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
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
library_name: diffusers
license: other
license_name: tencent-hunyuan-community
license_link: https://github.com/Tencent-Hunyuan/SRPO/blob/main/LICENSE.txt
pipeline_tag: text-to-image
base_model: black-forest-labs/FLUX.1-dev
SRPO R16 LoRA
Extraction of SRPO from Flux.1 SRPO