NUS-HPC-AI-Lab/Dynamic-Tuning

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Created 2 months ago
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NUS-HPC-AI-Lab/Dynamic-Tuning

NUS-HPC-AI-Lab

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The official implementation of "2024Arxiv Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"

OpenDiT

OpenDiT: An Easy, Fast and Memory-Efficient System for DiT Training and Inference

Neural-Network-Diffusion

We introduce a novel approach for parameter generation, named neural network diffusion (\textbf{p-diff}, p stands for parameter), which employs a standard latent diffusion model to synthesize a new set of parameters

InfoBatch

Lossless Training Speed Up by Unbiased Dynamic Data Pruning

DATM

ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

LARS-ImageNet-PyTorch

Accuracy 77%. Large batch deep learning optimizer LARS for ImageNet with PyTorch and ResNet, using Horovod for distribution. Optional accumulated gradient and NVIDIA DALI dataloader.

oh-my-server

GEOM

Pytorch implementation of "Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching"

pytorch-lamb

PyTorch implementation of LAMB for ImageNet/ResNet-50 training

Helen

The official implementation of "Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization"

CTRL

Pytorch implementation of "Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching"