Instructions to use CodeGoat24/FLUX.1-dev-UnifiedReward-Flex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CodeGoat24/FLUX.1-dev-UnifiedReward-Flex with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CodeGoat24/FLUX.1-dev-UnifiedReward-Flex", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| library_name: diffusers | |
| license: mit | |
| pipeline_tag: text-to-image | |
| base_model: | |
| - black-forest-labs/FLUX.1-dev | |
| # Model Summary | |
| This model is GRPO trained using [UnifiedReward-Flex](https://huggingface.co/collections/CodeGoat24/unifiedreward-flex) as reward on the training dataset of [UniGenBench](https://github.com/CodeGoat24/UniGenBench). | |
| π The inference code is available at [Github](https://github.com/CodeGoat24/Pref-GRPO/blob/main/inference/flux_dist_infer.sh). | |
| For further details, please refer to the following resources: | |
| - π° Paper: https://arxiv.org/abs/2602.02380 | |
| - πͺ Project Page: https://codegoat24.github.io/UnifiedReward/flex | |
| - π€ Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-flex | |
| - π€ Dataset: https://huggingface.co/datasets/CodeGoat24/UnifiedReward-Flex-SFT-90K | |
| - π Point of Contact: [Yibin Wang](https://codegoat24.github.io) | |
| # Qualitative Results | |
|  | |
|  | |
| # Quantitative Results | |
|  | |
| ## Citation | |
| ```bibtex | |
| @article{unifiedreward-flex, | |
| title={Unified Personalized Reward Model for Vision Generation}, | |
| author={Wang, Yibin and Zang, Yuhang and Han, Feng and Bu, Jiazi and Zhou, Yujie and Jin, Cheng and Wang, Jiaqi}, | |
| journal={arXiv preprint arXiv:2602.02380}, | |
| year={2026} | |
| } | |
| ``` |