Instructions to use fal/FLUX.2-dev-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/FLUX.2-dev-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fal/FLUX.2-dev-Turbo") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 04984708652d0519eda0a6ba332363fc131d963cdaf91b58b4c7e73f7f446a6c
- Size of remote file:
- 5.01 MB
- SHA256:
- 0372a83c07acc7bba7e7d92d08b5e6a8d96771e46962d59f99f107a62498c0f1
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