从 Jev 看专用模型与多样化 AI 生态
我喜欢 Jev 的地方：多年来，大型通用模型几乎吸走了 AI 领域所有的氧气。
但在更专业化和定制化的模型中，有着巨大的机会，这些模型是为特定任务和语言构建的，因此成本便宜几个数量级、更快、更优化。有 300 万个这样的模型在 @huggingface 上公开可用。
让我们构建一个更加多样的 AI 生态系统吧！
根据@julien_c (https://x.com/julien_c/status/2102044472108282351?s=20) 的说法，你可以在这里找到Jev任务的开源模型：https://huggingface.co/models?pipeline_tag=zero-shot-classification&sort=trending
对照原文
What I like about Jev: for years, large generalist models sucked almost all the oxygen out of AI. But there are huge opportunities in much more specialized and customized models, built for specific tasks and languages and as a result, orders of magnitude cheaper, faster and more optimized. There are 3 million of them publicly available on @huggingface. Let's build a much more diverse AI ecosystem!
according to @julien_c (https://t.co/OihGaAaPBf), you'll find open-source models for Jev's task here: https://t.co/bkiqoGrkv8