An agent lives or dies by the small decisions. Read a file with the file tool, not with a shell one-liner. Start a long run in the background instead of letting it hang. Treat text that came back from a tool as data, never as an instruction. Carry a multi-step job through to the end instead of stopping after step one. Both values are measured on this model, not inherited from the base. One default for everything: temperature 0.1. It wins tool work outright and costs the chat nothing. There is no temperature at which this model thinks in loops — 1 request of 1,212 hit the token limit across the whole series. Every build in this table was measured individually against the same 101 held-out Exe AI cases as the full-precision model — same pass^3 rule. Sizes that dropped in measurement were not published. All builds carry an importance matrix (imatrix) from the same calibration set used across the Exe models. Q4KM is the recommended build. On the 6–8 GB machines this model is built for, the whole 4–5-bit class measures within the ruler’s noise band of each other (71–73 of 101); Q4KM is the best fit of size to memory. Q6K (77) is the pick when 8 GB of headroom exist. IQ3M is the floor.…
Модальности:
Генерация текста
Области применения:
Диалог / чат Вызов функций (Tool use)
Задача: Генерация текста
Автор: exe-ai-harness
Теги: gguf, exe-ai, agent, tool-use, moe, llama.cpp, en, endpoints_compatible
Лайков: 3 | Загрузок: 1,057
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
