This repository contains custom APEX (Adaptive Precision for EXpert Models) -inspired quants, tuned specifically to the underlying mixture-of-experts architecture and focusing on intermediary-size tiers. ⚠️ Disclaimer: The layouts hosted here are custom-crafted and experimental. If you are looking for the standard, stable, and predictable APEX suite of this model, please visit mudler’s excellent repository here: (https://huggingface.co/mudler/gemma-4-26B-A4B-it-heretic-APEX-GGUF), where a complete baseline, uniform APEX suite is maintained. All credit for the underlying architecture, abliteration mechanics, and original model weights belongs entirely to the various upstream authors, and the imatrix-dataset was generated by mradermacher. Why APEX?** Regular uniform quantization applies compression equally across all layers, which can degrade MoE performance. The APEX layout locks the routing blocks at high-precision and shields vital shared experts, shifting aggressive compression strictly to redundant mid-layer tensors. Why custom?** The standard APEX configurations generally lack an intermediary tier, between high compression Mini & Compact and high precision Balanced & Quality.…
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Задача: Генерация текста
Автор: EmanuelOverride
Теги: gguf, gemma4, moe, pruning, reap, cerebras, expert-pruning, heretic
Лайков: 4 | Загрузок: 3,435
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
