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
- Draw Things
- DiffusionBee

- Xet hash:
- 3b7a02e6d0d226b956fd59ffb90f853b501a86dcfdc4363093c8e5ac02f92aa3
- Size of remote file:
- 1.62 MB
- SHA256:
- 93b4408ac9df327b968d96accad61702ef83f78021f2b94c227a8d823408b532
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