Cerebellum v5 is an ablation-guided mixed-precision GGUF quantization of google/gemma-4-26B-A4B-it. This is a 26B-parameter MoE model with 4B active parameters per token and 128 experts per layer. This release uses tensor-level precision overrides selected from 110+ ablation experiments across five internal iterations. — Current file: Gemma-4-26B-A4B-it-Cerebellum-Q3KM.gguf — Current release: v5 — File size: 11 GB — Base model: google/gemma-4-26B-A4B-it — Format: GGUF, mixed precision, imatrix-guided — Test hardware: RTX 3090, llama.cpp Measured on RTX 3090 with llama.cpp at temperature 0. HumanEval below is the legacy raw-completions number; for Gemma 4 the current protocol is the chat-completions harness (raw completions understate Gemma 4 coding), so treat it as legacy. Summary JSONs are in benchmarkresults/`. All benchmark results above were measured on the same local setup: RTX 3090 and llama.cpp. PPL was measured on the WikiText-2 test set with 2048 context and 128 chunks. PPL is high in absolute terms for this model and appears consistent across Gemma 4 26B quant levels tested locally. Gemma 4 requires —jinja. For non-thinking output, pass request-level chattemplatekwargs:…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: deucebucket
Теги: gguf, GGUF, gemma4, gemma, google, quantized, cerebellum, imatrix
Лайков: 4 | Загрузок: 83
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
