mlkorra's picture
Update pages/about.py
df4e370
import streamlit as st
import os
def read_markdown(path, folder="./About/"):
with open(os.path.join(folder, path)) as f:
return f.read()
def load_page():
st.markdown(""" # T5 for Sentence Split in English """)
st.markdown(""" ### Sentence Split is task of dividing complex sentence in two simple sentences """)
st.markdown(""" ## Goal """)
st.markdown(""" To make best sentence split model available till now """)
st.markdown(""" ## How to use the Model """)
st.markdown("""
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("flax-community/t5-base-wikisplit")
model = AutoModelForSeq2SeqLM.from_pretrained("flax-community/t5-base-wikisplit")
complex_sentence = "This comedy drama is produced by Tidy , the company she co-founded in 2008 with her husband David Peet , who is managing director ."
sample_tokenized = tokenizer(complex_sentence, return_tensors="pt")
answer = model.generate(sample_tokenized['input_ids'], attention_mask = sample_tokenized['attention_mask'], max_length=256, num_beams=5)
gene_sentence = tokenizer.decode(answer[0], skip_special_tokens=True)
gene_sentence
\"""
Output:
This comedy drama is produced by Tidy. She co-founded Tidy in 2008 with her husband David Peet, who is managing director.
\"""
``` """)
st.markdown(read_markdown("datasets.md"))
st.markdown(read_markdown("applications.md"))
#st.markdown(read_markdown("baseline.md"))
st.markdown(""" ## Current Basline from [paper](https://arxiv.org/abs/1907.12461) """)
st.image('./images/baseline.png')
st.markdown(read_markdown("results.md"))
st.markdown(read_markdown("accomplishments.md"))
st.markdown(read_markdown("gitrepo.md"))
st.markdown(read_markdown("contributors.md"))
st.markdown(read_markdown("credits.md"))