Skywork-Reward-V2-Llama-3.1-8B

Model overview

**Skywork-Reward-V2** is a series of eight reward models designed for versatility across a wide range of tasks, trained on a mixture of 26 million carefully curated preference pairs. While the Skywork-Reward-V2 series remains based on the Bradley-Terry model, we push the boundaries of training data scale and quality to achieve superior performance. Compared with the first generation of Skywork-Reward, the Skywork-Reward-V2 series offers the following major improvements: In the following table, we categorize the models into two types: Bradley-Terry (BT) reward models and Generative reward models. The Skywork-Reward-V2 series outperforms models in both categories with much smaller model sizes. 1. For most use cases, we recommend Skywork-Reward-V2-Llama-3.1-8B and consider smaller variants for low-resource settings. 2. All models are trained on preference data with a maximum length of 16,384 tokens. It is recommended to perform inference within this limit. 3. Do not include system prompts when using chat templates.

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.

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。

Frequently asked questions

Sources & traceability

许可证：llama3.1。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。