Comments (1)
I tried the scheduler from the paper, turns out to be totally instable. I'd also be curious to know the reason. The architecture seems identical.
from enhancing-transformers.
Related Issues (20)
- Pre-norm and Post-norm HOT 6
- An inplace operation in the forward process HOT 1
- Reconstruction Visualization HOT 2
- stage2 transformer HOT 2
- stage1 pretraining HOT 7
- Model license HOT 4
- stage2 transform HOT 9
- about training loss HOT 1
- The question is done. HOT 1
- ImageNet version.
- Reconstruction results HOT 4
- why not used pretrained discriminator
- Incomplete implementation of RQ-VAE
- raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['where', 'cl']' returned non-zero exit status 1. HOT 5
- Results HOT 5
- Smaller images HOT 10
- OOM for imagenet_gpt_vitvq_base and a 100M params GPT on A100 40G HOT 3
- Pretrained Stage 2 Transformer for ViT-VQGAN HOT 8
- Training time and number of GPUS HOT 6
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from enhancing-transformers.