> GGUF quantizations of AMD’s Instella-MoE-16B-A3B-Think, converted and optimized for local inference with llama.cpp-compatible runtimes that support the Instella-MoE architecture. This repository provides a full collection of GGUF quantizations for [amd/Instella-MoE-16B-A3B-Think](la-MoE-16B-A3B-Think. Instella-MoE-16B-A3B-Think is a Mixture-of-Experts reasoning model featuring approximately 16B total parameters with ~3B active parameters per token, designed for efficient high-quality inference while maintaining strong reasoning, coding, and instruction-following capabilities. — Local inference — CPU deployment — GPU-accelerated llama.cpp inference — Edge and workstation deployments — Quantized execution with reduced memory requirements — Reasoning-focused workloads These quantizations generally achieve superior quality-to-size ratios compared to traditional quant methods. The original model weights were converted directly into GGUF BF16 format using the Instella-MoE-enabled llama.cpp conversion tools. A lightweight calibration dataset was used to optimize IQ quantization quality while remaining practical on constrained hardware. IQ quant variants were produced using llama.cpp’s…
Модальности:
Генерация текста
Области применения:
Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: NANI-Nithin
Теги: llama.cpp, gguf, instella-moe, mixture-of-experts, amd, quantized, reasoning, think
Лайков: 3 | Загрузок: 2,121
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
