Comments (2)
lessw2020
commented on May 19, 2024
1
Hi @lucidrains - thanks for the fast update! Working great now:
C:\Users\lessw>git clone https://github.com/lucidrains/vit-pytorch.git vit2
Cloning into 'vit2'...
remote: Enumerating objects: 97, done.
remote: Counting objects: 100% (97/97), done.
remote: Compressing objects: 100% (74/74), done.
remote: Total 97 (delta 54), reused 51 (delta 19), pack-reused 0
Unpacking objects: 100% (97/97), done.
re: optimizers - thanks for the kind words! I am hoping to test out adahessian btw with vit here as it's produced good results on transformers for nlp and may be ideal for vit as well (although with much higher gpu mem requirements to use).
Thanks again for making this repo and hope to be able to contribute as I work more with ViT!
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lucidrains
commented on May 19, 2024
@lessw2020 i've updated the ipynb filename in the latest commit, could you try again?
btw, thanks for all your open source optimizer work :)
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Related Issues (20)
- Potential regression with PT 2.0 and CUDA 12.2/CuDNN 8.9.4 HOT 1
- Not correctly understanding the Multi Head Attention part of the ViT implementation... HOT 3
- CvT with 1 channel input data HOT 2
- Layernorm in Cross attention HOT 4
- how to train HOT 2
- Questions about distill_loss HOT 1
- Trouble loading ViT - Dino structure for channels>3?
- Question regarding 1d fft use HOT 1
- Masking attention with batches
- can we use CvT model for segmentation?
- Multi-target Regression Question
- Problems regarding training 3D Vision transformer : model does not converge
- Add implementation of LongVit HOT 4
- A question with ViT 3d
- Cuda memory for 3D VIT HOT 2
- PyPi page markdown render HOT 1
- CrossViT does not handle other than three channel images HOT 2
- Non-deterministic results based on group_max_seq_len in NaViT HOT 3
- Whether to include pre-trained models
- Request for Pre-trained Weights for Vit
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