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:
- 56842e4c817c9033023f4d09d6c1bfdf9850f8614feb92eba0f0a122a7be7aab
- Size of remote file:
- 1.89 MB
- SHA256:
- e2a28c6ec21970d5a5dee391d8c17b6f9a24b1125bc50321391fd115961c11c3
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