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Transformer_Autoregressive_Flow

Unconditional Image Generation
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@@ -39,6 +39,10 @@ We trained five models:
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  - ImageNet (64x64) conditioanl: imagenet_model_4_1024_8_8_0.05.pth
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  [1] Zhai S, Zhang R, Nakkiran P, et al. Normalizing flows are capable generative models[J]. arXiv preprint arXiv:2412.06329, 2024.
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  []
 
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  - ImageNet (64x64) conditioanl: imagenet_model_4_1024_8_8_0.05.pth
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+ The sampling traces maybe look like this:
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/682459b20ee49a8c3822a525/bx0U7vnZSu9SFoV2gtERI.png)
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+ From top to bottom: Img128cond, Img64cond (patch4), Img64uncond, AFHQ. From left to right: noise, Block 7-0, denoised image.
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  [1] Zhai S, Zhang R, Nakkiran P, et al. Normalizing flows are capable generative models[J]. arXiv preprint arXiv:2412.06329, 2024.
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  []