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import streamlit as st |
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import transformers |
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import tensorflow |
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from transformers import pipeline |
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model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg" |
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tokenizer = AutoTokenizer.from_pretrained(model_checkpoint) |
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@st.cache(allow_output_mutation=True, suppress_st_warning=True) |
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def load_model(): |
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return pipeline("text2text- generation", model=model_checkpoint) |
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model = load_model() |
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def infer(input_ids): |
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output_sequences = model.generate(inputs["input_ids"]).numpy()[0][1:-1] |
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return output_sequences |
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st.title("Writing Assistant for you π¦") |
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textbox = st.text_area('Write your text:', '', height=200, max_chars=1000) |
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