nblt

nblt's Stars

• huggingface/transformers

  🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

  Language:Python137k1.1k16.4k27.4k

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.7k4264.2k6.4k

• microsoft/LoRA

  Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

  Language:Python11k70108699

• CuriousAI/mean-teacher

  A state-of-the-art semi-supervised method for image recognition

  Language:Python1.6k5759336

• jiaweizzhao/GaLore

  GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

  Language:Python1.5k1955154

• caiyuanhao1998/MST

  A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.

  Language:Python66997476

• noahgolmant/pytorch-hessian-eigenthings

  Efficient PyTorch Hessian eigendecomposition tools!

  Language:Python367152844

• aisingapore/sealion

  South-East Asia Large Language Models

  Language:Shell28322521

• MCG-NJU/MOC-Detector

  [ECCV 2020] Actions as Moving Points

  Language:Python269114337

• caiyuanhao1998/PNGAN

  "Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training" (NeurIPS 2021)

  Language:Python1358922

• bwconrad/vit-finetune

  Fine-tuning Vision Transformers on various classification datasets

  Language:Python963613

• ZhenYangIACAS/WeTS

  A benchmark for the task of translation suggestion

  Language:Mask592325

• Baijiong-Lin/LoRA-Torch

  PyTorch Reimplementation of LoRA (featuring with supporting nn.MultiheadAttention)

  Language:Python47273

• nblt/DLDR

  [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces

  Language:Python402113

• nblt/Sub-AT

  [CVPR 2022 oral] Subspace Adversarial Training

  Language:Python27234

• nblt/TWA

  [ICLR 2023] Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions

  Language:Python26202

• nblt/F-SAM

  [CVPR 2024] Friendly Sharpness-Aware Minimization

  Language:Python25230

• val-iisc/NuAT

  Towards Efficient and Effective Adversarial Training, NeurIPS 2021

  Language:Python171341

• devansh20la/LPF-SGD

  Language:Jupyter Notebook14337

• cychomatica/One-Pixel-Shotcut

  One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks (ICLR 2023 Spotlight)

  Language:Python12102

• ywher/TUFL

  The implementation of my paper "Threshold-adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation"

  Language:Python12404

• nblt/RWP

  Language:Python11101

• ywher/SS-ADA

  The official code for my paper SS-ADA

  Language:Python10111

• fanghenshaometeor/vanilla-adversarial-training

  vanilla training and adversarial training in PyTorch

  Language:Python9102

• nblt/mARWP

  [TMLR 2024] Revisiting Random Weight Perturbation for Efficiently Improving Generalization

  Language:Python8100

• fanghenshaometeor/Circular-teaching

  Codes for circular-teaching [working in progress...]

  Language:Python71

• TrustAIoT/CR-SAM

  Code for AAAI 2024 paper: CR-SAM: Curvature Regularized Sharpness-Aware Minimization

  Language:Python7211

• fanghenshaometeor/Orthogonal-Multi-Path

  This is an old version code for the paper Learn Robust Features via Orthogonal Multi-Path (https://arxiv.org/abs/2010.12190v1).

  Language:Python5102

• CoinCheung/mixMatch

  Pytorch reproduction of the experiment in the paper of MixMatch.

  Language:Python2301