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-int4 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-int4 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-int4", 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 NOTICE from ModelsLab/Qwen-Image-2.1-W4A4-int4: direct link, hf CLI and curl.
- Browser
- Download file 148 Bytes
-
https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-int4/resolve/e5a75281f67c3e6c0381c6c1131270b398dcb4f4/NOTICE
- Command line
-
hf download hf://ModelsLab/Qwen-Image-2.1-W4A4-int4@e5a75281f67c3e6c0381c6c1131270b398dcb4f4/NOTICE
-
curl -L -o NOTICE https://huggingface.co/ModelsLab/Qwen-Image-2.1-W4A4-int4/resolve/e5a75281f67c3e6c0381c6c1131270b398dcb4f4/NOTICE
148 Bytes
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