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.
License
MIT, same as the code repository.
Citation
Please cite the paper; the BibTeX entry is in the code repository.