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A Speed Odyssey for Deployable Quantization of LLMs
The large language model era urges faster and less costly inference.
FPTQ: Fine-grained Post-Training Quantization for Large Language Models
In this study, we propose a novel W4A8 post-training quantization method for the available open-sourced LLMs, which combines the advantages of both two recipes.
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