Model overview
We explore the Reward Backpropagation technique 1 2 to optimized the generated videos by Wan2.1-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. Prompt Wan2.1-Fun-1.3B-InP Wan2.1-Fun-1.3B-InP HPSv2.1 Reward LoRA Wan2.1-Fun-1.3B-InP MPS Reward LoRA Expanded In a vast, sun-drenched Australian plain, a lively kangaroo bounds with powerful leaps across the dry grass, its shadow following closely. Nearby, a serene brown and white cow grazes leisurely, its tail swishing gently in the warm breeze. The sky is a vibrant blue, dotted with fluffy clouds.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。