Instructions to use VHKE/sprbtc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/sprbtc 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("VHKE/sprbtc") prompt = "SPRBTC mega sport biotic bottle on a night stand --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f4d941dd997be955caaedd13d3a462ef8979f9a0e0012ac29cd342422c5e5975
- Size of remote file:
- 3.14 MB
- SHA256:
- bb6f20fd735b678e9a8c72ff3a1523576c317523305c047b2b8abf4c31f98e87
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