Original model: https://huggingface.co/ibm-granite/granite-4.2-3b Model details: — Parameter count: 4B — Input support: text — Speculative decoding: no — imatrix: yes — details Don’t know which to choose? Grab Q4KM (2.32GB) — usually a good mix of size and performance. Download instructions available here These quants run with llama.cpp — installable in one line via llama.app: llama-server includes a built-in chat web UI, served at http://localhost:8080 by default. These quants were made with llama.cpp release b10603 — if this model’s architecture is newly supported, you’ll need that release or newer to run them. They also work in: LM Studio · koboldcpp · ramalama · Jan AI · Text Generation Web UI · LoLLMs · Atomic Chat All quants made using imatrix option, with a calibration corpus rendered through this model’s own chat template. The corpus pairs plain prose with tool-calling and reasoning conversations (corpus source data), encoded exactly as this model sees them at inference and processed with —parse-special, so chat-format special tokens contribute to the importance matrix. The corpus rendered for this model is included in this repo: granite-4.2-3b-calibration-v6.txt. The…
Модальности:
Генерация текста
Области применения:
Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: bartowski
Теги: gguf, granite, granite-4.2, reasoning, thinking, tool-calling, ibm, en
Лайков: 4 | Загрузок: 3,954
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
