lazarinastoy

import torch
import streamlit as st
from transformers import BartTokenizer, BartForConditionalGeneration
from transformers import T5Tokenizer, T5ForConditionalGeneration

st.title('Text Summarization Demo')
st.markdown('Using BART and T5 transformer model')

model = st.selectbox('Select the model', ('BART', 'T5'))

lazarinastoy

#Import streamlit library
import streamlit as st

st.title("Medium Article Generator") #set title of website
starting_sentence = st.text_input(label='Enter Starting Sentence') #set input and label

#Function to run model and generate new text
@st.cache
def generate():
    import gpt_2_simple as gpt2

lazarinastoy

import streamlit as st
from ludwig.api import LudwigModel
import pandas as pd

st.cache(show_spinner=False)
def load_model():
  #Update with the path to the Ludwig trained model
  model = LudwigModel.load("results/experiment_run_1/model/")
  return model