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', 'codellama/CodeLlama-7b-hf', 'hf-internal-testing/llama-tokenizer', 'gpt2', '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_area('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'{str(token_num)}', 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'{str(token_num)}', unsafe_allow_html=True)