Instructions to use kimi000/Flux1-Dev-4Step-2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kimi000/Flux1-Dev-4Step-2000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kimi000/Flux1-Dev-4Step-2000", 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 example.png from kimi000/Flux1-Dev-4Step-2000: direct link, hf CLI and curl.
- Browser
- Download file 1.4 MB
-
https://huggingface.co/kimi000/Flux1-Dev-4Step-2000/resolve/main/example.png
- Command line
-
hf download hf://kimi000/Flux1-Dev-4Step-2000/example.png
-
curl -L -o example.png https://huggingface.co/kimi000/Flux1-Dev-4Step-2000/resolve/main/example.png
1.4 MB

- Xet hash:
- b52bae6c3395b94b6c551e6ff5c4eca468fcbff9b791a9e1d4ece48549b408a8
- Size of remote file:
- 1.4 MB
- SHA256:
- 11fb9e3e97b58d3255d6e62150d870a21a35cf5ad88f241103195c36b9ded370
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