustafa Kaan Görgün, [Linkedin](https://www.linkedin.com/in/mustafa-kaan-görgün-a2461288/), [Model Card](https://huggingface.co/MKaan/multilingual-cpv-sector-classifier) ", unsafe_allow_html=True) |
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examples = pd.read_csv("examples.csv") |
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lang2example = dict(zip(examples.lang, examples.descr)) |
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st.markdown(f'##### Try it now:') |
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input_lang = st.selectbox( |
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label="Choose a language from the list of 22 languages", |
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options=examples.lang, |
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index=5 |
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) |
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input_text_1 = st.text_area( |
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label="Example description in choosen language", |
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value=lang2example[input_lang], |
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height=150, |
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max_chars=500 |
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) |
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button1 = st.button('Run the example') |
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st.write("or") |
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input_text_2 = st.text_area( |
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label="Write your own contract description in any of 104 languages that MBERT supports.", |
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value="Your description comes here..", |
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height=100, |
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max_chars=500 |
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) |
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button2 = st.button('Run your own') |
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st.markdown(f'##### Classified Sector: ') |
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if button1: |
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with st.spinner('In progress.......'): |
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sector_class = get_result(input_text_1) |
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st.success(sector_class) |
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if button2: |
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with st.spinner('In progress.......'): |
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sector_class = get_result(input_text_2) |
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st.success(sector_class) |
