AIが動く。未来が更新される。flux.1-fill-dev-OneReward
This repo contains the checkpoint from OneReward processed into a single model suitable for ComfyUI use. **OneReward** is a novel RLHF methodology for the visual domain by employing Qwen2.5-VL as a generative reward model to enhance multitask reinforcement learning, significantly improving the policy model’s generation ability across multiple subtask. Building on OneReward, **FLUX.1-Fill-dev-OneReward** - based on FLUX Fill [dev], outperforms closed-source FLUX Fill [Pro] in inpainting and outpainting tasks, serving as a powerful new baseline for future research in unified image editing. The following code snippet illustrates how to use the model with the `diffusers` library. Note that this requires the custom `FluxFillCFGPipeline` defined in the official source code.
翻訳準備中のため原文を表示しています
This repo contains the checkpoint from OneReward processed into a single model suitable for ComfyUI use. **OneReward** is a novel RLHF methodology for the visual domain by employing Qwen2.5-VL as a generative reward model to enhance multitask reinforcement learning, significantly improving the policy model’s generation ability across multiple subtask. Building on OneReward, **FLUX.1-Fill-dev-OneReward** - based on FLUX Fill [dev], outperforms closed-source FLUX Fill [Pro] in inpainting and outpainting tasks, serving as a powerful new baseline for future research in unified image editing. The following code snippet illustrates how to use the model with the `diffusers` library. Note that this requires the custom `FluxFillCFGPipeline` defined in the official source code.