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Found 3 papers, 3 papers with code
Effective Quantization for Diffusion Models on CPUs
Diffusion models have gained popularity for generating images from textual descriptions.
TEQ: Trainable Equivalent Transformation for Quantization of LLMs
As large language models (LLMs) become more prevalent, there is a growing need for new and improved quantization methods that can meet the computationalast layer demands of these modern architectures while maintaining the accuracy.
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Large Language Models (LLMs) have demonstrated exceptional proficiency in language-related tasks, but their deployment poses significant challenges due to substantial memory and storage requirements.
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