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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 1–10 of 37 papers

TitleStatusHype
DVD-Quant: Data-free Video Diffusion Transformers QuantizationCode1
OuroMamba: A Data-Free Quantization Framework for Vision Mamba Models—0
Enhancing Diversity for Data-free Quantization—0
Semantics Prompting Data-Free Quantization for Low-Bit Vision Transformers—0
Relation-Guided Adversarial Learning for Data-free Knowledge TransferCode1
A method of using RSVD in residual calculation of LowBit GEMM—0
Privacy-Preserving SAM Quantization for Efficient Edge Intelligence in Healthcare—0
MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity—0
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs—0
Data-Free Quantization via Pseudo-label Filtering—0
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