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microsoft/unilm

A comprehensive research hub for large-scale self-supervised pre-training of foundation models across diverse tasks, languages, and modalities.

Core Features

Pioneers novel foundation architectures (e.g., DeepNet, RetNet, LongNet, BitNet).

Develops advanced multimodal large language models (e.g., Kosmos series, MetaLM).

Offers specialized pre-trained models for language, vision, and speech tasks.

Focuses on enhancing model stability, generality, capability, efficiency, and transferability.

Supports extensive multilingual and cross-lingual AI applications.

Detailed Introduction

Microsoft's `unilm` project is a leading AI research initiative focused on large-scale self-supervised pre-training, aiming to build robust foundation models. It integrates diverse research streams, from novel architectures like DeepNet and RetNet to multimodal LLMs such as Kosmos. The project addresses challenges across various tasks, over 100 languages, and multiple modalities including text, image, and audio. By emphasizing stability, generality, capability, and efficiency, `unilm` drives the convergence towards more general and powerful AI systems, providing a platform for cutting-edge innovation in model design and application.