llama-3.1-tulu-3-70b-preference-mixture

<img src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu-3/Tulu3-logo.png" alt="Tulu3 banner" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

# Llama 3.1 Tulu 3 70B Preference Mixture

*Note that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact.*

This preference mixture used for DPO on our the [Llama 3.1 Tulu 3 70B SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-SFT) checkpoint to obtain [Llama 3.1 Tulu 3 70B DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO).

This mix is made up from the following preference datasets:
- https://huggingface.co/datasets/allenai/tulu-3-sft-reused-off-policy
- https://huggingface.co/datasets/allenai/tulu-3-sft-reused-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-IF-augmented-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-unused
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-ultrafeedback-cleaned-on-policy-70b

It contains 337,186 generation pairs obtained using the following models:
- [Mistral 7B Instruct v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) (Apache 2.0)
- [Mistral Nemo Instruct 2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) (Apache 2.0)
- [Tulu 2 7B](https://huggingface.co/allenai/tulu-2-7b) (Ai2 ImpACT Low Risk License)
- [Tulu 2 13B](https://huggingface.co/allenai/tulu-2-13b) (Ai2 ImpACT Low Risk License)
- [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat) (Apache 2.0)
- [Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat) (Apache 2.0)
- [MPT 30B Chat](https://huggingface.co/mosaicml/mpt-30b-chat) (CC-BY-SA-4.0)
- [MPT 7B 8k Chat](https://huggingface.co/mosaicml/mpt-7b-8k-chat) (CC-BY-SA-4.0)
- [Google Gemma 2 27B it](https://huggingface.co/google/gemma-2-27b-it) (Gemma is provided under and subject to the Gemma Terms of Use found at [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms))
- [Google Gemma 2 9B it](https://huggingface.co/google/gemma-2-9b-it) (Gemma is provided under and subject to the Gemma Terms of Use found at [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms))
- [InternLM2.5 20B](https://huggingface.co/internlm/internlm2_5-20b-chat) (InternLM weights are fully open for academic research and also allow free commercial usage. A commercial license can be obtained as instructed in the model card.)
- [InternLM2.5 7B](https://huggingface.co/internlm/internlm2_5-7b-chat) (InternLM weights are fully open for academic research and also allow free commercial usage. A commercial license can be obtained as instructed in the model card.)
- [InternLM2.5 1.8B](https://huggingface.co/internlm/internlm2_5-1_8b-chat) (InternLM weights are fully open for academic research and also allow free commercial usage. A commercial license can be obtained as instructed in the model card.)
- [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b-instruct) (Apache 2.0)
- [Qwen2.5 72B Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) (Qwen is licensed under the Qwen LICENSE AGREEMENT, Copyright (c) Alibaba Cloud. All Rights Reserved.)
- [Qwen2.5 32B Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) (Apache 2.0)
- [Qwen2.5 14B Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) (Apache 2.0)
- [Qwen2.5 7B Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) (Apache 2.0)
- [Llama 3.1 8B Instruct ](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) (this dataset was partially "Built with Llama" and is thus subject to the Llama 3.1 License)
- [Llama 3.1 70B Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) (this dataset was partially "Built with Llama" and is thus subject to the Llama 3.1 License)
- [Llama 3 8B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B) (this dataset was partially "Built with Meta Llama 3" and is thus subject to the Llama 3 License)
- [GPT-4 Turbo](https://openai.com/index/new-models-and-developer-products-announced-at-devday/) and [GPT-4o](https://openai.com/index/hello-gpt-4o/) (Outputs produced by GPT-4 are subject to OpenAI's [terms of use](https://openai.com/policies/row-terms-of-use))
- [Claude 3.5 Sonnet](https://www.anthropic.com/news/claude-3-5-sonnet) (Outputs produced by Claude are subject to Anthropic [terms of service](https://www.anthropic.com/legal/commercial-terms) and [usage policy](https://www.anthropic.com/legal/aup))

