---
title: flux.1-dev-SRPO-LoRas
canonical_url: "https://www.modelscope.cn/models/Alissonerdx/flux.1-dev-SRPO-LoRas"
md_url: "https://www.modelscope.cn/models/Alissonerdx/flux.1-dev-SRPO-LoRas.md"
repository: Alissonerdx/flux.1-dev-SRPO-LoRas
last_updated: 2025-09-29
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - wikeeyang/SRPO-Refine-Quantized-v1.0
  - rockerBOO/flux.1-dev-SRPO
  - tencent/SRPO
base_model_relation: finetune
parameters: 7.9B
tensor_type:
  - F16
  - BF16
library_name:
  - pytorch
  - safetensors
frameworks:
  - pytorch
downloads: 2247
stars: 4
tags:
  - srpo
  - flux-dev
  - flux
---

# flux.1-dev-SRPO-LoRas

> flux.1-dev-SRPO-LoRas - Alissonerdx 在 ModelScope 开源的模型。Flux.1-Dev SRPO LoRAs

Alissonerdx/flux.1-dev-SRPO-LoRas 是 ModelScope 魔搭社区上的 7.9B 参数text-to-image-synthesis模型，基于 wikeeyang/SRPO-Refine-Quantized-v1.0、rockerBOO/flux.1-dev-SRPO、tencent/SRPO 构建。

- **Repository**: Alissonerdx/flux.1-dev-SRPO-LoRas
- **Tasks**: text-to-image-synthesis
- **Parameters**: 7.9B
- **Base model**: wikeeyang/SRPO-Refine-Quantized-v1.0, rockerBOO/flux.1-dev-SRPO, tencent/SRPO
- **Tags**: srpo, flux-dev, flux
- **Downloads**: 2247
- **Stars**: 4
- **Last updated**: 2025-09-29

Source: https://www.modelscope.cn/models/Alissonerdx/flux.1-dev-SRPO-LoRas

---

### 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).

Notes: 
- The Loras version for Nunchaku was converted using the official Nunchaku conversion tool but it is something experimental I still need to test and analyze the results, I do not recommend using it for now it is only for testing.
- These loras allow you to use the quality of SRPO using the official flux dev as a base, without the need to use the base flux SRPO, that is, in my opinion, it is not very advantageous to use any of these loras + flux SRPO as a base, unless you want to apply the quality of, for example, SRPO RockerBOO in the base flux SRPO model. 
- The version I recommend is RockerBOO but I advise you to test the others, because the original version will give you different results than the other versions.
- According to some reports it seems to work well with Flux Krea, the report was with rank 256, I haven't tested it yet to confirm.

![Comparison](images/compare_oficial_lora_prompt_1.png)
![Comparison](images/compare_oficial_lora_prompt_2.png)
![Comparison](images/compare_oficial_lora_prompt_3.png)
![Comparison](images/compare_oficial_lora_prompt_4.png)
![Comparison](images/compare_oficial_lora_prompt_5.png)
![Comparison](images/compare_oficial_lora_prompt_6.png)
![Comparison](images/compare_oficial_lora_prompt_7.png)
![Comparison](images/compare_oficial_lora_prompt_8.png)
![Comparison](images/compare_oficial_lora_prompt_9.png)
![Comparison](images/compare_oficial_lora_prompt_10.png)
![Comparison](images/compare_oficial_lora_prompt_11.png)
![Comparison](images/compare_oficial_lora_prompt_12.png)
![Comparison](images/compare_oficial_lora_prompt_13.png)

*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]

```