
Here is a collective list of instruction dataset used for Neural Chat fine-tuning. The total number of instruction samples and tokens are about 1.1M and 326M respectively.

  | Type         | Language | Dataset                                                                                                                           | Number |
  |--| ---- |--------|----|
  | HC3  | en | [HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3)                                 | 24K   |
  | dolly  | en | [databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)                                 | 15K   |
  | alpaca-zh  | zh | [tigerbot-alpaca-zh-0.5m](https://huggingface.co/datasets/TigerResearch/tigerbot-alpaca-zh-0.5m)                                 | 500K   |
  | alpaca-en  | en | [TigerResearch/tigerbot-alpaca-en-50k](https://huggingface.co/datasets/TigerResearch/tigerbot-alpaca-en-50k)                                  | 50K   |
  | math     | en | [tigerbot-gsm-8k-en](https://huggingface.co/datasets/TigerResearch/tigerbot-gsm-8k-en)                                           | 8K     |
  | general     | en | [tigerbot-stackexchange-qa-en-0.5m](https://huggingface.co/datasets/TigerResearch/tigerbot-stackexchange-qa-en-0.5m)             | 500K    |

The collective dataset has been validated on multiple LLMs (such as MPT, LLama) by the NeuralChat team (Kaokao Lv, Wenxin Zhang, Xuhui Ren, and Haihao Shen) from Intel/SATG/AIA/AIPT. Thanks to [Hello-SimpleAI](https://huggingface.co/Hello-SimpleAI), [databricks](https://huggingface.co/databricks), [TigerResearch/TigerBot](https://github.com/TigerResearch/TigerBot) for releasing the open-source instruction dataset.


license:apache-2.0 region:us
{"license": "apache-2.0"}
TAGS
#license-apache-2.0 #region-us 

Here is a collective list of instruction dataset used for Neural Chat fine-tuning. The total number of instruction samples and tokens are about 1.1M and 326M respectively.



The collective dataset has been validated on multiple LLMs (such as MPT, LLama) by the NeuralChat team (Kaokao Lv, Wenxin Zhang, Xuhui Ren, and Haihao Shen) from Intel/SATG/AIA/AIPT. Thanks to Hello-SimpleAI, databricks, TigerResearch/TigerBot for releasing the open-source instruction dataset.



TAGS
#license-apache-2.0 #region-us 

passage: TAGS
#license-apache-2.0 #region-us 
