We support the [Jinja 2](https://jinja.palletsprojects.com/en/3.1.x/) templating language for writing prompts. In practice, this means you can take your dataset's columns and do many basic string manipulations to place each document into prompted format.
Suppose our dataset has a `"question"` field, and an `"answer"` field, which are both strings. We want the model to see, if given a `document` object that is a row of our dataset:
Take for example `super_glue/boolq`, as input, we'd like to use the features `passage` and `question` and string them together so that for a a sample line `doc`, the model sees something the format of:
```
Question: {document[question]}
doc["passage"]
Question: doc["question"]?
Answer:
```
We do this by writing
We do this by [writing](https://github.com/EleutherAI/lm-evaluation-harness/blob/1710b42d52d0f327cb0eb3cb1bfbbeca992836ca/lm_eval/tasks/super_glue/boolq/default.yaml#L9C1-L9C61)
Such that {{question}} will be replaced by `doc["question"]` when rendering the prompt template.
Such that `{{passage}}` will be replaced by `doc["passage"]` and `{{question}}` with `doc["question"]` when rendering the prompt template.
Our intended output is for the model to predict a single whitespace, and then the answer to the question. We do this via:
```yaml
doc_to_target:"{{answer}}"
```
`doc_to_target` can output either a string or a integer that corresponds to an index that will point to the correct option from `doc_to_choice`. If `doc_to_target` is an index, the fewshot samples generated will still be a string that is sourced from `doc_to_choice` using that index.
**Important**: We always add one whitespace between the input and output, such that the full input-output string is `doc_to_target(doc) + " " + doc_to_text(doc)`. doc_to_text and doc_to_target should not contain trailing right or left whitespace, respectively.
