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2d8a41cae8
* Add wanx pipeline, model and example * wanx_merged_v1 * change WanX into Wan * fix i2v fp32 oom error Link: https://code.alibaba-inc.com/open_wanx2/diffusers/codereview/20607813 * support t2v load fp32 ckpt * add example * final merge v1 * Update autoencoder_kl_wan.py * up * update middle, test up_block * up up * one less nn.sequential * up more * up * more * [refactor] [wip] Wan transformer/pipeline (#10926) * update * update * refactor rope * refactor pipeline * make fix-copies * add transformer test * update * update * make style * update tests * tests * conversion script * conversion script * update * docs * remove unused code * fix _toctree.yml * update dtype * fix test * fix tests: scale * up * more * Apply suggestions from code review * Apply suggestions from code review * style * Update scripts/convert_wan_to_diffusers.py * update docs * fix --------- Co-authored-by: Yitong Huang <huangyitong.hyt@alibaba-inc.com> Co-authored-by: 亚森 <wangjiayu.wjy@alibaba-inc.com> Co-authored-by: Aryan <aryan@huggingface.co>
1.1 KiB
1.1 KiB
AutoencoderKLWan
The 3D variational autoencoder (VAE) model with KL loss used in Wan 2.1 by the Alibaba Wan Team.
The model can be loaded with the following code snippet.
from diffusers import AutoencoderKLWan
vae = AutoencoderKLWan.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers", subfolder="vae", torch_dtype=torch.float32)
AutoencoderKLWan
autodoc AutoencoderKLWan
- decode
- all
DecoderOutput
autodoc models.autoencoders.vae.DecoderOutput