In iterative pruning, you create a binary mask for each iteration that contains pruning information. Applying the mask to the weights array does not change either the size of the array or the structure of the n
Large Models (LMs) have recently captured considerable public interest. Their ability to understand context and nuances enables them to proficiently handle diverse tasks across multiple domains, including natural language processing (NLP), computer vision (CV), etc. In the field of NLP, Large Languag...
Pruning and quantization algorithm with applications in memristor-based convolutional neural network Article 19 January 2023 References Cerquitelli T, Meo M, Curado M, Skorin-Kapov L, Tsiropoulou EE. Machine learning empowered computer networks. Elsevier; 2023. p. 109807. Chandrasekar A, Rakki...
LoRAPruning不仅对预训练模型权重采用结构化剪枝,而且对 LoRA 权重也采用结构化剪枝。非结构化 LoRA 剪枝方法主要侧重于稀疏模型权重,同时保持 LoRA 权重的密集性,从而使权重合并难以实现,与此相反,LoRAPruning 可以轻松合并权重。此外,这项工作还引入了一种新颖的标准,利用 LoRA 梯度作为预训练权重梯度的近似值,从而能...
Quantization: For Jetson devices, consider using TensorRT for model optimization. TensorRT can significantly improve inference speed without compromising much on accuracy. Pruning: Model pruning can help reduce the model size and increase inference speed. You might want to explore this if you haven't...
(2022b). Qoc: quantum on-chip training with param- eter shift and gradient pruning. In Proceedings of the 59th ACM/IEEE Design Automation Conference, pp. 655–660 Wossnig, L. (2021). Quantum machine learning for classical data. CoRR abs/2105.03684 Zhang, K., Liu, L., Hsieh, M. H...
Pruning AGP Pruner Slim Pruner FPGM Pruner NetAdapt Pruner SimulatedAnnealing Pruner ADMM Pruner AutoCompress Pruner Quantization QAT Quantizer DoReFa Quantizer Feature Engineering (Beta) GradientFeatureSelector GBDTSelector Early Stop Algorithms Median Stop Curve Fitting Local Machine Remote Servers...
●混合式PEFT:结合多种PEFT 方法的优点,例如 UniPELT 结合了 LoRA、Prefix-tuning 和 Adapter。 一些研究还利用神经架构搜索 (NAS) 来寻找最佳的 PEFT 方法组合。 >> 核心思路步骤:PEFT 方法的核心思路步骤大致如下: ● 选择 PEFT 方法:根据具体任务和模型选择合适的 PEFT 方法。
NNI provides CommandLine Tool as well as an user friendly WebUI to manage training experiments. With the extensible API, you can customize your own AutoML algorithms and training services. To make it easy for new users, NNI also provides a set of build-in stat-of-the-art AutoML algorithms...
NNI provides CommandLine Tool as well as an user friendly WebUI to manage training experiments. With the extensible API, you can customize your own AutoML algorithms and training services. To make it easy for new users, NNI also provides a set of build-in stat-of-the-art AutoML algorithms...