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2026-07-13 12:38:16 +08:00

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---
title: Reward models
---
These models output a scalar reward score or classification result, often used in reinforcement learning or content moderation tasks.
They are executed with `--is-embedding` and some may require `--trust-remote-code`.
## Example launch Command
<CodeGroup>
```shell Command
python3 -m sglang.launch_server \
--model-path Qwen/Qwen2.5-Math-RM-72B \ # example HF/local path
--is-embedding \
--host 0.0.0.0 \
--tp-size=4 \ # set for tensor parallelism
--port 30000 \
```
</CodeGroup>
## Supported models
| Model Family (Reward) | Example HuggingFace Identifier | Description |
|---------------------------------------------------------------------------|-----------------------------------------------------|---------------------------------------------------------------------------------|
| **Llama (3.1 Reward / `LlamaForSequenceClassification`)** | `Skywork/Skywork-Reward-Llama-3.1-8B-v0.2` | Reward model (preference classifier) based on Llama 3.1 (8B) for scoring and ranking responses for RLHF. |
| **Gemma 2 (27B Reward / `Gemma2ForSequenceClassification`)** | `Skywork/Skywork-Reward-Gemma-2-27B-v0.2` | Derived from Gemma2 (27B), this model provides human preference scoring for RLHF and multilingual tasks. |
| **InternLM 2 (Reward / `InternLM2ForRewardMode`)** | `internlm/internlm2-7b-reward` | InternLM 2 (7B)based reward model used in alignment pipelines to guide outputs toward preferred behavior. |
| **Qwen2.5 (Reward - Math / `Qwen2ForRewardModel`)** | `Qwen/Qwen2.5-Math-RM-72B` | A 72B math-specialized RLHF reward model from the Qwen2.5 series, tuned for evaluating and refining responses. |
| **Qwen2.5 (Reward - Sequence / `Qwen2ForSequenceClassification`)** | `jason9693/Qwen2.5-1.5B-apeach` | A smaller Qwen2.5 variant used for sequence classification, offering an alternative RLHF scoring mechanism. |