FedWSQ applies weight standardization in federated learning and uses Gaussian-optimal non-uniform quantization with a shared global scaling vector, improving accuracy at very low bit rates.
Qlora: Efficient finetuning of quantized llms
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FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
FedWSQ applies weight standardization in federated learning and uses Gaussian-optimal non-uniform quantization with a shared global scaling vector, improving accuracy at very low bit rates.