tulu-3-wildchat-ultrafeedback

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# Llama 3.1 Tulu 3 WildChat Ultrafeedback

*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 collection includes the following datasets:

- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-8b

This preference dataset is part of our Tulu 3 preference mixture:
it contains prompts from [WildChat](https://huggingface.co/datasets/allenai/WildChat) and generations 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))

## Completion Generation Approach:
Given a set of prompts, we generated the completions and preferences using a synthetic pipeline that combines both on-policy and off-policy data, and obtained the preference annotations on four different aspects using the Ultrafeedback template and an LLM judge. The code for the synthetic generation pipeline is found in the scripts/synth_pref directory of [open-instruct](https://github.com/allenai/open-instruct/)

## 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.

<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 WildChat 超反馈偏好数据集

**注意**：本数据集合集采用ODC-BY-1.0开源协议授权；数据子集可能适用不同授权条款，部分数据仅可用于非商业用途。本合集以研究原型的形式发布。

本合集包含以下数据集：
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-if-on-policy-8b
- https://huggingface.co/datasets/allenai/tulu-3-wildchat-reused-on-policy-8b

本偏好数据集属于Tulu 3偏好混合数据集的一部分，其提示词源自[WildChat](https://huggingface.co/datasets/allenai/WildChat)，模型生成结果由以下模型生成：
- [Mistral 7B Instruct v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)（采用Apache 2.0协议授权）
- [Mistral Nemo Instruct 2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)（采用Apache 2.0协议授权）
- [Tulu 2 7B](https://huggingface.co/allenai/tulu-2-7b)（采用Ai2低风险使用许可协议）
- [Tulu 2 13B](https://huggingface.co/allenai/tulu-2-13b)（采用Ai2低风险使用许可协议）
- [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat)（采用Apache 2.0协议授权）
- [Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)（采用Apache 2.0协议授权）
- [MPT 30B Chat](https://huggingface.co/mosaicml/mpt-30b-chat)（采用CC-BY-SA-4.0协议授权）
- [MPT 7B 8k Chat](https://huggingface.co/mosaicml/mpt-7b-8k-chat)（采用CC-BY-SA-4.0协议授权）
- [Google Gemma 2 27B it](https://huggingface.co/google/gemma-2-27b-it)（Gemma模型的使用需遵循[Gemma使用条款](https://ai.google.dev/gemma/terms)）
- [Google Gemma 2 9B it](https://huggingface.co/google/gemma-2-9b-it)（Gemma模型的使用需遵循[Gemma使用条款](https://ai.google.dev/gemma/terms)）
- [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；如需商业授权，请参照模型卡片说明申请）
- [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；如需商业授权，请参照模型卡片说明申请）
- [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；如需商业授权，请参照模型卡片说明申请）
- [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b-instruct)（采用Apache 2.0协议授权）
- [Qwen2.5 72B Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct)（采用Qwen许可协议授权，版权所有©阿里巴巴云计算有限公司，保留一切权利）
- [Qwen2.5 32B Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct)（采用Apache 2.0协议授权）
- [Qwen2.5 14B Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)（采用Apache 2.0协议授权）
- [Qwen2.5 7B Instruct](https://huggingface.co/Qwen/Qwen2.5-7b-Instruct)（采用Apache 2.0协议授权）
- [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开发，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开发，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开发，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/)与[GPT-4o](https://openai.com/index/hello-gpt-4o/)（GPT-4生成的输出内容需遵循OpenAI[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生成的输出内容需遵循Anthropic[服务条款](https://www.anthropic.com/legal/commercial-terms)与[使用政策](https://www.anthropic.com/legal/aup)）

## 完成内容生成方案
针对给定的提示词集合，我们采用结合同策略（on-policy）与异策略（off-policy）数据的合成流水线生成完成结果与偏好标签，并通过Ultrafeedback模板与大语言模型（LLM）评判器从四个不同维度获取偏好标注。合成生成流水线的代码可在[open-instruct](https://github.com/allenai/open-instruct/)的`scripts/synth_pref`目录中获取。

## 许可协议
本数据集采用ODC-BY协议授权。根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内容，这些内容需遵循对应模型的单独使用条款。