Prompt Templating

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Builtin Templates

By default, we provide two templates for question-and-answering which we have adapted from Alpaca-Lora format as our prompt template format. You can use these templates or create your own. For more information on templating see this page.

There are two options for the templates, short and long. The short template is a single sentence prompt and the long template is a multi-sentence prompt. They are shown below:

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Alpaca template (long)

description: "Generic long template for fine-tuning.",
prompt_input: "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:\n",
prompt_no_input: "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n",
response_split: "### Response:"

This would be used by adding the following to your config.yaml file:

dataset_args:
  prompt_template: "long"

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Alpaca template (short)

"description": "A shorter template to experiment with.",
"prompt_input": "### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:\n",
"prompt_no_input": "### Instruction:\n{instruction}\n\n### Response:\n",
"response_split": "### Response:"

This would be used by adding the following to your config.yaml file:

dataset_args:
  prompt_template: "short"

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Custom Templates

If you would like to use a custom template, you can do so by adding it to your config.yaml file under the prompt_template parameter. This should be in the format shown below:

dataset_args:
  prompt_template:
    "description": "An optional description for your template",
    "prompt_input": "### Your Instruction:\n{instruction}\n\n### Some context label:\n{input}\n\n### Your response prefix:\n",
    "prompt_no_input":  "### Your Instruction:\n{instruction}\n\n### Your response prefix:\n",
    "response_split": "### Your response prefix:"

Where your template contains the following parameters in the template string:

• {instruction}: The instruction for the prompt. This will be filled in with the instruction_column parameter from your dataset.
• {input}: The context for the prompt. This will be filled in with the context_column parameter from your dataset.
• {response}: The response prefix for the prompt. This will be filled in with the label_column parameter from your dataset.

where instruction_column, context_column, and label_column are the parameters you have defined for your dataset in the dataset_args section of your config file and correspond to the labels in your dataset.json file.