pre-commit reformat

docs/README.md

 # Eval Harness Documentation
 
-Welcome to the docs for the LM Evaluation Harness! 
+Welcome to the docs for the LM Evaluation Harness!
 
 ## Table of Contents
 
@@ -20,4 +20,4 @@ Tracking progress on revamping documentation pages for the refactor of LM-Evalua
 * [ ] Explaining registries + decorators
 * [ ] model_guide.md for adding new model API
   * [ ] guide to writing an adapter to new advanced codebase (e.g. NeoX)
-* [ ] Parallelism guide (?)
+* [ ] Parallelism guide (?)
\ No newline at end of file

docs/model_guide.md

@@ -46,9 +46,9 @@ class MyCustomLM(LM):
     #...
 ```
 
-We support 
+We support
 
-The three types of 
+The three types of
 
 
 
@@ -64,9 +64,9 @@ smth smth tokenizer-agnostic
 
 ## Registration
 
-Congrats on implementing your model! Now it's time to test it out. 
+Congrats on implementing your model! Now it's time to test it out.
 
-To make your model usable via the command line interface to `lm-eval` using `main.py`, you'll need to tell `lm-eval` what your model's name is. 
+To make your model usable via the command line interface to `lm-eval` using `main.py`, you'll need to tell `lm-eval` what your model's name is.
 
 This is done via a *decorator*, `lm_eval.api.registry.register_model`. Using `register_model()`, one can both tell the package what the model's name(s) to be used are when invoking it with `python main.py --model <name>` and alert `lm-eval` to the model's existence.
 
@@ -87,4 +87,4 @@ Using this decorator results in the class being added to an accounting of the us
 
 ## Conclusion
 
-After reading this guide, you should be able to add new model APIs or implementations to the Eval Harness library! 
+After reading this guide, you should be able to add new model APIs or implementations to the Eval Harness library!
\ No newline at end of file

lm_eval/api/task.py

@@ -436,7 +436,9 @@ class Task(abc.ABC):
             # always prepend the (possibly empty) task description
             labeled_examples = self._config.description
         else:
-            labeled_examples = self._config.description + self.sampler.get_context(doc, num_fewshot)
+            labeled_examples = self._config.description + self.sampler.get_context(
+                doc, num_fewshot
+            )
 
         example = self.doc_to_text(doc)
         return labeled_examples + example