Model Openness Tool combats openwashing in LLMs

TL;DR. A new Model Openness Tool (MOT) helps users identify whether large language models (LLMs) truly adhere to open-source definitions, fighting 'openwashing'. - Many LLMs advertised as open source frequently fail to meet Open Source Initiative (OSI) criteria due to restrictive licensing. - The tool aims to clarify model transparency and prevent legal risks for users assuming full open-source freedoms. - It provides a standardized framework for evaluating how open various AI models genuinely are.

• Many LLMs described as open source do not meet true open-source definitions due to restrictive licenses.
• The Model Openness Tool (MOT) helps users assess the actual openness of LLMs and combat 'openwashing'.
• The tool addresses inconsistencies in licensing that can expose users to legal risks.
• The Linux Foundation's AI & Data Foundation developed the Model Openness Framework to tackle these challenges.

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