
# Dataset Card for "moss-002-sft-data"

## Dataset Description

- **Homepage:** [https://txsun1997.github.io/blogs/moss.html](https://txsun1997.github.io/blogs/moss.html)
- **Repository:** [https://github.com/OpenLMLab/MOSS](https://github.com/OpenLMLab/MOSS)
- **Total amount of disk used:** 2.16 GB

### Dataset Summary

An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to [Self-Instruct](https://arxiv.org/abs/2212.10560). The AI responses are generated using `text-davinci-003`. The user prompts of `en_harmlessness` are from [Anthropic red teaming data](https://github.com/anthropics/hh-rlhf/tree/master/red-team-attempts).

### Data Splits

| name                 | \# samples |
|----------------------|-----------:|
| en_helpfulness.json  | 419049     |
| en_honesty.json      | 112580     |
| en_harmlessness.json | 38873      |
| zh_helpfulness.json  | 447750     |
| zh_honesty.json      | 142885     |


task_categories:conversational task_categories:text-generation size_categories:1M<n<10M language:en language:zh license:cc-by-4.0 arxiv:2212.10560 region:us
{"language": ["en", "zh"], "license": "cc-by-4.0", "size_categories": ["1M<n<10M"], "task_categories": ["conversational", "text-generation"]}
TAGS
#task_categories-conversational #task_categories-text-generation #size_categories-1M<n<10M #language-English #language-Chinese #license-cc-by-4.0 #arxiv-2212.10560 #region-us 

Dataset Card for "moss-002-sft-data"
====================================


Dataset Description
-------------------


* Homepage: URL
* Repository: URL
* Total amount of disk used: 2.16 GB


### Dataset Summary


An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using 'text-davinci-003'. The user prompts of 'en\_harmlessness' are from Anthropic red teaming data.


### Data Splits




### Dataset Summary


An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using 'text-davinci-003'. The user prompts of 'en\_harmlessness' are from Anthropic red teaming data. ### Data Splits
TAGS
#task_categories-conversational #task_categories-text-generation #size_categories-1M<n<10M #language-English #language-Chinese #license-cc-by-4.0 #arxiv-2212.10560 #region-us 
 ### Dataset Summary


An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using 'text-davinci-003'. The user prompts of 'en\_harmlessness' are from Anthropic red teaming data. ### Data Splits
passage: TAGS
#task_categories-conversational #task_categories-text-generation #size_categories-1M<n<10M #language-English #language-Chinese #license-cc-by-4.0 #arxiv-2212.10560 #region-us 
### Dataset Summary


An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using 'text-davinci-003'. The user prompts of 'en\_harmlessness' are from Anthropic red teaming data.### Data Splits