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import streamlit as st
import pandas as pd
st.set_page_config(page_title="Datasets Preparation", page_icon="š", layout="wide")
##########################################
# Read lines from the text file
with open("datafiles/sample_nep_corpus.txt") as file:
items = file.readlines()
# Split each line into separate columns
datacorpus = pd.DataFrame(items, columns=["Content"])
# datacorpus.columns =["Content"]
# st.write(f"{datacorpus}")
datasentences = pd.read_csv("datafiles/sample_nep_sentences.csv")
data100k = pd.read_csv(
r"datafiles/sample_nep_spell_100k.csv",
nrows=50,
)
###########################################
st.title("Dataset Preparation")
st.write("---")
st.header(
"""
A Large Scale Nepali Text Corpus
"""
)
st.caption("**Table 1.** A Large Scale Nepali Text Corpus")
st.dataframe(datacorpus, use_container_width=True)
st.write("---")
st.header(
"""
Sentence extracted from A Large Scale Nepali Text Corpus
"""
)
st.caption("**Table 2.** Extracted sentences")
st.dataframe(datasentences, use_container_width=True)
st.write("---")
st.header(
"""
Parallel dataset using extracted sentences
"""
)
st.caption("**Table 3.** 100k Dataset used for training")
st.dataframe(data100k, use_container_width=True)
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