File size: 773 Bytes
bef7abc 3a33679 bef7abc 712f163 bef7abc 026d9d8 a5f9c84 bef7abc 5c6eae7 4e2fd87 5c6eae7 bef7abc a8d72ba bef7abc 5c6eae7 bef7abc d46bc93 738f127 d46bc93 5c6eae7 026d9d8 5c6eae7 026d9d8 5c6eae7 026d9d8 5c6eae7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 |
import streamlit as st
import transformers
import tensorflow
from transformers import pipeline
model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg"
@st.cache(allow_output_mutation=True, suppress_st_warning=True)
def load_model():
return pipeline("text2text-generation", model=model_checkpoint)
model = load_model()
#prompts
st.title("Writing Assistant for you 🦄")
textbox = st.text_area('Write your text:', '', height=200, max_chars=1000)
button = st.button('Detect grammar mistakes:')
if button:
output_text = model(textbox)[0]
st.markdown(output_text)
#inputs = tokenizer("Grammar: "+sent,return_tensors="tf")
#output_sequences = infer(inputs)
#generated_sequences = tokenizer.decode(output_ids)
#st.write(generated_sequences)
|