README.md

---
license: other
license_name: nvidia-license
license_link: LICENSE
tags:
  - pixel-diffusion
  - decoder
  - super-resolution
  - non-commercial
  - sceneworks
extra_gated_prompt: >-
  This model is licensed under the NVIDIA License (NSCLv1). It and any
  derivative works may be used for NON-COMMERCIAL (research or evaluation)
  purposes only. The non-commercial restriction flows to decoded output.
---

# PiD — sdxl 2kto4k decoder (SceneWorks redistribution)

A format-converted redistribution of NVIDIA's **PiD** (Pixel Diffusion) `sdxl`
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).

PiD is an **optional, per-generation replacement for the VAE decoder**: it denoises
directly in pixel space and **decodes + 4× super-resolves in one 4-step pass**. This
`sdxl` student serves the **SDXL VAE latent space** (4-channel, the largest
latent→pixel ratio) — SDXL base, RealVisXL (incl. RealVisXL Lightning), and Kolors,
which share the SDXL VAE.

## ⚠️ License — non-commercial (research/evaluation) only

This checkpoint is under the **NVIDIA License** (HuggingFace tag `NSCLv1`); see
[`LICENSE`](LICENSE) and [`NOTICE`](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).

**This restriction flows to the output.** Images decoded with PiD are for
research/evaluation use only, distinct from the rest of the SceneWorks pipeline.

## Contents

| File | Description |
|------|-------------|
| `pid_sdxl_2kto4k.safetensors` | sdxl `2kto4k` 4-step student backbone + sigma-aware LQ adapter (456 tensors, bf16, ~2.7 GB). |
| `LICENSE` | Full NVIDIA License text (verbatim from the original release). |
| `NOTICE` | NVIDIA attribution, provenance, and the exact conversion performed. |

The PiD caption encoder (`gemma-2-2b-it`) and the SDXL VAE are provisioned
separately by SceneWorks; this repo holds only the PiD student weights.

## Provenance / conversion

Converted from NVIDIA's original
`checkpoints/PiD_res2kto4k_sr4x_official_sdxl_distill_4step/model_ema_bf16.pth`
(from [`nvidia/PiD`](https://huggingface.co/nvidia/PiD)) via a lossless
key/format transform (`net.`-prefix strip + drop training-only
`net_ema.*`/`fake_score.*`/`discriminator.*`; dtype preserved). No re-training.

- Project: https://research.nvidia.com/labs/sil/projects/pid/
- Code: https://github.com/nv-tlabs/pid
- Paper: arXiv:2605.23902