Text-to-Image
Diffusers
Safetensors
English
Chinese
Russian
QwenImage21Pipeline
image-editing
qwen-image
turbo
few-step
distillation
Instructions to use WaveCut/Turbo-Image-2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Turbo-Image-2.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Turbo-Image-2.1", 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 media/examples.jpg from WaveCut/Turbo-Image-2.1: direct link, hf CLI and curl.
- Browser
- Download file 574 kB
-
https://huggingface.co/WaveCut/Turbo-Image-2.1/resolve/main/media/examples.jpg
- Command line
-
hf download hf://WaveCut/Turbo-Image-2.1/media/examples.jpg
-
curl -L -o examples.jpg https://huggingface.co/WaveCut/Turbo-Image-2.1/resolve/main/media/examples.jpg
574 kB

- Xet hash:
- 864404b10c4b129be9a4a229b265eb102db6ca9f853ba11c842c1e4ddf5d070f
- Size of remote file:
- 574 kB
- SHA256:
- 8e6aa7fadc8c64021c237c92cf80d846c33945f611c4c35abb223fa5997edbf7
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