diff --git a/docs/analyzer/nlp_engines/transformers.md b/docs/analyzer/nlp_engines/transformers.md
index 1beb11121..12f737fda 100644
--- a/docs/analyzer/nlp_engines/transformers.md
+++ b/docs/analyzer/nlp_engines/transformers.md
@@ -208,6 +208,14 @@ The `ner_model_configuration` section contains the following parameters:
 - `low_confidence_score_multiplier`: A multiplier to apply to the score of entities with low confidence.
 - `low_score_entity_names`: A list of entity types to apply the low confidence score multiplier to.
 
+
+!!! note "Defining the entity mapping"
+    To be able to create the `model_to_presidio_entity_mapping` dictionary, it is advised to check which classes the model is able to predict. 
+    This can be found on the huggingface hub site for the model in some cases. In other, one can check the model's `config.json` uner `id2label`. 
+    For example, for `bert-base-NER-uncased`, it can be found here: https://huggingface.co/dslim/bert-base-NER-uncased/blob/main/config.json. 
+    Note that most NER models add a prefix to the class (e.g. `B-PER` for class `PER`). When creating the mapping, do not add the prefix.
+
+
 See more information on parameters on the [spacy-huggingface-pipelines Github repo](https://github.com/explosion/spacy-huggingface-pipelines#token-classification).
   
 Once created, see [the NLP configuration documentation](../customizing_nlp_models.md#Configure-Presidio-to-use-the-new-model) for more information.