Checkpointing is a special task in the modern deep learning training process as it poses a hard tradeoff between training efficiency and reliability. Frequent checkpoints of model states can enhance ...

Ternary quantization has emerged as a powerful technique for reducing both computational and memory footprint of large language models (LLM), enabling efficient real-time inference deployment without ...