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Data Free Quantization

Data Free Quantization is a technique to achieve a highly accurate quantized model without accessing any training data.

Source: Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples

Papers

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Showing 21–30 of 37 papers

TitleStatusHype
Zero-Shot Learning of a Conditional Generative Adversarial Network for Data-Free Network Quantization—0
A method of using RSVD in residual calculation of LowBit GEMM—0
Towards Feature Distribution Alignment and Diversity Enhancement for Data-Free Quantization—0
Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning—0
Data-Free Quantization via Pseudo-label Filtering—0
Data-Free Quantization with Accurate Activation Clipping and Adaptive Batch Normalization—0
Diversifying Sample Generation for Accurate Data-Free Quantization—0
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs—0
Enhancing Diversity for Data-free Quantization—0
Generative Zero-shot Network Quantization—0
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