Unofficial GGUF conversion and importance-matrix quantizations of inclusionAI/Ling-3.0-tiny, created from immutable source revision a2ee06c0. No fine-tuning, merging, or other parameter training was performed. The original model documentation, intended use, benchmark claims, and limitations remain authoritative. > Experimental runtime requirement > > As of 2026-08-11, BailingMoE3 support remains unmerged in upstream > llama.cpp. INVALID LANGUAGE PAIR SPECIFIED. EXAMPLE: LANGPAIR=EN|IT USING 2 LETTER ISO OR RFC3066 LIKE ZH-CN. ALMOST ALL LANGUAGES SUPPORTED BUT SOME MAY HAVE NO CONTENT — BailingMoeV3 hybrid KDA/MLA sparse MoE, 526 GGUF tensors — 7,893,392,800 parameters total; approximately 1.3B active per token — 24 layers; 128 routed experts, 8 selected per token, plus 1 shared expert — Q-LoRA rank 256 and KV-LoRA rank 512 — Native configured context: 131,072 tokens — Embedded tokenizer and source chat template — No NEXTN/MTP layers…
Модальности:
Генерация текста
Области применения:
Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: Mike0021
Теги: gguf, llama.cpp, bailingmoe3, mixture-of-experts, quantized, reasoning, conversational
Лайков: 4 | Загрузок: 2,768
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
