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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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base_model:
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- vladmandic/Qwen-Lightning
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library_name: diffusers
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tags:
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- sdnq
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- qwen_image
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---
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4 bit (UINT4 with SVD rank 32) quantization of [vladmandic/Qwen-Lightning](https://huggingface.co/vladmandic/Qwen-Lightning) using [SDNQ](https://github.com/vladmandic/sdnext/wiki/SDNQ-Quantization).
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Usage:
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```
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pip install git+https://github.com/Disty0/sdnq
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```
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```py
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import torch
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import diffusers
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from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers
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pipe = diffusers.QwenImagePipeline.from_pretrained("Disty0/Qwen-Image-Lightning-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
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pipe.enable_model_cpu_offload()
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prompt = "a tiny astronaut hatching from an egg on the moon, Ultra HD, 4K, cinematic composition."
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negative_prompt = " "
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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width=1024,
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height=1024,
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num_inference_steps=8,
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true_cfg_scale=1.0,
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generator=torch.manual_seed(0),
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).images[0]
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image.save("qwen-image-lightning-sdnq-uint4-svd-r32.png")
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```
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Original BF16 vs SDNQ quantization comparison:
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| Quantization | Model Size | Visualization |
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| --- | --- | --- |
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| Original BF16 | 40.9 GB |  |
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| SDNQ UINT4 | 11.6 GB |  |
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