| import gradio as gr | |
| from transformers import AutoModelForSeq2SeqLM, AutoTokenizer | |
| model_id = "methodya/arabic-summarizer-philosophy" | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_id) | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| def summarize(text, max_length=150): | |
| inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True) | |
| outputs = model.generate(**inputs, max_length=max_length) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| interface = gr.Interface( | |
| fn=summarize, | |
| inputs=[ | |
| gr.Textbox(lines=8, label="النص"), | |
| gr.Slider(50, 250, value=150, label="طول الملخص") | |
| ], | |
| outputs=gr.Textbox(label="الملخص"), | |
| title="ملخص النصوص الفلسفية", | |
| description="نموذج لتلخيص النصوص الفلسفية باللغة العربية" | |
| ) | |
| interface.launch() |