File size: 1,947 Bytes
5e61ec4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8c31ec6
5e61ec4
 
0fc43ea
5e61ec4
 
 
0fc43ea
 
 
 
 
 
 
5e61ec4
0fc43ea
5e61ec4
0fc43ea
253c57f
 
 
5e61ec4
 
253c57f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
---
license: apache-2.0
language:
- en
- zh
base_model:
- Qwen/Qwen2.5-7B-Instruct
pipeline_tag: text-generation
tags:
- reasoning
- reinforcement
- learning
- RLT
- math
- science
- code
- distillation
---

# RLT-7B

This repository contains a 7B parameter student model trained using the **Reinforcement-Learned Teachers (RLT)** pipeline introduced in our paper [Reinforcement Learning Teachers](https://arxiv.org/abs/2506.08388).

## Model Details

- **Developed by:** [Sakana AI](https://sakana.ai/)
- **Model type:** Autoregressive Language Model
- **License:** Apache License, Version 2.0
- **Paper:** https://arxiv.org/abs/2506.08388
- **Code:** https://github.com/SakanaAI/RLT

## Model Description

This 7B RLT student was distilled from a 7B Reinforcement-Learned Teacher, which has been explicitly trained to produce high-quality reasoning traces optimized for student distillation. The model was trained with supervised fine-tuning using the same hyperparameters, the system prompt, and the reasoning tags from [Li et al. 2025](https://arxiv.org/pdf/2502.07374).
Evaluation was conducted using the [SkyThought](https://github.com/NovaSky-AI/SkyThought) library at commit `4bb8f3e`. Please refer to our [repository](https://github.com/SakanaAI/RLT) and [paper](https://arxiv.org/abs/2506.08388) for details and results.


## Usage

This model is provided for research and development purposes only and should be considered as an experimental prototype. It is not intended for commercial use or deployment in mission-critical environments. Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed. Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained. Users must fully understand the risks associated with the use of this model and use it at their own discretion.