Halo: open-source post-training framework claims 2.8x TRL throughput with lower memory
_akhaliq · x · 2026-09-22
White Circle has released Halo, an open-source framework for post-training of open-source LLMs and multimodal models, claiming up to 2.8x the throughput of stock TRL with lower peak memory usage while keeping weights in native HuggingFace format.
- Apache-2.0 licensed on GitHub
- Ships vLLM and SGLang docker-compose configs (with EFA multi-node support), examples, and skills directories
- A new project (31 commits), so the performance claims remain to be independently verified
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