### Model Family

| **Stage** | **Llama 3.1 8B** | **Llama 3.1 70B** |
|----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
| **Base Model** | [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) | [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B) |
| **SFT** | [allenai/Llama-3.1-Tulu-3-8B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-SFT) | [allenai/Llama-3.1-Tulu-3-70B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-SFT) |
| **DPO** | [allenai/Llama-3.1-Tulu-3-8B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-DPO) | [allenai/Llama-3.1-Tulu-3-70B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO) |
| **Final Models (RLVR)** | [allenai/Llama-3.1-Tulu-3-8B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B) | [allenai/Llama-3.1-Tulu-3-70B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B) |
| **Reward Model (RM)**| [allenai/Llama-3.1-Tulu-3-8B-RM](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-RM) | (Same as 8B) |

## License
This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use). This dataset includes output data generated from third party models that are subject to separate terms governing their use.

## Citation

If Tülu3 or any of the related materials were helpful to your work, please cite:
```
@article{lambert2024tulu3,
title = {Tülu 3: Pushing Frontiers in Open Language Model Post-Training},
author = {
Nathan Lambert and
Jacob Morrison and
Valentina Pyatkin and
Shengyi Huang and
Hamish Ivison and
Faeze Brahman and
Lester James V. Miranda and
Alisa Liu and
Nouha Dziri and
Shane Lyu and
Yuling Gu and
Saumya Malik and
Victoria Graf and
Jena D. Hwang and
Jiangjiang Yang and
Ronan Le Bras and
Oyvind Tafjord and
Chris Wilhelm and
Luca Soldaini and
Noah A. Smith and
Yizhong Wang and
Pradeep Dasigi and
Hannaneh Hajishirzi
},
year = {2024},
email = {[e-mail]}
}
```

<img src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu-3/Tulu3-logo.png" alt="Tulu3 banner" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

# Llama 3.1 Tulu 3 70B 偏好混合数据集

*请注意，本数据集合集采用ODC-BY-1.0协议授权；数据子集可能适用不同的许可协议。本数据集部分内容仅允许非商业使用。我们将该混合数据集作为研究成果发布。*

本偏好混合数据集用于在我们的[Llama 3.1 Tulu 3 70B SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-SFT) 检查点上开展DPO训练，以得到[Llama 3.1 Tulu 3 70B DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO) 模型。

该混合数据集由以下偏好数据集构成：
- https://huggingface.co/datasets/allenai/tulu-3-sft-reused-off-policy
- https://huggingface.co/datasets/allenai/tulu-3-sft-reused-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-IF-augmented-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-unused
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-70b
- https://huggingface.co/datasets/allenai/tulu-3-ultrafeedback-cleaned-on-policy-70b

