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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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@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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st.title("Writing Assistant for you 🦄") |
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textbox = st.text_area('Write your text in this box:', '', height=200, max_chars=1000) |
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button = st.button('Detect grammar mistakes:') |
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if button: |
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output_text = model(textbox)[0]["generated_text] |
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st.write("Correct : ", output_text) |
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#inputs = tokenizer("Grammar: "+sent,return_tensors="tf") |
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#output_sequences = infer(inputs) |
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#generated_sequences = tokenizer.decode(output_ids) |
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#st.write(generated_sequences) |
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