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/orrery.png from ModelsLab/Qwen-Image-2.1-W4A4-nvfp4: direct link, hf CLI and curl.
- Browser
- Download file 1.68 MB
-
https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/resolve/main/samples/orrery.png
- Command line
-
hf download hf://ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/samples/orrery.png
-
curl -L -o orrery.png https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-nvfp4/resolve/main/samples/orrery.png
1.68 MB

- Xet hash:
- 4ce5f6c9f98bc4cca1a613f06eda07d14863f46fb77624d2ac602d92e3df7686
- Size of remote file:
- 1.68 MB
- SHA256:
- 2cb8e743ced7353f81d425faf8bf14ae492f1a28c12090e21fee96d60e9481ad
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