tulu-3-wildchat-if-on-policy-70b

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# Llama 3.1 Tulu 3 Wildchat IF (on-policy 70b)

*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 dataset is part of our Tulu 3 preference mixture:
it contains prompts from [WildChat](allenai/WildChat-1M), which include constraints, and it contains 10,792 generation pairs (some of which on-policy from allenai/Llama-3.1-Tulu-3-70B) 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.

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# Llama 3.1 Tulu 3 Wildchat IF（同策略70B版本）

*请注意，此数据集集合采用 ODC-BY-1.0 许可证授权；数据子集可能适用不同的许可证。数据集的部分内容为非商业用途。我们将此混合数据集作为研究成果发布。*

此偏好数据集属于我们的 Tulu 3 偏好混合数据集的一部分：其提示词源自 [WildChat](allenai/WildChat-1M)，包含各类约束条件；此外数据集包含 10,792 个生成对（其中部分为来自 allenai/Llama-3.1-Tulu-3-70B 的**同策略（on-policy）**生成结果），这些生成对通过以下模型获取：

- [Mistral 7B Instruct v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)（采用 Apache 2.0 许可证）
- [Mistral Nemo Instruct 2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)（采用 Apache 2.0 许可证）
- [Tulu 2 7B](https://huggingface.co/allenai/tulu-2-7b)（采用 Ai2 ImpACT 低风险许可证）
- [Tulu 2 13B](https://huggingface.co/allenai/tulu-2-13b)（采用 Ai2 ImpACT 低风险许可证）
- [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat)（采用 Apache 2.0 许可证）
- [Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)（采用 Apache 2.0 许可证）
- [MPT 30B Chat](https://huggingface.co/mosaicml/mpt-30b-chat)（采用 CC-BY-SA-4.0 许可证）
- [MPT 7B 8k Chat](https://huggingface.co/mosaicml/mpt-7b-8k-chat)（采用 CC-BY-SA-4.0 许可证）
- [Google Gemma 2 27B it](https://huggingface.co/google/gemma-2-27b-it)（Gemma 模型需遵守 [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms) 中的 Gemma 使用条款）
- [Google Gemma 2 9B it](https://huggingface.co/google/gemma-2-9b-it)（Gemma 模型需遵守 [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms) 中的 Gemma 使用条款）
- [InternLM2.5 20B](https://huggingface.co/internlm/internlm2_5-20b-chat)（InternLM 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，请参照模型卡片中的说明获取）
- [InternLM2.5 7B](https://huggingface.co/internlm/internlm2_5-7b-chat)（InternLM 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，请参照模型卡片中的说明获取）
- [InternLM2.5 1.8B](https://huggingface.co/internlm/internlm2_5-1_8b-chat)（InternLM 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，请参照模型卡片中的说明获取）
- [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b-instruct)（采用 Apache 2.0 许可证）
- [Qwen2.5 72B Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct)（Qwen 采用 Qwen 许可协议授权，版权所有 © 阿里巴巴云计算有限公司，保留所有权利）
- [Qwen2.5 32B Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct)（采用 Apache 2.0 许可证）
- [Qwen2.5 14B Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)（采用 Apache 2.0 许可证）
- [Qwen2.5 7B Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)（采用 Apache 2.0 许可证）
- [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”，因此需遵守 Llama 3.1 许可证）
- [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”，因此需遵守 Llama 3.1 许可证）
- [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”，因此需遵守 Llama 3 许可证）
- [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 生成的输出需遵守 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 生成的输出需遵守 Anthropic 的[服务条款](https://www.anthropic.com/legal/commercial-terms)与[使用政策](https://www.anthropic.com/legal/aup)）

## 补全生成方法
给定一组提示词，我们通过结合同策略（on-policy）与异策略（off-policy）数据的合成流水线生成补全结果与偏好标签，并使用 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。该合成生成流水线的代码可在 [open-instruct](https://github.com/allenai/open-instruct/) 的 scripts/synth_pref 目录中找到。

## 许可证
此数据集采用 ODC-BY 许可证授权，旨在遵循艾伦人工智能研究所（Allen Institute for AI）的[负责任使用指南](https://allenai.org/responsible-use)供研究与教育使用。本数据集包含由第三方模型生成的输出数据，这些数据需遵守其各自的使用条款。

搜集汇总

背景与挑战

背景概述

该数据集是Tulu 3偏好混合的一部分，包含来自WildChat的提示和10,792个生成对，部分生成对来自allenai/Llama-3.1-Tulu-3-70B模型。它采用合成生成管道结合在策略和离策略数据，并基于Ultrafeedback模板进行偏好标注，遵循ODC-BY许可证，适用于研究和教育用途。