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updating sidebar
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app.py
CHANGED
@@ -2,7 +2,7 @@ import streamlit as st
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# from huggingface_hub import snapshot_download
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page = st.sidebar.selectbox("Model ", ["
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def load_model(model_name):
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with st.spinner('Waiting for the model to load.....'):
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@@ -15,21 +15,16 @@ def load_model(model_name):
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seed = st.sidebar.text_input('Starting text', 'ආයුබෝවන්')
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seq_num = st.sidebar.number_input('Number of sentences to generate ', 1, 20, 5)
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max_len = st.sidebar.number_input('Length of the sentence ', 5, 300, 100)
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if page ==
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st.
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st.markdown('This model has been finetuned Sinhala-gpt2 model with 6000 news articles(~12MB)')
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# seed = st.text_input('Starting text', 'ආයුබෝවන්')
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# seq_num = st.number_input('Number of sentences to generate ', 1, 20, 5)
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# max_len = st.number_input('Length of the sentence ', 5, 300, 100)
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model, tokenizer = load_model('keshan/sinhala-gpt2-newswire')
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if
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try:
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with st.spinner('Generating...'):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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@@ -38,14 +33,14 @@ if page == "Finetuned on News data":
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except Exception as e:
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st.exception(f'Exception: {e}')
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else:
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-
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st.
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model, tokenizer = load_model('
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if
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try:
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with st.spinner('Generating...'):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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@@ -53,7 +48,7 @@ else:
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st.write(seqs)
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except Exception as e:
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st.exception(f'Exception: {e}')
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-
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st.markdown('____________')
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st.markdown('by Keshan with Flax Community')
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# from huggingface_hub import snapshot_download
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page = st.sidebar.selectbox("Model ", ["Finetuned on News data", "Pretrained GPT2"])
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def load_model(model_name):
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with st.spinner('Waiting for the model to load.....'):
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seed = st.sidebar.text_input('Starting text', 'ආයුබෝවන්')
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seq_num = st.sidebar.number_input('Number of sentences to generate ', 1, 20, 5)
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max_len = st.sidebar.number_input('Length of the sentence ', 5, 300, 100)
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gen_bt = st.sidebar.button('Generate')
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if page == 'Pretrained GPT2':
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st.title('Sinhala Text generation with GPT2')
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st.markdown('A simple demo using Sinhala-gpt2 model trained during hf-flax week')
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model, tokenizer = load_model('flax-community/Sinhala-gpt2')
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if gen_bt:
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try:
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with st.spinner('Generating...'):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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except Exception as e:
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st.exception(f'Exception: {e}')
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else:
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st.title('Sinhala Text generation with Finetuned GPT2')
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st.markdown('This model has been finetuned Sinhala-gpt2 model with 6000 news articles(~12MB)')
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model, tokenizer = load_model('keshan/sinhala-gpt2-newswire')
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if gen_bt:
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try:
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with st.spinner('Generating...'):
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generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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st.write(seqs)
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except Exception as e:
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st.exception(f'Exception: {e}')
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st.markdown('____________')
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st.markdown('by Keshan with Flax Community')
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