import gradio as gr from transformers import AutoModelForSeq2SeqLM, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("./mt5") model = AutoModelForSeq2SeqLM.from_pretrained("./mt5") model.resize_token_embeddings(len(tokenizer)) model.eval() def translate(hakubun): input_ids = tokenizer.encode(hakubun, return_tensors="pt", max_length=20, truncation=True) output = model.generate(input_ids) kakikudashi = tokenizer.decode(output[0], skip_special_tokens=True) return kakikudashi title = "Kanbun-LM" description = "Gradio Demo for Kanbun-LM. Upload a hakubun then you can earn get its kanbun. Texts other than Tang poetry may not be translated correctly.
" \ "書き下し文生成のデモです。白文を入力し、翻訳された書き下し文を得ることができます。唐詩以外の漢文は正しく翻訳されない可能性があります。" article = "

arXiv

" \ "

Github Repo

" examples = [['春眠不覚暁'], ['処処聞啼鳥'], ['洛陽親友如相問'], ['一片氷心在玉壺']] demo = gr.Interface(fn=translate, inputs="text", outputs="text", title=title, description=description, article=article, examples=examples, allow_flagging=False) demo.launch()