@DanKornas: Most AI agents still split vision, language, and action across separate systems. Magma is a Microsoft Research foundati…
Summary
Magma is an open-source repository from Microsoft Research for building multimodal AI agents that integrate vision, language, and action, providing model links, inference examples, training instructions, and demos.
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Most AI agents still split vision, language, and action across separate systems.
Magma is a Microsoft Research foundation model repo for multimodal AI agents that need to perceive images/videos and produce goal-driven actions.
It helps you study and prototype agentic models by putting the paper, model links, inference examples, training instructions, evaluation paths, and demos in one place.
Key features:
• Multimodal agent focus – designed around image/video understanding plus goal-driven visual plans and actions • Model access – README links Magma-8B on Hugging Face and Azure AI Foundry • Multiple inference paths – examples for Hugging Face Transformers, local repo code, and bitsandbytes • Training docs – includes Open-X pretraining notes and Magma-820K finetuning instructions • Agent tooling – includes lmms-eval, SimplerEnv, FastAPI server, UI agent, gaming agent, and robot visual-planning demo docs
It’s open-source (MIT license).
Link in the reply
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Mage (GitHub Repo)
Microsoft releases Mage, a family of lightweight 4B-parameter multimodal models for visual understanding and generation, including Mage-VL for image/video understanding and Mage-Flow for text-to-image generation and editing, designed for research and deployment on modest hardware.