Text-to-Image
Diffusers
Safetensors
QwenImagePipeline
nvidia
ModelOpt
Qwen-Image
quantized
FP4
fp4
8-bit precision
Instructions to use nvidia/Qwen-Image-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/Qwen-Image-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("nvidia/Qwen-Image-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
File size: 199 Bytes
06b4b72 | 1 2 3 4 5 6 7 8 9 10 11 12 | attention_config:
backend: VANILLA
parallel_config:
cfg_size: 1
ulysses_size: 1
torch_compile_config:
enable: false
cuda_graph_config:
enable: false
compilation_config:
skip_warmup: true
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