Instructions to use AlexanderLab/OSKLBROWNLFR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlexanderLab/OSKLBROWNLFR 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.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AlexanderLab/OSKLBROWNLFR") prompt = "OSKLBROWNLFR" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 554a8f40606620f7d505c88d6e87ae478ff264ba4a9154721bc58ff78720340b
- Size of remote file:
- 344 MB
- SHA256:
- c0f912920f6292719a5c0c233ed358f78cb89a461a54cf42ebb6bdded0bb87c6
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