metadata
base_model:
- wikeeyang/SRPO-Refine-Quantized-v1.0
- rockerBOO/flux.1-dev-SRPO
- tencent/SRPO
tags:
- srpo
- flux-dev
- flux
pipeline_tag: text-to-image
library_name: diffusers
Flux.1-Dev SRPO LoRAs
These LoRAs were extracted from three sources:
- the original SRPO (Flux.1-Dev): tencent/SRPO
- community checkpoint: rockerBOO/flux.1-dev-SRPO
- community checkpoint (quantized/refined): wikeeyang/SRPO-Refine-Quantized-v1.0
They are designed to provide modular, lightweight adaptations you can mix with other LoRAs, reducing storage and enabling fast experimentation across ranks (8, 16, 32, 64, 128).
Example comparison between Flux1-Dev baseline and LoRA extractions
use with 🧨diffusers:
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights('Alissonerdx/flux.1-dev-SRPO-LoRas', weight_name='srpo_128_base_R%26Q_model_fp16.safetensors')
pipe.to("cuda")
prompt = "aiyouxiketang, a man in armor with a beard and a beard"
image = pipe(
prompt,
num_inference_steps=28,
guidance_scale=5.0,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]