Hugging Face 推出 ML Intern，通过聊天即可运行机器学习实验

Hugging Face 推出了“ML Intern”，这是一个内置于其聊天机器人的 AI 助手，让用户无需任何机器学习专业知识即可运行机器学习实验。用户首先在对话中描述他们的想法。该助手：https://huggingface.co/chat/ 然后搜索 Hugging Face Hub、GitHub 和网络，以找到合适的模型、数据集和工具。在开始任何操作之前，ML Intern 会估算所需的计算成本并建议预算。一旦批准，它将不会超过该限制。

从此系统将自主运行。它可以创建数据集、训练模型、监控运行中的任务、将结果上传到 Hub、撰写报告以及构建演示。每次训练运行都会有自己的仪表板用于跟踪进度。根据 Hugging Face 的说法，演示视频中的一个示例运行了大约六个小时，花费不到 0.50 美元。

该工具降低了在平台上开展新 ML 项目的门槛。与此同时，Hugging Face 本身正处于被 Nvidia 收购的过程中：https://the-decoder.com/nvidia-buys-the-front-door-to-open-ai-as-closed-labs-increasingly-design-their-own-silicon/。CEO 黄仁勋承诺会保持平台开放且硬件中立。广告 广告

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Hugging Face launched "ML Intern," an AI assistant built into its chatbot that lets users run machine learning experiments without any ML expertise. Users start by describing their idea in a conversation. The assistant：https://huggingface.co/chat/ then searches the Hugging Face Hub, GitHub, and the web to find the right models, datasets, and tools. Before kicking anything off, ML Intern estimates the required compute costs and suggests a budget. Once approved, it won't exceed that limit.

From there, the system works on its own. It can create datasets, train models, monitor running jobs, upload results to the Hub, write reports, and build demos. Each training run gets its own dashboard for tracking progress. One example from the demo video ran for about six hours and cost less than $0.50, according to Hugging Face.

The tool lowers the barrier for new ML projects on the platform. Meanwhile, Hugging Face itself is in the middle of an acquisition by Nvidia：https://the-decoder.com/nvidia-buys-the-front-door-to-open-ai-as-closed-labs-increasingly-design-their-own-silicon/. CEO Jensen Huang has promised to keep the platform open and hardware-neutral. Ad Ad

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