app.py

import torch
from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr

# トークナイザーとモデルの準備
tokenizer = AutoTokenizer.from_pretrained('sonoisa/t5-base-japanese') 
model = AutoModelForSeq2SeqLM.from_pretrained('models/')    


def summary(text):
    # 文章をテンソルに変換
    input = tokenizer.encode(text, return_tensors='pt', max_length=512, truncation=True)
    # 推論
    
    model.eval()
    with torch.no_grad():
        summary_ids = model.generate(input)
        
        return tokenizer.decode(summary_ids[0][1:-1])
 
descriptions = "T5による文章要約。文章を入力すると、その要約文を出力します。"

demo = gr.Interface(fn=summary, inputs=gr.Textbox(lines=5, placeholder="文章を入力してください"), outputs=gr.Textbox(lines=5),title="Sentence Summary", description=descriptions)

demo.launch()