Comments (2)
ckkelvinchan
commented on August 12, 2024
Do you mean training or inference? For training, you may want to reduce the patch size and the sequence length to reduce memory consumption. For inference, you can try to separate the sequences into shorter segments. Using max_seq_len may help.
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hello-eternity
commented on August 12, 2024
Thanks a lot, your answer helps me, I mean inference
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Related Issues (20)
- about training problem HOT 1
- output image have some bad color area
- 模型太大了，没法落地，V100都得跑60多毫秒，端测没法用哦 HOT 1
- Always get error in the huggingface space demo
- Welcome update to OpenMMLab 2.0
- Visualizing the generated LQ video in training process
- about VideoLQ dataset HOT 1
- How to train x2 model?
- about x2 effect
- FileNotFoundError HOT 1
- Does the pretrained model support x2 super-resolution?
- Does it support raising to a specific resolution? For example, from 1280*720P to 1920*1080P HOT 1
- What is GT when training RealBasicVSR HOT 1
- Can I put a separate copy of the code in git?
- GPU num for training
- Inference with a low quality low resolution video, got a bad quality output.
- contrast RealBasicVSR and BasicVSR_PlusPlus
- upscaler a video, but the result is bad HOT 2
- 背景会闪烁
- May we use the VideoLQ dataset for a demonstration at a trade fair?
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