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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).
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## Model
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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).
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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.
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# RLT-7B
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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).
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## Model Details
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- **Developed by:** [Sakana AI](https://sakana.ai/)
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- **Model type:** Autoregressive Language Model
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- **License:** Apache License, Version 2.0
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- **Paper:** https://arxiv.org/abs/2506.08388
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- **Code:** https://github.com/SakanaAI/RLT
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## Model Description
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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).
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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.
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