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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Efradeca/lightloom-style-lora") prompt = "lghtlm style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 11aebeaeacb932c548fed75be0274ae2a5675ead1781905674388ed9da0ae7aa
- Size of remote file:
- 66.9 MB
- SHA256:
- b1db1e85eb4648f503eeba7d61870ec71f6d606d3383cd86d551bfd3329f4564
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