Overview

Wan2.2 Fun Reward LoRAs are specialized low-rank adaptation modules designed to enhance the aesthetic and motion quality of Alibaba's Wan2.2 text-to-video framework. Rather than retraining the base model, these LoRAs leverage reward-model feedback to steer video generation toward higher visual fidelity and more natural movement. For developers, this means a lightweight way to fine-tune output style and consistency without the computational overhead of full parameter updates. They are particularly useful for creative pipelines where specific cinematic quality or motion dynamics are required. Integration is straightforward via standard LoRA loading mechanisms, making them compatible with existing Diffusers-based workflows and enabling rapid iteration across different visual styles.

Highlights

Lightweight adapters for enhanced video aesthetic and motion
Reduces computational cost compared to full model fine-tuning
Compatible with standard Diffusers and LoRA integration pipelines
Optimized via reward-model feedback for higher visual fidelity
Apache-2.0 licensed for flexible commercial and open-source use

Usage

Install

# Install Hugging Face transformers
pip install transformers torch

SDK Usage

# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("alibaba-pai/Wan2.2-Fun-Reward-LoRAs")
tokenizer = AutoTokenizer.from_pretrained("alibaba-pai/Wan2.2-Fun-Reward-LoRAs")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance

pip install -U huggingface_hub

CLI Download

Download the full repository

huggingface-cli download alibaba-pai/Wan2.2-Fun-Reward-LoRAs

Download a single file to a local folder (e.g. config.json into ./dir)

huggingface-cli download alibaba-pai/Wan2.2-Fun-Reward-LoRAs config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('alibaba-pai/Wan2.2-Fun-Reward-LoRAs')

Git Download

Make sure git-lfs is installed first

Git Download

git lfs install
git clone https://huggingface.co/alibaba-pai/Wan2.2-Fun-Reward-LoRAs

To skip LFS large-file downloads, use:

Skip LFS

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/alibaba-pai/Wan2.2-Fun-Reward-LoRAs

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

pip install -U transformers torch

Load the model and run inference

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('alibaba-pai/Wan2.2-Fun-Reward-LoRAs')
tokenizer = AutoTokenizer.from_pretrained('alibaba-pai/Wan2.2-Fun-Reward-LoRAs')

Full Documentation

来源: HuggingFace

---
license: apache-2.0
base_model:

alibaba-pai/Wan2.2-Fun-A14B-InP

Wan-AI/Wan2.2-T2V-A14B

library_name: videox_fun
pipeline_tag: text-to-video
---

Wan2.2-Fun-Reward-LoRAs

Introduction

We explore the Reward Backpropagation technique <sup>1 2</sup> to optimized the generated videos by Wan2.2-Fun for better alignment with human preferences.
We provide the following pre-trained models (i.e. LoRAs) along with the training script. You can use these LoRAs to enhance the corresponding base model as a plug-in or train your own reward LoRA.

For more details, please refer to our GitHub repo.

> [!NOTE]
> We found that, MPS reward LoRA for the low-noise model converges significantly more slowly than on the other models, and may not deliver satisfactory results. Therefore, for the low-noise model, we recommend using HPSv2.1 reward LoRA.

Demo

Wan2.2-Fun-A14B-InP

<table border="0" style="width: 100%; text-align: center; margin-top: 20px;">
<thead>
<tr>
<th style="text-align: center;" width="10%">Prompt</sup></th>
<th style="text-align: center;" width="30%">Wan2.2-Fun-A14B-InP</th>
<th style="text-align: center;" width="30%">Wan2.2-Fun-A14B-InP <br> high + low HPSv2.1 Reward LoRA</th>
<th style="text-align: center;" width="30%">Wan2.2-Fun-A14B-InP <br> high MPS + low HPSv2.1 Reward LoRA</th>
</tr>
</thead>
<tr>
<td>
A panda eats bamboo while a monkey swings from branch to branch
<details>
<summary>Expanded</summary>
<p>In a lush green forest, a panda sits comfortably against a tree, leisurely munching on bamboo stalks. Nearby, a lively monkey swings energetically from branch to branch, its tail curling around the limbs. Sunlight filters through the canopy, casting dappled shadows on the forest floor.</p>
</details>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_baseline_00000001.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_hpsv2.1%2Blow_hps2.1_00000001.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_mps%2Blow_hpsv2.1_00000001.mp4" width="100%" controls autoplay loop></video>
</td>
</tr>
<tr>
<td>
A dog runs through a field while a cat climbs a tree
<details>
<summary>Expanded</summary>
<p>In a sunlit, expansive green field surrounded by tall trees, a playful golden retriever sprints energetically across the grass, its fur gleaming in the afternoon sun. Nearby, a nimble tabby cat gracefully climbs a sturdy tree, its claws gripping the bark effortlessly. The sky is clear blue with occasional birds flying.</p>
</details>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_baseline_00000002.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_hpsv2.1%2Blow_hps2.1_00000002.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_mps%2Blow_hpsv2.1_00000002.mp4" width="100%" controls autoplay loop></video>
</td>
</tr>
<tr>
<td>
A penguin waddles on the ice, a camel treks by
<details>
<summary>Expanded</summary>
<p>A small penguin waddles slowly across a vast, icy surface under a clear blue sky. The penguin's short, flipper-like wings sway at its sides as it moves. Nearby, a camel treks steadily, its long legs navigating the snowy terrain with ease. The camel's fur is thick, providing warmth in the cold environment.</p>
</details>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_baseline_00000004.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_hpsv2.1%2Blow_hps2.1_00000004.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_high_mps%2Blow_hpsv2.1_00000004.mp4" width="100%" controls autoplay loop></video>
</td>
</tr>
<tr>
<td>
Pig with wings flying above a diamond mountain
<details>
<summary>Expanded</summary>
<p>A whimsical pig, complete with delicate feathered wings, soars gracefully above a shimmering diamond mountain. The pig's pink skin glistens in the sunlight as it flaps its wings. The mountain below sparkles with countless facets, reflecting brilliant rays of light into the clear blue sky.</p>
</details>
</td>
<td>
<video src="https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/reward_lora/14B_baseline_00000008.mp4" width="100%" controls autoplay loop></video>
</td>
<td>
<v