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
Commit History
26 days ago
-
Add the 8-seed text sweep these numbers came from
Verified signature8d7b6a0 -
Record the reference-free text-accuracy sweep
Verified signatureecdcedf -
W4A4 nvfp4 checkpoint, SVDQuant + GPTQ, LPIPS 0.1425
Verified signature84b13fa -
initial commit
Verified signature440c00c