Comments (2)
The default branch for torch hub load is master, but facebookresearch/dino
uses main
, so you need to specify the branch you are downloading, e.g.
deits16 = torch.hub.load('facebookresearch/dino:main', 'dino_deits16')
from dino.
The default branch for torch hub load is master, but
facebookresearch/dino
usesmain
, so you need to specify the branch you are downloading, e.g.deits16 = torch.hub.load('facebookresearch/dino:main', 'dino_deits16')
from dino.
Related Issues (20)
- Hyperparameters for ViT-B/16 + ImageNet pretraining
- issue with the ViT-S/8 full checkpoint
- Intermediate checkpoints?
- Facing Accuracy Drop while running in QDQ onnx runtime
- Why the patchembedding defaut img size is not equal to the image size in visualize attention? HOT 1
- Loss Nan Error
- Difference between DINO and DINOv2
- For large batches (256), there is a problem of loss non convergence
- Why not setting correct img_size when building the student network? HOT 1
- Why do we skip cases where the student and teacher operate on the same view? If they are operating on different views, why should they produce similar results to calculate the cross-entropy loss? HOT 1
- a solution to solve memory issues (but slows down training a bit)
- Best features for image similarity HOT 1
- Loss is not decresing HOT 4
- Why Teacher network perform bettert than Student one during training? HOT 1
- How to convert to onnx HOT 2
- Can I use dino model to match images with pixels? Just like with the clip model you can match pixels with text. HOT 1
- Choice of out_dim HOT 1
- Cannot reproduce KNN performance for vanilla ViT-S training HOT 1
- Reproducing results on segmentation using training from scratch
- Changing number of classes
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