Instructions to use Runware/BFL-FLUX.2-klein-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/BFL-FLUX.2-klein-9B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/BFL-FLUX.2-klein-9B", 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
- Xet hash:
- a28cdbb02c6ff7e24a73270f37f45ca8ed92bdc71496a0c2b21170e317f29f39
- Size of remote file:
- 4.98 GB
- SHA256:
- 74927fec432e050365bf757bb30348f560a44394efac89f492680b7c910b64fd
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