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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
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs—0
Data-Free Quantization via Pseudo-label Filtering—0
Robustness-Guided Image Synthesis for Data-Free Quantization—0
Causal-DFQ: Causality Guided Data-free Network QuantizationCode0
Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning—0
QNNRepair: Quantized Neural Network Repair—0
Rethinking Data-Free Quantization as a Zero-Sum GameCode0
ACQ: Improving Generative Data-free Quantization Via Attention Correction—0
Genie: Show Me the Data for QuantizationCode0
Zero-Shot Learning of a Conditional Generative Adversarial Network for Data-Free Network Quantization—0
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