Instructions to use rockerBOO/flux.1-dev-SRPO-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rockerBOO/flux.1-dev-SRPO-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.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rockerBOO/flux.1-dev-SRPO-LoRA") prompt = "She is in modern street wear in a city along a bridge at sunset." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- a4da29d03ad59cba0690ec306a973ff40e01704f7b74fc1cc61b0cd17ea1cf3d
- Size of remote file:
- 1.18 MB
- SHA256:
- db0b4fd990f8a6b1b3c5f3faeb7c58ed38b2055b661b7fbc272f14275c6a7d13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.