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import streamlit as st
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
st.title("AI Accountant - Prompt-Based ERP Entry")
model_path = "google/flan-t5-large" # load directly from Hugging Face hub
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
user_input = st.text_area("Enter accounting transaction:")
if st.button("Generate Entry"):
inputs = tokenizer(user_input, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
st.json(eval(result))
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