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app.py

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+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()