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:
- 877452b0fd78026d1f3de6bfa4ee17dc257c38c24b4fb51d3c30a81e9d9a5b79
- Size of remote file:
- 1.58 GB
- SHA256:
- cb73f466fade5716702bda38d4e3b321c9358c39889e46fb9d613fb038bfcb2f
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