import streamlit as st | |
from transformers import pipeline | |
#model = AutoModelForSeq2SeqLM.from_pretrained("t5-base") | |
#tokenizer = AutoTokenizer.from_pretrained("t5-base") | |
classifier = pipeline('text-generation', model="dbmdz/german-gpt2", | |
tokenizer="dbmdz/german-gpt2") | |
def main(): | |
st.title("Text translation") | |
with st.form("text_field"): | |
text = st.text_area('enter some text:') | |
# clicked==True only when the button is clicked | |
clicked = st.form_submit_button("Submit") | |
if clicked: | |
results = classifier([text]) | |
st.json(results) | |
if __name__ == "__main__": | |
main() |