---
library_name: diffusers
license: mit
base_model:
- black-forest-labs/FLUX.1-dev
---




## FLUX.1-dev-PrefGRPO

This model is trained using [Pref-GRPO](https://codegoat24.github.io/UnifiedReward/Pref-GRPO) on the training dataset of [UniGenBench](https://github.com/CodeGoat24/UniGenBench).


For further details, please refer to the following resources:
- 📰 Paper: 
- 🪐 Project Page: https://codegoat24.github.io/UnifiedReward/Pref-GRPO
- 🤗 UniGenBench: https://github.com/CodeGoat24/UniGenBench
- 🤗 Leaderboard: https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard
- 👋 Point of Contact: [Yibin Wang](https://codegoat24.github.io)


### Quick Start
~~~python
pip install -U diffusers
~~~

~~~python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("CodeGoat24/FLUX.1-dev-PrefGRPO", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power

prompt = "A cat holding a sign that says hello world"
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=3.5,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev.png")

~~~


## Citation

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