Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved.

Built with Qwen.

This repository redistributes, for non-commercial research and evaluation use only, files derived from
Qwen/Qwen-Image-2.1 (revision 790c92633540aa0cb11d9abf19eb46d861714758).

Unmodified files: LICENSE, processor/, scheduler/, text_encoder/generation_config.json.

MODIFIED FILES (changed by joseplcam):

- transformer/diffusion_pytorch_model.safetensors, transformer/config.json
  Quantized from the official BF16 transformer with SVDQuant + GPTQ (NVFP4 weights and activations,
  rank-32 BF16 low-rank branch) using diffuse-compressor. Blocks 0, 1, 30, 31 and the global
  modulation are the official BF16 tensors. config.json gained a `quantization_config` entry.
  sha256 0304fc3e84b13663b439601380066754ef9b92025e159275abe163bc5f1ceeb4

- text_encoder/model.safetensors, text_encoder/config.json
  Quantized from the official BF16 Qwen3-VL text encoder with the same method: the MLP projections
  (gate/up/down) of decoder layers 4-31, rank-128 low-rank branch. All attention projections, decoder
  layers 0-3 and 32-35, the vision tower, embeddings and lm_head are the official BF16 tensors.
  config.json gained a `nunchaku_lite` entry.
  sha256 83c4462b5ce6b98e2708ca53031e2f9a60a8e402c4c4a0ccd19cb2df8e817ae2

- vae/diffusion_pytorch_model.safetensors, vae/config.json
  The official VAE weights cast from FP32 to BF16.
  sha256 71879ffd5321e6d10c3c87513e2b474b1252efa7f3dec2969214a9bf06a6dd5c

- model_index.json
  The `text_encoder` and `transformer` entries point to the custom classes below.

NEW FILES: text_encoder/modeling_nunchaku_qwen3vl.py, transformer/modeling_nunchaku_qwenimage21.py,
tools/ (the scripts that produced this repository).