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path: root/candle-transformers/src/models/wuerstchen
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* Module Docs (#2624)zachcp2024-11-181-3/+10
* Documentation Pass for Models (#2617)zachcp2024-11-151-0/+9
* Do not implement Module for BatchNorm. (#1513)Laurent Mazare2024-01-011-1/+1
* Add flash-attn support. (#912)Laurent Mazare2023-09-204-8/+70
* Add some missing biases. (#908)Laurent Mazare2023-09-201-4/+3
* Line-up the wuerstchen model with the python implementation. (#901)Laurent Mazare2023-09-192-4/+6
* Improve the error message on shape mismatch for cat. (#897)Laurent Mazare2023-09-192-1/+3
* Only use classifier free guidance for the prior. (#896)Laurent Mazare2023-09-193-8/+37
* Specialized attention module for Wuerstchen. (#890)Laurent Mazare2023-09-184-5/+80
* Prior denoising. (#889)Laurent Mazare2023-09-181-0/+4
* Fix the W clip embeddings. (#887)Laurent Mazare2023-09-182-0/+98
* More Wuerstchen fixes. (#882)Laurent Mazare2023-09-172-13/+18
* Remove the parameters for the Wuerstchen layer-norm. (#879)Laurent Mazare2023-09-174-44/+44
* Wuerstchen main (#876)Laurent Mazare2023-09-171-3/+109
* W fixes. (#862)Laurent Mazare2023-09-153-14/+14
* Replication pad (#861)Laurent Mazare2023-09-151-2/+2
* Add the embed mapper convolutions. (#860)Laurent Mazare2023-09-151-2/+31
* DiffNeXt/unet (#859)Laurent Mazare2023-09-153-9/+180
* Add the upblocks. (#853)Laurent Mazare2023-09-142-4/+52
* More DiffNeXt. (#847)Laurent Mazare2023-09-141-2/+144
* Add the attention block. (#846)Laurent Mazare2023-09-143-5/+95
* Start adding the Wuerstchen diffusion pipeline (#843)Laurent Mazare2023-09-144-0/+278
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