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| import streamlit as st | |
| import transformers | |
| import tensorflow | |
| import PIL | |
| from PIL import Image | |
| import time | |
| from transformers import pipeline | |
| model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg" | |
| def load_model(): | |
| return pipeline("text2text-generation", model=model_checkpoint) | |
| model = load_model() | |
| #prompts | |
| st.title("Writing Assistant for you 🦄") | |
| image = Image.open('grammar.jpg').resize((1000,300)) | |
| st.image(image, caption='Sunrise by the mountains') | |
| st.subheader("Some examples: ") | |
| example_1 = st.button("I am write on AI") | |
| example_2 = st.button("This sentence has, bads grammar mistake!") | |
| textbox = st.text_area('Write your text in this box:', '', height=100, max_chars=1000) | |
| button = st.button('Detect grammar mistakes:') | |
| # output | |
| if example_1: | |
| with st.spinner('In progress.......'): | |
| output_text = model("I am write on AI")[0]["generated_text"] | |
| st.markdown("## "+output_text) | |
| if example_2: | |
| with st.spinner('In progress.......'): | |
| output_text = model("This sentence has, bads grammar mistake!")[0]["generated_text"] | |
| st.markdown("**"+output_text+"**") | |
| if button: | |
| with st.spinner('In progress.......'): | |
| output_text = model(textbox)[0]["generated_text"] | |
| st.markdown("**"+output_text+"**") | |