nateraw / huggingface-vit-finetune
Finetune Google's pre-trained ViT models from HuggingFace's model hub.
☆18Updated 3 years ago
Alternatives and similar repositories for huggingface-vit-finetune:
Users that are interested in huggingface-vit-finetune are comparing it to the libraries listed below
- ☆95Updated 2 years ago
- Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"☆47Updated 6 months ago
- This is a PyTorch implementation of the paperViP A Differentially Private Foundation Model for Computer Vision☆36Updated last year
- Official Implementation for PlugIn Inversion☆16Updated 3 years ago
- Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation☆44Updated last year
- Recycling diverse models☆44Updated 2 years ago
- Patching open-vocabulary models by interpolating weights☆91Updated last year
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 3 years ago
- PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures (CVPR 2022)☆103Updated 2 years ago
- ☆57Updated last year
- Code for T-MARS data filtering☆35Updated last year
- ☆26Updated 2 years ago
- ☆34Updated 6 months ago
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆81Updated 3 years ago
- Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)☆38Updated 3 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆29Updated 2 years ago
- Implementation of Beyond Neural Scaling beating power laws for deep models and prototype-based models☆33Updated last month
- ☆28Updated last year
- ☆21Updated 2 years ago
- Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training wi…☆52Updated 3 years ago
- ☆17Updated 2 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆25Updated last year
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"☆15Updated 2 years ago
- This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.☆70Updated 2 years ago
- Release of ImageNet-Captions☆45Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 2 years ago
- PRIME: A Few Primitives Can Boost Robustness to Common Corruptions☆42Updated 2 years ago
- Host CIFAR-10.2 Data Set☆13Updated 3 years ago