Spaces:
Sleeping
Sleeping
add process function
Browse files
app.py
CHANGED
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import streamlit as st
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st.title('Tokenizers demo
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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option = st.selectbox(
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model_name = st.text_input('Model Name', 'deepseek-ai/deepseek-coder-1.3b-instruct')
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'Your choice:', model_name
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import streamlit as st
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from utils import get_res
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st.title('Tokenizers demo')
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#x = st.slider('Select a value')
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#st.write(x, 'squared is', x * x)
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option = st.selectbox(
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model_name = st.text_input('Model Name', 'deepseek-ai/deepseek-coder-1.3b-instruct')
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'Your choice:', model_name
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input_data = st.text_input('Input Sentence', 'Hello world!!!')
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res = get_res(model_name=model_name, input_sentence=input_data, single_print=False)
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st.write(res)
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utils.py
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from transformers import AutoTokenizer
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import itertools
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def get_color():
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colors = [i for i in range(41, 48)]
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return itertools.cycle(colors)
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def get_res(model_name, input_sentence, single_print=True):
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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color_iterator = get_color()
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out = tokenizer.encode(input_sentence, add_special_tokens=False)
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token_num = len(out)
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w = [ '\033[''1;'+str(next(color_iterator))+f'm {tokenizer.decode(x)}\033[m' for x in out]
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res = ''.join(w) + f' {str(token_num)}'
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if single_print:
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print(res)
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else:
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return res
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