The GRaPE Family was trained on about 14 billion tokens of data after pre-training. About half was code related tasks, with the rest being heavy on STEAM. Ensuring the model has a sound logical basis. GRaPE Flash and Nano are monomodal models, only accepting text. GRaPE Mini being trained most recently supports image and video inputs. As GRaPE Mini is the only model that thinks, it has some support for reasoning modes. In testing, these modes sometimes work. Likely due to an innefficient dataset formatting for it. To use thinking modes, you need an XML tag, `, which can equal these values: — Minimal: Skip thinking (does not work most of the time, you’ll have to be careful with this one) — Low: Think Below 1024 tokens — Medium: Think between 1024 and 8192 tokens — High: Think for any amount above 8192 tokens In your prompt, place the thinking mode at the end of your prompt, like this: I recommend using LM Studio for running GRaPE Models, and have generally found these sampling parameter This was a demo proving the efficiency and power this architecture can make. GRaPE Mini is…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: SL-AI
Теги: qwen3_vl, image-text-to-text, conversational, en, endpoints_compatible
Лайков: 3 | Загрузок: 25
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
