White Circle 推出 Halo 框架：开源模型后训练吞吐量达 TRL 的 2.8 倍
Training models is becoming easier and easier - just look at this and TRL - especially with agents! ...
想自己微调模型可以看看 White Circle 的 Halo，吞吐量达 TRL 的 2.8 倍、更省内存，还不用转格式，已开源。
White Circle 发布开源框架 Halo，定位为开源模型后训练工具。官方数据显示其吞吐量最高达到原版 TRL 的 2.8 倍，峰值内存占用更低。Halo 让模型保持原生 HuggingFace 格式，训练后无需额外转换。代码已在 GitHub 开源，Hugging Face CEO Clement Delangue 转发推荐，称训练模型正变得越来越容易。
Training models is becoming easier and easier - just look at this and TRL - especially with agents! ...
Training models is becoming easier and easier - just look at this and TRL - especially with agents! You're missing out if you're still using off the shelf models for all your tasks! White Circle @whitecircle Introducing Halo, the best framework for post-training of open-source models. Halo delivers up to 2.8x the throughput of stock TRL with less peak memory, while models stay in their native HuggingFace format. Star us on GitHub: github.com/whitecircle/ha… Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 2 🔄 0 ❤️ 26 👀 1816 📊 4 ⚡
