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:
- 5772df481f9dd9db93083065de412d94697b37434dd2e30c40d7bd6b484965ef
- Size of remote file:
- 2.42 MB
- SHA256:
- a3c095c368f99f98fcd19127af96ad2c5c95c4e42728a2ac61cd89f585d06016
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