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qwenimage
4-step distillation decoder, packaged for SceneWorks' native (no-PyTorch) PiD
decoder (mlx-gen-pid on macOS/MLX, candle-gen-pid on Windows·Linux/CUDA).qwenimage student serves the Qwen-Image VAE latent space — Qwen-Image, the
Qwen-Image-Edit variants, and Krea 2.NSCLv1); see
LICENSE and NOTICE. Per §3.3, the Work and any
derivative works may be used non-commercially — for research or evaluation
purposes only (NVIDIA and its affiliates excepted).| File | Description |
|---|---|
pid_qwenimage_2kto4k_v1pt5.safetensors | PiD v1.5 qwenimage 2kto4k 4-step student (461 tensors, bf16, ~2.8 GB). Improved color fidelity, no grid-corner artifacts, better anime/face detail. The default for the 2kto4k (up-to-4K) output tier. |
pid_qwenimage_2kto4k.safetensors | qwenimage v1.0 2kto4k 4-step student (456 tensors, bf16, ~2.7 GB). Retained as the fallback for installs that predate v1.5. |
LICENSE | Full NVIDIA License text (verbatim from the original release). |
NOTICE | NVIDIA attribution, provenance, and the exact conversion performed. |
res2k student (v1.0 or v1.5), so the 2K and up-to-4K tiers
both use a 2kto4k file. The engine picks v1.0 vs v1.5 by sniffing the weights
(not the filename), so either loads correctly and a pre-v1.5 install keeps working.nvidia/PiD)
via a lossless key/format transform (net.-prefix strip + drop training-only
net_ema.*/fake_score.*/discriminator.*; dtype preserved). No re-training.2kto4k: checkpoints/PiD_v1pt5_res2kto4k_sr4x_official_qwenimage_distill_4step/model_ema_bf16.pth2kto4k: checkpoints/PiD_res2kto4k_sr4x_official_qwenimage_distill_4step/model_ema_bf16.pth