本数据集包含337,186组生成配对，其生成来源涵盖以下模型：
- [Mistral 7B Instruct v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)（采用Apache 2.0协议）
- [Mistral Nemo Instruct 2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)（采用Apache 2.0协议）
- [Tulu 2 7B](https://huggingface.co/allenai/tulu-2-7b)（采用Ai2 ImpACT低风险许可协议）
- [Tulu 2 13B](https://huggingface.co/allenai/tulu-2-13b)（采用Ai2 ImpACT低风险许可协议）
- [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat)（采用Apache 2.0协议）
- [Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)（采用Apache 2.0协议）
- [MPT 30B Chat](https://huggingface.co/mosaicml/mpt-30b-chat)（采用CC-BY-SA-4.0协议）
- [MPT 7B 8k Chat](https://huggingface.co/mosaicml/mpt-7b-8k-chat)（采用CC-BY-SA-4.0协议）
- [Google Gemma 2 27B it](https://huggingface.co/google/gemma-2-27b-it)（Gemma模型依据[ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms)中的Gemma使用条款提供并受其约束）
- [Google Gemma 2 9B it](https://huggingface.co/google/gemma-2-9b-it)（Gemma模型依据[ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms)中的Gemma使用条款提供并受其约束）
- [InternLM2.5 20B](https://huggingface.co/internlm/internlm2_5-20b-chat)（InternLM模型权重完全开放用于学术研究，同时支持免费商业使用。商业许可可参照模型卡中的说明申请。）
- [InternLM2.5 7B](https://huggingface.co/internlm/internlm2_5-7b-chat)（InternLM模型权重完全开放用于学术研究，同时支持免费商业使用。商业许可可参照模型卡中的说明申请。）
- [InternLM2.5 1.8B](https://huggingface.co/internlm/internlm2_5-1_8b-chat)（InternLM模型权重完全开放用于学术研究，同时支持免费商业使用。商业许可可参照模型卡中的说明申请。）
- [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b-instruct)（采用Apache 2.0协议）
- [Qwen2.5 72B Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct)（Qwen模型依据Qwen许可协议授权，版权归阿里云所有，保留所有权利。）
- [Qwen2.5 32B Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct)（采用Apache 2.0协议）
- [Qwen2.5 14B Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)（采用Apache 2.0协议）
- [Qwen2.5 7B Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)（采用Apache 2.0协议）
- [Llama 3.1 8B Instruct ](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)（本数据集部分内容“基于Llama构建”，因此需遵循Llama 3.1许可协议）
- [Llama 3.1 70B Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct)（本数据集部分内容“基于Llama构建”，因此需遵循Llama 3.1许可协议）
- [Llama 3 8B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B)（本数据集部分内容“基于Meta Llama 3构建”，因此需遵循Llama 3许可协议）
- [GPT-4 Turbo](https://openai.com/index/new-models-and-developer-products-announced-at-devday/) 和 [GPT-4o](https://openai.com/index/hello-gpt-4o/)（GPT-4生成的输出需遵循OpenAI的[使用条款](https://openai.com/policies/row-terms-of-use)）
- [Claude 3.5 Sonnet](https://www.anthropic.com/news/claude-3-5-sonnet)（Claude生成的输出需遵循Anthropic的[服务条款](https://www.anthropic.com/legal/commercial-terms)与[使用政策](https://www.anthropic.com/legal/aup)）

### 模型家族

| **阶段** | **Llama 3.1 8B** | **Llama 3.1 70B** |
|----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
| **基础模型** | [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) | [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B) |
| **SFT** | [allenai/Llama-3.1-Tulu-3-8B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-SFT) | [allenai/Llama-3.1-Tulu-3-70B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-SFT) |
| **DPO** | [allenai/Llama-3.1-Tulu-3-8B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-DPO) | [allenai/Llama-3.1-Tulu-3-70B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO) |
| **最终模型（RLVR）** | [allenai/Llama-3.1-Tulu-3-8B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B) | [allenai/Llama-3.1-Tulu-3-70B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B) |
| **奖励模型（RM）**| [allenai/Llama-3.1-Tulu-3-8B-RM](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-RM) | 与8B版本一致 |

## 许可协议

本数据集采用ODC-BY协议授权。依据艾伦人工智能研究所(Ai2)的[负责任使用指南](https://allenai.org/responsible-use)，本数据集仅用于研究与教育用途。本数据集包含由第三方模型生成的输出数据，此类数据需遵循对应模型的单独使用条款。

## 引用方式

若Tülu3或其相关材料对你的研究工作有所帮助，请引用以下文献：

@article{lambert2024tulu3,
title = {Tülu 3: Pushing Frontiers in Open Language Model Post-Training},
author = {
Nathan Lambert and
Jacob Morrison and
Valentina Pyatkin and
Shengyi Huang and
Hamish Ivison and
Faeze Brahman and
Lester James V. Miranda and
Alisa Liu and
Nouha Dziri and
Shane Lyu and
Yuling Gu and
Saumya Malik and
Victoria Graf and
Jena D. Hwang and
Jiangjiang Yang and
Ronan Le Bras and
Oyvind Tafjord and
Chris Wilhelm and
Luca Soldaini and
Noah A. Smith and
Yizhong Wang and
Pradeep Dasigi and
Hannaneh Hajishirzi
},
year = {2024},
email = {[e-mail]}
}