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Runtime error
| # -*- coding: utf-8 -*- | |
| import numpy as np | |
| import streamlit as st | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| st.set_page_config( | |
| page_title="", layout="wide", initial_sidebar_state="expanded" | |
| ) | |
| def load_model(model_name): | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name) | |
| return model | |
| tokenizer = AutoTokenizer.from_pretrained("snoop2head/KoBrailleT5-small-v1") | |
| model = load_model("snoop2head/KoBrailleT5-small-v1") | |
| st.title("한국어 점역과 역점역") | |
| st.write("Braille Pattern Conversion") | |
| default_value = '⠍⠗⠠⠪⠋⠕⠀⠘⠪⠐⠗⠒⠊⠕⠐⠀⠘⠮⠐⠍⠨⠟⠀⠚⠣⠕⠚⠕⠂' | |
| src_text = st.text_area( | |
| "번역하고 싶은 문장을 입력하세요:", | |
| default_value, | |
| height=300, | |
| max_chars=100, | |
| ) | |
| print(src_text) | |
| if src_text == "": | |
| st.warning("Please **enter text** for translation") | |
| else: | |
| # translate into english sentence | |
| src_text += "</s>" | |
| translation_result = model.generate( | |
| tokenizer( | |
| src_text, | |
| return_tensors="pt", | |
| padding="max_length", | |
| truncation=True, | |
| max_length=64, | |
| ).input_ids, | |
| ) | |
| translation_result = tokenizer.decode( | |
| translation_result[0], | |
| clean_up_tokenization_spaces=True, | |
| skip_special_tokens=True, | |
| ) | |
| print(f"{src_text} -> {translation_result}") | |
| st.write(translation_result) | |
| print(translation_result) | |