Comments (2)
Hi Zhuowei,
Thanks for double-checking! Yes, changing this value to 1000 will recover the setting described here. I have updated this value to 850 since I find it helps produce better results, and I will update the arxiv version to reflect this change soon. Sorry about the confusion!
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Thx for your reply. :)
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Related Issues (20)
- Unpaired image-to-image translation HOT 2
- Question about LDM support HOT 4
- several researchers and practitioners have found that when trained with the same “random seed” leads to similar images (Nichol et al., 2022) HOT 3
- Please tell train the image to image translation with custom dataset HOT 1
- Which part of algorithm 1 stands for cycle, why do you call it cyclediffusion? HOT 7
- code example for plug-and-play guidance for diffusion models HOT 2
- Custom dataset load Issue HOT 1
- Can I use the unpaired images of different sizes for image to image translate HOT 12
- Is there any training in Cycle Diffusion HOT 5
- Encoding two images to obtain third image HOT 4
- About outputs issue HOT 1
- No outputs: Unpaired image-to-image translation with diffusion models trained on two domains HOT 4
- ldm_models.zip Corrupt files,损坏的文件 HOT 6
- what version of Pytorch to use,询问作者使用的pytroch版本。 HOT 4
- Questions with Plug-and-play Guidance HOT 2
- TypeError: cannot unpack non-iterable NoneType object HOT 5
- torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 613558) of binary: HOT 4
- Does the unpaired image-to-image translation works with Hugging Face Stable Diffusion checkpoints? HOT 6
- install envionment issue HOT 1
- How to write config.yaml for custom datasets HOT 1
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