Jun Kim, oMLX creator and maintainer, joins Hugging Face to support the MLX community

Jun Kim, oMLX 的创建者兼维护者加入 Hugging Face，以支持 MLX 社区

We are super excited to welcome Jun as our newest team member 🔥. We are completely invested in local AI, and MLX is a central piece of the ecosystem. We are delighted that Jun chose us to set up home and continue contributing to MLX.

我们非常激动地欢迎 Jun 成为我们团队的最新成员 🔥。我们全力投入于本地 AI 领域，而 MLX 是该生态系统的核心部分。我们很高兴 Jun 选择加入我们，在这里安家并继续为 MLX 做出贡献。

MLX is Apple’s framework for local AI, especially optimized for Apple Silicon. We are big MLX supporters since it was the Christmas present from Awni and Angelos in 2023, and proud that Hugging Face is the Hub where people find MLX models and contribute their own. Usage of open, local AI is accelerating, and we believe in a healthy ecosystem where people can find the tools that work for them.

MLX 是苹果公司用于本地 AI 的框架，专门针对 Apple Silicon 进行了优化。自 2023 年 Awni 和 Angelos 将其作为圣诞礼物发布以来，我们一直是 MLX 的坚定支持者。我们很自豪 Hugging Face 能够成为人们寻找 MLX 模型并贡献自己作品的中心。开放式本地 AI 的使用正在加速，我们相信一个健康的生态系统能让人们找到适合自己的工具。

What is the impact for oMLX? Stability, and hopefully faster development! Graduating from a side job to a fully maintained and funded project will allow Jun to better guide the contributors and build for the long-term. oMLX stays Apache 2.0, and Jun keeps leading it as before.

这对 oMLX 有什么影响？是稳定性，以及有望实现更快的开发！从副业转变为一个有充分维护和资金支持的项目，将使 Jun 能够更好地引导贡献者并进行长期建设。oMLX 将保持 Apache 2.0 协议，Jun 也将像以前一样继续领导该项目。

What is the impact for MLX at large? Our end goal is to unblock the community to run local AI in any shape or form, and provide the tools and building blocks to make that happen. We expect oMLX to serve as a testbed for new ideas, while leveraging the foundational work of the dependencies it already relies upon, such as mlx-lm or mlx-vlm.

这对整个 MLX 生态有什么影响？我们的最终目标是帮助社区以任何形式运行本地 AI，并提供实现这一目标的工具和构建模块。我们期望 oMLX 能够作为新想法的试验场，同时利用其已依赖的底层工作，例如 mlx-lm 或 mlx-vlm。

We believe that strong modeling and inference libraries help the community, so we’d love to upstream work to wherever it makes sense. We have been collaborating with many projects mlx-lm, mlx-vlm, LMStudio, and we hope we can strengthen the relationship with Cheng, Prince, Yagil, and their teams to better serve the community together.

我们相信强大的建模和推理库对社区有帮助，因此我们乐于在合理的地方将工作向上游合并。我们一直在与 mlx-lm、mlx-vlm、LMStudio 等多个项目合作，希望能够加强与 Cheng、Prince、Yagil 及其团队的关系，共同更好地服务社区。

Concretely, one focus area is the quick transition from a transformers model definition to a reference MLX implementation that can be consumed by different engines, so each one can focus on the unique features they provide. The transformers library has become the reference for ML model definitions, we want to streamline the process to make new transformers models run on MLX. We are incredibly excited about the future. Welcome, Jun! 🙌

具体来说，一个重点领域是实现从 transformers 模型定义到可被不同引擎调用的参考 MLX 实现的快速转换，这样每个引擎都可以专注于其提供的独特功能。transformers 库已成为 ML 模型定义的参考标准，我们希望简化流程，让新的 transformers 模型能够在 MLX 上运行。我们对未来感到无比兴奋。欢迎你，Jun！🙌