Instructions to use AlexanderLab/OSKLSHB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlexanderLab/OSKLSHB 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/OSKLSHB") prompt = "OSKLSHB" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 39d7b37bfba054083db50fa2db00d1ba817c700cca9da9b166fb60d1237f5089
- Size of remote file:
- 344 MB
- SHA256:
- 5d02dfbb8eab7265f9d69a9851f05f20df9f34a0aa166162bc2998e23837c169
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.