This Paper Introduces AQLM: A Machine Learning Algorithm that Helps in the Extreme Compression of Large Language Models via Additive Quantization

In the rapidly advancing domain of artificial intelligence, the efficient operation of large language models (LLMs) on consumer-level hardware represents a significant technical challenge. This issue arises from the inherent trade-off between the models’ size and computational efficiency. Compression methods, including direct and multi-codebook quantization (MCQ), have offered partial solutions to minimize these AI behemoths’ […]

The post This Paper Introduces AQLM: A Machine Learning Algorithm that Helps in the Extreme Compression of Large Language Models via Additive Quantization appeared …

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