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https://github.com/vladmandic/automatic
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add Nunchaku-Qwen-Image-Lightning
Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
@@ -6,6 +6,9 @@
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- **Chroma** final versions: [Chroma1-HD](https://huggingface.co/lodestones/Chroma1-HD), [Chroma1-Base](https://huggingface.co/lodestones/Chroma1-Base) and [Chroma1-Flash](https://huggingface.co/lodestones/Chroma1-Flash)
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- **Qwen-Image** [InstantX ControlNet Union](https://huggingface.co/InstantX/Qwen-Image-ControlNet-Union) support
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*note* qwen-image is already a very large model and controlnet adds 3.5GB on top of that so quantization and offloading are highly recommended!
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- [Nunchaku-Qwen-Image-Lightning](https://huggingface.co/nunchaku-tech/nunchaku-qwen-image)
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if you have a compatible nVidia GPU, Nunchaku is the fastest quantization engine, currently available for Flux.1, SANA and Qwen-Image models
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*note*: release version of `nunchaku==0.3.2` does NOT include support, so you need to build [nunchaku](https://nunchaku.tech/docs/nunchaku/installation/installation.html) from source
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- updated [SD.Next Model Samples Gallery](https://vladmandic.github.io/sd-samples/compare.html)
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- **Core**
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- enable offload during pre-forward by default
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+1
-1
@@ -196,7 +196,7 @@
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"skip": true,
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"extras": ""
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},
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"Qwen-Lightning": {
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"Qwen-Image-Lightning": {
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"path": "vladmandic/Qwen-Lightning",
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"preview": "Qwen-Lightning.jpg",
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"desc": " Qwen-Lightning is step-distilled from Qwen-Image to allow for generation in 8 steps.",
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@@ -12,7 +12,9 @@ def load_qwen_nunchaku(repo_id):
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shared.log.error(f'Load module: quant=Nunchaku module=transformer repo="{repo_id}" low nunchaku version')
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return None
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if repo_id.lower().endswith('qwen-image'):
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nunchaku_repo = f"nunchaku-tech/nunchaku-qwen-image/svdq-{nunchaku_precision}_r128-qwen-image.safetensors" # r32 vs R128
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nunchaku_repo = f"nunchaku-tech/nunchaku-qwen-image/svdq-{nunchaku_precision}_r128-qwen-image.safetensors" # r32 vs r128
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elif repo_id.lower().endswith('qwen-lightning'):
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nunchaku_repo = f"nunchaku-tech/nunchaku-qwen-image/svdq-{nunchaku_precision}_r128-qwen-image-lightningv1.1-8steps.safetensors" # 8-step variant
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else:
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shared.log.error(f'Load module: quant=Nunchaku module=transformer repo="{repo_id}" unsupported')
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if nunchaku_repo is not None:
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