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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
As the number of bits decreases, the quantization grid broadens, thus emphasizing the importance of up and down rounding.
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