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--- |
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license: apache-2.0 |
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base_model: |
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- Wan-AI/Wan2.2-TI2V-5B-Diffusers |
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--- |
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# SDXL latent to image |
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It takes the 4ch latent and decodes it with the [WanDecoder3d module](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B-Diffusers/tree/main/vae). |
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After a short warmup phase, the head of the WanDecoder3d became part of the process. |
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During the warmup, the model learned the color space. Later on, the imported/modified head improved the stability of the image. |
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```python |
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if __name__ == '__main__': |
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model = WanXL() |
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vae = AutoencoderKLWan.from_pretrained('Wan-AI/Wan2.2-TI2V-5B-Diffusers', subfolder='vae') |
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z = torch.randn(1, 4, 128, 128) # (B, C, H, W) |
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x = model(z) # (B, C, T, H, W) |
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image = transforms.functional.to_pil_image(model.decode_by(vae, x).squeeze()) |
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``` |
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The SDXL latent was generated by this [model](https://huggingface.co/Laxhar/noobai-XL-Vpred-1.0/tree/main/vae). |
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As shown in the example, the target image size is preferably 1024px due to the lossy compression of the original encoded data. |
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## Datasets |
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- 12TPICS |
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- jlbaker361/flickr_humans |
