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A modification to llama.cpp allows real-time hot-swapping of the Ngram PLE Table for Qwen models, enabling knowledge injection and suggesting new ways for low-cost training.
DeadPool introduces a fault-tolerance mechanism for LLM training that enables hot-swapping of failed nodes with spare nodes using zero-overhead in-memory checkpointing, achieving fast recovery without interrupting the job.