InternVL-U is a 4B-parameter unified multimodal model (UMM) that brings multimodal understanding, reasoning, image generation, image editing into a single framework.
Principalele funcționalități ale opengvlab/internvl-u sunt: Unified Models, Unified Multimodal Models.
Alternativele open-source pentru opengvlab/internvl-u includ: bytedance/lance — A 3B-active-parameter native unified multimodal model for image and video understanding, generation, and editing. alpha-vllm/lumina-dimoo — Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding. byteflow-ai/tokenflow — [CVPR 2025] 🔥 Official impl. of "TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation". deepseek-ai/janus — Janus is a multimodal large language model and unified framework that integrates visual understanding and image… facebookresearch/tuna-2 — Official implementation of Tuna-2: Pixel Embeddings Beat Vision Encoders for Unified Understanding and Generation. lehduong/onediffusion.
A 3B-active-parameter native unified multimodal model for image and video understanding, generation, and editing.
Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding
CVPR 2025 🔥 Official impl. of "TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation".
Janus is a multimodal large language model and unified framework that integrates visual understanding and image generation within a single neural network. It functions as both a visual understanding model for analyzing images and a text-to-image generator. The system uses a unified transformer backbone and a multimodal latent space to bridge the gap between text and visual data. This architecture employs decoupled visual encoding and cross-modal tokenization to separate the paths for discriminative understanding and generative tasks, representing images as grids of discrete codes. The projec