OLMo 2 1B is the smallest model in the OLMo 2 family, featuring a transformer-style architecture with 4 trillion training tokens. It supports multiple models and fine-tuning options, and is designed for language modeling applications. The model and its associated resources are available on GitHub under an Apache 2.0 license.

Liquid is an innovative auto-regressive model that integrates visual comprehension and generation by tokenizing images into discrete codes and learning them alongside text tokens. This multimodal large language model operates within a shared feature space, allowing for seamless understanding and generation without relying on external visual embeddings. Liquid is available in multiple sizes and explores the scaling laws of multimodal models, revealing mutual benefits between understanding and generation tasks.