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Bayesian Bits: Unifying Quantization and Pruning.

, , , , , , и . NeurIPS, (2020)

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Markus Nagel

Markus Nagel

Sebastian Nagel

Edgar Nagel

Michael Nagel

 

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Understanding and Overcoming the Challenges of Efficient Transformer Quantization., , и . EMNLP (1), стр. 7947-7969. Association for Computational Linguistics, (2021)QBitOpt: Fast and Accurate Bitwidth Reallocation during Training., , , , и . ICCV (Workshops), стр. 1274-1283. IEEE, (2023)Up or Down? Adaptive Rounding for Post-Training Quantization., , , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 7197-7206. PMLR, (2020)A Practical Mixed Precision Algorithm for Post-Training Quantization., , , , , и . BMVC Workshop, BMVA Press, (2023)Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters., , , , , , , , , и 2 other автор(ы). CoRR, (2024)In-Hindsight Quantization Range Estimation for Quantized Training., и . CVPR Workshops, стр. 3063-3070. Computer Vision Foundation / IEEE, (2021)Bayesian Bits: Unifying Quantization and Pruning., , , , , , и . NeurIPS, (2020)Low-Rank Quantization-Aware Training for LLMs., , и . CoRR, (2024)Sparse High Rank Adapters., , , , , , , , , и 2 other автор(ы). CoRR, (2024)Softmax Bias Correction for Quantized Generative Models., , , и . ICCV (Workshops), стр. 1445-1450. IEEE, (2023)