Generative Modeling via Drifting: Pretrained Weights

JAX weights for the ImageNet 256x256 models of Generative Modeling via Drifting (NeurIPS 2026, oral). Code, usage, and evaluation instructions: lambertae/drifting. Project page: lambertae.github.io/projects/drifting.

Files

Path	Description
models/gen/jax/latent_L_sota	Latent-space generator, L/2 (FID 1.54, 1-NFE)
models/gen/jax/latent_B_sota	Latent-space generator, B/2 (FID 1.75, 1-NFE)
models/gen/jax/pixel_L_sota	Pixel-space generator, L/16 (FID 1.61, 1-NFE)
models/gen/jax/pixel_B_sota	Pixel-space generator, B/16 (FID 1.76, 1-NFE)
models/gen/jax/ablation	Ablation-setting generator, B/2
models/mae/jax/mae_latent_640	Latent-space MAE-640 feature encoder
models/mae/jax/mae_pixel_640	Pixel-space MAE-640 feature encoder
models/mae/jax/mae_latent_256	Latent-space MAE-256 feature encoder (ablations)

The code downloads these weights automatically.

MIT, same as the code repository.

Please cite the paper; the BibTeX entry is in the code repository.

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