Text-to-Image
Diffusers
Safetensors
image-to-image
quantization
w4a4
svdquant
gptq
nunchaku
8-bit precision
Instructions to use ModelsLab/Qwen-Image-2.1-W4A4-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/Qwen-Image-2.1-W4A4-nvfp4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/Qwen-Image-2.1-W4A4-nvfp4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download samples/flat.png from ModelsLab/Qwen-Image-2.1-W4A4-nvfp4: direct link, hf CLI and curl.
- Browser
- Download file 1.02 MB
-
https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/resolve/main/samples/flat.png
- Command line
-
hf download hf://ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/samples/flat.png
-
curl -L -o flat.png https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/resolve/main/samples/flat.png
1.02 MB

- Xet hash:
- 1b81527a81d1903a4a25b5751864e01dd608a984e08603f6e7d5f1ab867d4f30
- Size of remote file:
- 1.02 MB
- SHA256:
- 334f5509667dc0fbccc41cbb4a9df76ed6eaff842c900222e618fcf9d231ed3d
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