Comments (2)
going to close this. documentation is in and we will aim to rather push the moco-v3 implementation.
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ConViT released in latest release: https://github.com/facebookresearch/vissl/releases/tag/v0.1.6.
Documentation is here: https://vissl.readthedocs.io/en/v0.1.6/ssl_approaches/vision_transformers.html?highlight=convit#convit
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Related Issues (20)
- Example of using ZeRO and LARC
- Incosistent results when running inference on trained resnet model HOT 1
- Low performance of Supervised training
- MLP_DIM in ViT is not adjustable through the config. HOT 2
- [Feature] Online linear probing
- Linear Image classification weights not loading properly: vissl pretrained models simclr or Dcv2 HOT 3
- "on_forward"-hook operations and back-propagation
- EMA does not work on fp16 and does not copy weights?
- First-class support for timm models
- Can't load pretrained seer/swav checkpoints (RG_Y_128GF) HOT 1
- Is it possible to get full imagenet pretrained weights of MoCo v2 ? HOT 2
- NPID + MoCoV2 weights are the same? HOT 1
- Potential confusion over licensing comment
- Does the MoCo implementation do shuffled Batch Norm when run on a single GPU? HOT 3
- Loading TRAINED models with VISSL HOT 9
- Use pretrain outside of vissl
- can someone share/has anyone shared a checkpoint ( with the class head) of a ssl model on imagenet?
- What config relate to learning rate warm up, weight decay, and momentum in 1 node n GPUs (n > 1 && n < 8) config?
- AttributeError: module 'importlib_resources' has no attribute 'is_resource'
- all vissl.ai/tutorials links broken
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