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app.py

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+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqGeneration
+
+# Model ve tokenizer'ı yükle
+model_name = "ozcangundes/mt5-small-turkish-summarization"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqGeneration.from_pretrained(model_name)
+summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
+
+def summarize_text(text):
+    if len(text.split()) < 100:
+        return "Metin çok kısa. En az 100 kelime olmalıdır."
+    
+    # Metni özetle
+    summary = summarizer(text, 
+                        max_length=150, 
+                        min_length=50, 
+                        length_penalty=2.0,
+                        num_beams=4,
+                        early_stopping=True)
+    
+    return summary[0]['summary_text']
+
+# Gradio arayüzünü oluştur
+iface = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(lines=10, label="Özetlenecek Metin"),
+    outputs=gr.Textbox(label="Özet"),
+    title="Türkçe Metin Özetleme",
+    description="Türkçe metinleri özetleyen yapay zeka modeli. En az 100 kelimelik metin giriniz."
+)
+
+iface.launch()

requirements.txt

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+gradio>=3.50.2
+transformers>=4.30.0
+torch>=2.0.0
+sentencepiece>=0.1.99