matthew null Pippoz commited on
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Duplicate from Pippoz/Hugging_Space

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Co-authored-by: Filippo Ziliotto <Pippoz@users.noreply.huggingface.co>

Files changed (4) hide show
  1. .gitattributes +27 -0
  2. README.md +13 -0
  3. app.py +58 -0
  4. requirements.txt +3 -0
.gitattributes ADDED
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+ *.model filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ title: OPT- Meta
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+ emoji: 🤖
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+ colorFrom: blue
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+ colorTo: white
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+ sdk: streamlit
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+ sdk_version: 1.9.0
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+ app_file: app.py
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+ pinned: true
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+ duplicated_from: Pippoz/Hugging_Space
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
app.py ADDED
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+ import streamlit as st
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+ import time
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+ from transformers import pipeline
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+ import torch
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+
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+ st.markdown('## Text-generation OPT from Facebook')
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+
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+ @st.cache(allow_output_mutation=True, suppress_st_warning =True, show_spinner=False)
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+ def get_model():
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+ return pipeline('text-generation', model=model, do_sample=True)
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+
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+ col1, col2 = st.columns([2,1])
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+
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+ with st.sidebar:
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+ st.markdown('## Model Parameters')
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+
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+ max_length = st.slider('Max text length', 0, 150, 80)
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+
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+ num_beams = st.slider('N° tree beams search', 2, 15, 5)
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+
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+ early_stopping = st.selectbox(
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+ 'Early stopping text generation',
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+ ('True', 'False'), key={'True' : True, 'False': False}, index=0)
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+
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+ no_ngram_repeat = st.slider('Max repetition limit', 1, 5, 2)
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+
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+ with col1:
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+ prompt= st.text_area('Your prompt here',
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+ '''Who is Elon Musk?''')
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+
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+ with col2:
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+ select_model = st.radio(
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+ "Select the model to use:",
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+ ('OPT-125m', 'OPT-350m', 'OPT-1.3b'), index = 1)
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+
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+ if select_model == 'OPT-1.3b':
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+ model = 'facebook/opt-1.3b'
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+ elif select_model == 'OPT-350m':
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+ model = 'facebook/opt-350m'
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+ elif select_model == 'OPT-125m':
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+ model = 'facebook/opt-125m'
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+
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+ with st.spinner('Loading Model... (This may take a while)'):
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+ generator = get_model()
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+ st.success('Model loaded correctly!')
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+
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+ gen = st.info('Generating text...')
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+ answer = generator(prompt,
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+ max_length=max_length, no_repeat_ngram_size=no_ngram_repeat,
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+ early_stopping=early_stopping, num_beams=num_beams)
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+ gen.empty()
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+
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+ lst = answer[0]['generated_text']
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+
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+ t = st.empty()
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+ for i in range(len(lst)):
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+ t.markdown("#### %s" % lst[0:i])
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+ time.sleep(0.04)
requirements.txt ADDED
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+ streamlit
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+ transformers
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+ torch