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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 AutoTokenizer, TFAutoModelForSeq2SeqLM |
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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 |
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def load_model(model_name): |
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model = TFAutoModelForSeq2SeqLM.from_pretrained(model_name) |
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return model |
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model= load_model(model_checkpoint) |
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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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default_value = "Write your text here!" |
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st.title("Writing Assistant for you 🦄") |
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sent = st.text_area("Text", default_value, height = 275) |
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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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