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FlattenQuant: Breaking Through the Inference Compute-bound for Large Language Models with Per-tensor Quantization
The 4-bit matrix multiplication introduced in the FlattenQuant method can effectively address the compute-bound caused by large matrix calculation.
Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment
Large language models (LLMs) such as GPT-3, OPT, and LLaMA have demonstrated remarkable accuracy in a wide range of tasks.
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