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import streamlit as st | |
from utils import get_res | |
st.sidebar.title('Tokenizers demo') | |
#x = st.slider('Select a value') | |
#st.write(x, 'squared is', x * x) | |
model_option = ['deepseek-ai/deepseek-coder-1.3b-instruct', | |
'MediaTek-Research/Breeze-7B-Instruct-64k-v0_1', | |
'microsoft/phi-2', | |
'mistralai/Mistral-7B-Instruct-v0.2', | |
'enter by myself'] | |
input_option = ['123.5', 'hello world!!!', '大雨+寒流來襲!全台極凍72小時「探5度以下」', | |
'大雨+寒流来袭!全台极冻72小时「探5度以下」', | |
'enter by myself'] | |
st.sidebar.subheader('Choose the tokenizer', divider='grey') | |
st.sidebar.write('You can choose `enter by myself` to paste the model you want.') | |
model_name_A = st.sidebar.selectbox( | |
'Model Name A', | |
model_option) | |
if model_name_A == 'enter by myself': | |
model_name_A = st.sidebar.text_input('Please enter Model Name A', 'deepseek-ai/deepseek-coder-1.3b-instruct') | |
model_name_B = st.sidebar.selectbox( | |
'Model Name B', | |
model_option) | |
if model_name_B == 'enter by myself': | |
model_name_B = st.sidebar.text_input('Please enter Model Name B', 'deepseek-ai/deepseek-coder-1.3b-instruct') | |
#with st.sidebar.expander("Models that you might want"): | |
# for m in model_option: | |
# st.write(m) | |
#'Your choice:', model_name | |
st.sidebar.subheader('Choose the input sentence', divider='grey') | |
st.sidebar.write('You can choose `enter by myself` to enter the text you want.') | |
input_data = st.sidebar.selectbox( | |
'Input Sentence', | |
input_option) | |
if input_data == 'enter by myself': | |
input_data = st.sidebar.text_input('Write the Input Sentence', 'Hello sunshine!!!') | |
#with st.sidebar.expander("Input that you might want to test"): | |
# for m in input_option: | |
# st.write(m) | |
col1, col2 = st.columns(2) | |
with col1: | |
st.subheader(model_name_A, divider='grey') | |
res, token_num = get_res(model_name=model_name_A, input_sentence=input_data, single_print=False) | |
st.subheader('Tokenized result') | |
st.markdown(res, unsafe_allow_html=True) | |
st.subheader('Number of tokens') | |
st.markdown(f'<span style="font-size:1.875em">{str(token_num)}</span>', | |
unsafe_allow_html=True) | |
with col2: | |
st.subheader(model_name_B, divider='grey') | |
res, token_num = get_res(model_name=model_name_B, input_sentence=input_data, single_print=False) | |
st.subheader('Tokenized result') | |
st.markdown(res, unsafe_allow_html=True) | |
st.subheader('Number of tokens') | |
st.markdown(f'<span style="font-size:1.875em">{str(token_num)}</span>', | |
unsafe_allow_html=True) | |