Instructions to use VHKE/slpsps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/slpsps 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/slpsps") prompt = "SLPSPS" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 97a9017398c8ca58b5400b60f723e11036c8accd8debf41ca45372d2e3aed123
- Size of remote file:
- 1.97 MB
- SHA256:
- b1e8c68934148f91b75f8ef65b801efed727aca63e3adf5e65d3ee62cc1bfb7a
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