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:
- 9671026897969c45670ca04e61cb1424cefb3c51639e1b8e30d67ca3f1eeb186
- Size of remote file:
- 1.75 MB
- SHA256:
- 243484450715c24c0b1079770296083bf777c7aed3d5e8bf473f80a7b005d91f
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