LMFlow

Full training stack: Supports continuous pretraining, instruction tuning, parameter-efficient fine-tuning, alignment tuning, and inference in one toolkit.

Lightweight design: Easier to use and extend than heavier frameworks like Megatron or DeepSpeed for practitioners who want to iterate quickly.

Community adoption: Became a popular tool in the open-source LLM ecosystem for reproducing fine-tuning recipes.

Training ecosystem: Part of the broader 2023 proliferation of accessible LLM training tooling (Axolotl, LLaMA-Factory, LitGPT) that enabled community fine-tuning.