Innovator-VL-8B-Thinking is a multimodal reasoning-oriented large language model designed for complex scientific problem solving. Built upon Innovator-VL-8B-Instruct, this model is further optimized for explicit multi-step reasoning, long-horizon chain-of-thought generation, and token-efficient scientific analysis. The model is particularly suitable for scientific tasks that require structured reasoning over visual and textual evidence, such as mathematics, chemistry, materials science, and multimodal scientific benchmarks. — Model Type: Vision-Language Reasoning Model — Parameter Size: 8B — Base Language Model: Qwen3-8B-Base — Vision Encoder: RICE-ViT — Projector: PatchMerger The model supports native-resolution multi-image inputs and is optimized for reasoning-intensive multimodal scenarios. Innovator-VL-8B-Thinking is trained to explicitly generate structured reasoning traces, enabling the model to: — Perform multi-step logical deduction grounded in visual evidence — Solve complex mathematical and scientific problems — Maintain reasoning consistency across long contexts The model is further optimized using reinforcement learning to improve: — Reasoning correctness -…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: InnovatorLab
Теги: innovator_vl, conversational, custom_code, en, zh
Лайков: 4 | Загрузок: 17
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
