app.py

import streamlit as st
from transformers import GPT2Tokenizer, GPT2Model, FlaxGPT2LMHeadModel, GPT2LMHeadModel, pipeline, set_seed
import torch

#===========================================#
#        Loads Model and Pipeline        #
#===========================================#

from transformers import GPT2Tokenizer, GPT2Model, FlaxGPT2LMHeadModel, GPT2LMHeadModel, pipeline, set_seed
 
tokenizer = AutoTokenizer.from_pretrained("flax-community/swe-gpt-wiki")
model = AutoModelWithLMHead.from_pretrained("flax-community/swe-gpt-wiki")

generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
set_seed(42)


#===========================================#
#              Streamlit Code               #
#===========================================#
desc = "En svensk GPT-modell tränad på wikipedia"

st.title('Vi använder wikipidea för att generera text')
st.write(desc)

num_sentences = st.number_input('Number of Sentences', min_value=1, max_value=20, value=5)
user_input = st.text_input('Seed Text (can leave blank)')


if st.button('Generate Text'):
    generated_text = generator(user_input, max_length=num_sentences, num_return_sequences=1)
    st.write(generated_text[0]["generated_text"])