Comments (2)
40GB VRAM is enough for both stages. If you encounter the OOM error of GPU in training, you can try to reduce 1) batch size 2) video size (height, width, and length).
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Thank you for your comment. May I know the resources used by you to train the best model, and also how long it took you?
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Related Issues (20)
- stage2训练卡0显存泄露,爆显存
- can anyone explain the classifier-free guidance in referencenetattention? HOT 1
- how to realize pose2img ? can i modify pose2vid based on pipeline_pose2img.py???
- Set gradient_accumulate_steps > 1 will occur to accelerate.backward() twice error HOT 1
- additional dataset were added?
- Will you fix face quality later? HOT 2
- quantitative results
- inference for stage1 HOT 1
- Inconsistency of classifier-free guidance between training and testing. HOT 1
- Question about Finetue MotionModel
- how can i return just inference video HOT 2
- Why the height in train stage 1 and train stage 2 are different?
- Question about training memory usage HOT 2
- question about inference parameters
- Is there any difference between diffusers unet_2d_condition and yours unet_2d_condition?
- Misimplementation of Spatial-attention? HOT 2
- Inference Too Buggy
- During both stage 1 and stage 2 training, the training stops unexpectedly for unknown reasons.
- How to reduce the size of the resulting video (while maintaining high quality) HOT 2
- Some top layer parames of reference_unet don't need grad, what is the reason? HOT 1
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