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Рекомендации по использованию этого JSON для тренинга:
Feature Engineering (Инженерия признаков): Поле uptime_seconds является ключевым. Модель должна научиться связывать низкие числовые значения (например, < 300) с флагом “anomaly_detected”: true.
Негативные примеры: Пример normal_ecmp_stable_01 критически важен. Без него модель может начать считать любые множественные пути аномалией, вместо того чтобы сравнивать их возраст.
Формат обучения: Вы можете преобразовать этот JSON в формат {"instruction": “Проанализируй вывод show ip route на предмет аномалий”, “input”: “”, “output”: “”} для стандартного fine-tuning’а (например, в форматах Alpaca или ChatML).
Контекст протоколов: В reasoning явно указано, почему низкий uptime плох для BGP/OSPF, но мог бы быть нормальным для статического маршрута, только что добавленного администратором. Это помогает модели строить контекстно-зависимые выводы.
http://vbproject.shmeleff.com/page00002.htm