Our approach is the first 32-bit integer-based edge kernel implementation for vision transformers with post-training integer-only quantization, ensuring both ...
Our approach is the first 32-bit integer-based edge kernel implementation for vision transformers with post-training integer-only quantization, ensuring both ...
Semantic Scholar extracted view of "Practical Edge Kernels for Integer-Only Vision Transformers Under Post-training Quantization" by Zining Zhang et al.
Dive into the cutting-edge with this curated list of papers on Vision Transformers (ViT) quantization and hardware acceleration, featured in top-tier AI ...
Jul 4, 2022 · In this paper, we propose I-ViT, an integer-only quantization scheme for ViTs, to enable ViTs to perform the entire computational graph of inference with ...
Quantization is a promising approach to reducing model complexity, and the dyadic arithmetic pipeline can allow the quantized models to perform efficient ...
[MLSys'23] Practical Edge Kernels for Integer-Only Vision Transformers Under Post-training Quantization, National university of Singapore. [ACL'22] AraT5 ...
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Quantizing vision transformers with our mixed non-linear quantization approach reduces quantization error in non-linear layers on a layerwise basis, allowing ...
In this paper, we propose an activation-aware fully sub-8-bit quantization-aware training (QAT) framework called PackQViT for efficient yet accurate ViT ...
Practical edge kernels for integer-only vision transformers under post- training quantization. Proceedings of Machine Learning and. Systems, 5, 2023. 3. 3657.