The AI development community is increasingly making use of hosting intermediaries such as Hugging Face provide easy access to user-uploaded models and training data. These model marketplaces lower technical deployment barriers for hundreds of thousands of users, yet can be used in numerous potentially harmful and illegal ways. In this article, we explain ways in which AI systems, which can both `contain' content and be open-ended tools, present one of the trickiest platform governance challenges seen to date. We provide case studies of several incidents across three illustrative platforms -- Hugging Face, GitHub and Civitai -- to examine how model marketplaces moderate models. Building on this analysis, we outline important (and yet nevertheless limited) practices that industry has been developing to respond to moderation demands: licensing, access and use restrictions, automated content moderation, and open policy development. While the policy challenge at hand is a considerable one, we conclude with some ideas as to how platforms could better mobilize resources to act as a careful, fair, and proportionate regulatory access point.

翻译：人工智能开发社区日益依赖如Hugging Face等托管中介，以方便用户获取上传的模型和训练数据。这些模型市场降低了数十万用户的技术部署门槛，但同时也可能被用于多种有害或非法用途。本文阐释了AI系统既可能“包含”内容又可能成为开放式工具的特性，如何构成了迄今最棘手的平台治理挑战之一。我们通过对Hugging Face、GitHub和Civitai三个典型平台的案例研究，剖析了模型市场如何对模型进行调适。基于此分析，我们概述了行业为应对调适需求而发展出的重要（但仍有局限）实践：许可授权、访问与使用限制、自动化内容审核以及开放政策制定。尽管当前面临的政策挑战十分严峻，我们最终提出了一些关于平台如何更有效调动资源、作为审慎、公平且适度的监管接入点的思路。