Katta til modellari (LLM) ma'lumotlar to'plamining o'lchami va modeldagi parametrlar sonini oshirish orqali ishlashni yaxshilaydi va har bir omilning optimal miqdori sizning hisob-kitobingiz miqdoriga qarab o'zgaradi. Chinchilla o'lchash qonunlarini (Hoffman 2022) qo'llab, ma'lum bir FLOP byudjeti uchun optimal model va ma'lumotlar to'plami o'lchamlarini taxmin qilish quyida mavjud: █ Model o'lchami █ FLOP byudjeti █ Tokenlar █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █ █
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence