Instructions to use Efradeca/lightloom-style-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Efradeca/lightloom-style-lora 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.2-klein-base-4B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Efradeca/lightloom-style-lora") prompt = "lghtlm style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d79cfe71c4a242a37094fa8db10057c0301f0e45f11967d2451bd27a4edca69d
- Size of remote file:
- 66.9 MB
- SHA256:
- 57a3c093ecc8770aef3e97b5126c0a8e11a7b43b3dfa54471c6407de5b5bbf48
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