
- describe
process FreedomIntelligence/HuatuoGPT-sft-data-v1 to multiturn format
```json
{
    "instruction": "听起来很不错。人工智能可能在哪些方面面临挑战呢？",
    "input": "",
    "output": "人工智能面临的挑战包括数据隐私、安全和道德方面的问题，以及影响就业机会的自动化等问题。",
    "history": [
      ["你好，你能帮我解答一个问题吗？", "当然，请问有什么问题？"],
      ["我想了解人工智能的未来发展方向，你有什么想法吗？", "人工智能在未来的发展方向可能包括更强大的机器学习算法，更先进的自然语言处理技术，以及更加智能的机器人。"]
    ]
  }
```
which can be used at [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)

- example
task_categories:question-answering size_categories:100M<n<1B language:zh license:apache-2.0 medical region:us
{"language": ["zh"], "license": "apache-2.0", "size_categories": ["100M<n<1B"], "task_categories": ["question-answering"], "tags": ["medical"]}
TAGS
#task_categories-question-answering #size_categories-100M<n<1B #language-Chinese #license-apache-2.0 #medical #region-us 


- describe
process FreedomIntelligence/HuatuoGPT-sft-data-v1 to multiturn format

which can be used at LLaMA-Efficient-Tuning

- example
TAGS
#task_categories-question-answering #size_categories-100M<n<1B #language-Chinese #license-apache-2.0 #medical #region-us 

passage: TAGS
#task_categories-question-answering #size_categories-100M<n<1B #language-Chinese #license-apache-2.0 #medical #region-us 
