added explained to use python function

docs/new_task_guide.md

@@ -64,7 +64,7 @@ fewshot_split: <split name to draw fewshot examples from, or `null`>
 ```
 though if this is not set, we will default to train/validation/test sets, in that order.
 
-### Writing a prompt
+### Writing a prompt with Jinja 2
 
 The next thing we need to do is decide what format to use when presenting the data to the LM. This is our **prompt**, where we'll define both an input and output format.
 
@@ -93,6 +93,32 @@ doc_to_target: "{{answer}}"
 
 **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.
 
+### Using Python Functions for Prompts
+
+There may be cases where the prompt we want to implement is easier expressed in Python instead of Jinja 2. For this, we can use Python helper functions that are defined in the YAML config. It should be noted that the function script must be in the same directory as the yaml.
+
+A good example is WikiText that requires a lot of regex rules to clean the samples.
+```
+def wikitext_detokenizer(doc):
+    string = doc["page"]
+    # contractions
+    string = string.replace("s '", "s'")
+    string = re.sub(r"/' [0-9]/", r"/'[0-9]/", string)
+    ...
+    string = string.replace(" 's", "'s")
+
+    return string
+```
+
+We can load this function in `doc_to_target` by using a `!function` operator after `doc_to_target` and followed by `<file name>.<function name>`. In the file [wikitext.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/6ae376e3a43caa58b95bb8aa73054a94827bf560/lm_eval/tasks/wikitext/wikitext.yaml) we write:
+```
+doc_to_target: !function preprocess_wikitext.wikitext_detokenizer
+```
+
+### Importing a Prompt from Promptsource
+
+Promptsource is a great repository for crowdsourced prompts for many datasets. We can load these prompts easily by
+
 TODO: mention promptsource here, or reserve it for advanced guide
 
 #### Multiple choice format