[DOC] more detailed steps to add model

README.md

@@ -1038,6 +1038,21 @@ file](https://github.com/tatsu-lab/alpaca_eval/tree/main/src/alpaca_eval/leaderb
 with the
 config, outputs file, and updated leaderboard.
 
+Concretely you should do something like:
+
+1. Fork the repository in github
+2. Clone the forked repository `git clone <URL>`
+3. Make a model config at `src/alpaca_eval/models_configs/<model_name>` and evaluate it `evaluate_from_model --model_configs '<model_name>'`
+4. Add the model configs, output, and leaderboard entry to the forked repository
+```sh
+git add src/alpaca_eval/models_configs/<model_name>
+git add src/alpaca_eval/leaderboards/data_AlpacaEval
+git add results/<model_name>/model_outputs.json
+git commit -m "Add <model_name> to AlpacaEval"
+git push
+``` 
+5. Create a [pull request on AlpacaEval](https://github.com/tatsu-lab/alpaca_eval/pulls)
+
 </details>
 
 <details>

src/alpaca_eval/annotators/base.py

@@ -109,6 +109,11 @@ def SingleAnnotator(self) -> Type["SingleAnnotator"]:
         pass
 
     #######################
+    @property
+    def available_fields_to_format(self):
+        """Fields that can be formatted in the prompt template."""
+        return self.all_keys
+
     @property
     def annotation_key(self) -> str:
         """How to refer to the annotations, this will be the key for annotations in the output."""
@@ -231,7 +236,9 @@ def _annotate(self, df_to_annotate: pd.DataFrame, **decoding_kwargs) -> pd.DataF
             logging.info(f"Annotating {curr_idcs.sum()} examples with {annotator}")
 
             # actual annotation
-            curr_annotated = self.annotators[annotator](df_annotated.loc[curr_idcs, self.all_keys], **decoding_kwargs)
+            curr_annotated = self.annotators[annotator](
+                df_annotated.loc[curr_idcs, self.available_fields_to_format], **decoding_kwargs
+            )
 
             df_annotated = self._merge_annotations(df_annotated, curr_annotated)