python3 train.py --name cifar10-100_500 --dataset cifar10 --model_type ViT-B_16 --pretrained_dir checkpoint/ViT-B_16.npz. CIFAR-10 and CIFAR-100 are ... ... <看更多>
「cifar-100 vit」的推薦目錄:
- 關於cifar-100 vit 在 omihub777/ViT-CIFAR - GitHub 的評價
- 關於cifar-100 vit 在 PeizeSun/ViT-pytorch repositories - Hi,Github 的評價
- 關於cifar-100 vit 在 Transformers for Image Recognition at Scale | Deep Learner 的評價
- 關於cifar-100 vit 在 Quick demo of HuggingFace version of Vision Transformer 的評價
- 關於cifar-100 vit 在 The strategy of transferring ImageNet-21k ViT model to cifar100 的評價
- 關於cifar-100 vit 在 Vision Transformer (ViT) - An Image is Worth 16x16 Words 的評價
- 關於cifar-100 vit 在 Upernet github - ADR 的評價
- 關於cifar-100 vit 在 Upernet github 的評價
- 關於cifar-100 vit 在 How would I increase my accuracy in the cifar-100 dataset? I ... 的評價
cifar-100 vit 在 Transformers for Image Recognition at Scale | Deep Learner 的推薦與評價
Transformers의 계산 효율성 및 확장성으로 100B 이상의 parameter를 사용하여 전례 ... 더 큰 모델인 Vit-H/14는 ImageNet 및 CIFAR-100과 VTAB에서 성능이 더욱 향상 ... ... <看更多>
cifar-100 vit 在 Quick demo of HuggingFace version of Vision Transformer 的推薦與評價
Quick demo: Vision Transformer (ViT) by Google Brain ... where I fine-tune ViT on CIFAR-10 using the Trainer/PyTorch Lightning. ... Downloading: 100%. ... <看更多>
cifar-100 vit 在 The strategy of transferring ImageNet-21k ViT model to cifar100 的推薦與評價
Currently I use timm train.py to finetune the 'vit_base_patch16_224_miil_in21k' model on cifar100, however I can't get the reported result 94.2%. ... <看更多>
cifar-100 vit 在 Upernet github - ADR 的推薦與評價
Note that we only show models whose model sizes are under 100M. ... Comparison between the proposed LV-ViT and other re Swin-B(UperNet) 기본설정으로돌림-> ... ... <看更多>
cifar-100 vit 在 Upernet github 的推薦與評價
... ML tasks on well-known datasets - datasets like CIFAR-10 and ImageNet where ... Comparison between the proposed LV-ViT and other recent works based on ... ... <看更多>
cifar-100 vit 在 omihub777/ViT-CIFAR - GitHub 的推薦與評價
GitHub - omihub777/ViT-CIFAR: PyTorch implementation for Vision Transformer[Dosovitskiy, A.(ICLR'21)] ... 2.2 CIFAR-100. Accuracy Acc. C100. Loss Loss. C100 ... ... <看更多>