LLaMA-Factory-Mirror/data/README.md

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If you are using a custom dataset, please provide your dataset definition in the following format in `dataset_info.json`.
```json
"dataset_name": {
"hf_hub_url": "the name of the dataset repository on the HuggingFace hub. (if specified, ignore below 3 arguments)",
"script_url": "the name of the directory containing a dataset loading script. (if specified, ignore below 2 arguments)",
"file_name": "the name of the dataset file in the this directory. (required if above are not specified)",
"file_sha1": "the SHA-1 hash value of the dataset file. (optional)",
"ranking": "whether the examples contains ranked responses or not. (default: false)",
"columns": {
"prompt": "the name of the column in the datasets containing the prompts. (default: instruction)",
"query": "the name of the column in the datasets containing the queries. (default: input)",
"response": "the name of the column in the datasets containing the responses. (default: output)",
"history": "the name of the column in the datasets containing the history of chat. (default: None)"
}
}
```
where the `prompt` and `response` columns should contain non-empty values. The `query` column will be concatenated with the `prompt` column and used as input for the model. The `history` column should contain a list where each element is a string tuple representing a query-response pair.
For datasets used in reward modeling or DPO training, the `response` column should be a string list, with the preferred answers appearing first, for example:
```json
{
"instruction": "Question",
"input": "",
"output": [
"Chosen answer",
"Rejected answer"
]
}
```