app.py

import streamlit as st
import transformers
import tensorflow


from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM

model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg"

tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)

@st.cache
def load_model(model_name):
    model = TFAutoModelForSeq2SeqLM.from_pretrained(model_name)
    return model
    
model= load_model(model_checkpoint)

def infer(input_ids):
    output_sequences = model.generate(inputs["input_ids"]).numpy()[0][1:-1]
    return output_sequences
    
default_value = "Write your text here!"
#prompts
st.title("Writing Assistant for you 🦄")

sent = st.text_area("Text", default_value, height = 275)

inputs = tokenizer("Grammar: "+sent,return_tensors="tf")

output_sequences = infer(inputs)

generated_sequences = tokenizer.decode(output_ids)

st.write(generated_sequences)