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import streamlit as st
from transformers import AutoModel, AutoTokenizer, trainer_utils
# Load the model and tokenizer outside the text generation function
device = "cpu"
model = AutoModel.from_pretrained("Tanrei/GPTSAN-japanese").to(device)
tokenizer = AutoTokenizer.from_pretrained("Tanrei/GPTSAN-japanese")
# Function to generate text
def generate_text(input_text, max_tokens=50):
x_token = tokenizer(input_text, return_tensors="pt")
trainer_utils.set_seed(30)
input_ids = x_token.input_ids.to(device)
gen_token = model.generate(input_ids, max_new_tokens=max_tokens)
return tokenizer.decode(gen_token[0])
# Streamlit app
def main():
st.title("Japanese Text Generator")
# Input text
input_text = st.text_area("Enter the starting text:", "織田信長は、")
# Max tokens
max_tokens = st.slider("Max Tokens", 1, 100, 50)
# Generate button
if st.button("Generate Text"):
generated_text = generate_text(input_text, max_tokens)
st.text("Generated Text:")
st.write(generated_text)
if __name__ == "__main__":
main()
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