Photo7B is a 7-billion parameter multimodal model designed to bridge the gap between high-resolution visual perception and natural language reasoning. By leveraging a decoupled vision encoder and a robust language backbone, Photo7B achieves state-of-the-art performance on benchmarks requiring fine-grained image detail and complex instructional following. 1. Architecture Overview
Focuses on "feature alignment" using massive image-text pairs (e.g., LAION-5B). The goal is to teach the LLM what objects look like without updating the LLM weights.
Explaining complex scenes or reading text within images (OCR).
Photo7B is a 7-billion parameter multimodal model designed to bridge the gap between high-resolution visual perception and natural language reasoning. By leveraging a decoupled vision encoder and a robust language backbone, Photo7B achieves state-of-the-art performance on benchmarks requiring fine-grained image detail and complex instructional following. 1. Architecture Overview
Focuses on "feature alignment" using massive image-text pairs (e.g., LAION-5B). The goal is to teach the LLM what objects look like without updating the LLM weights.
Explaining complex scenes or reading text within images (OCR).
