Update README.md

README.md

@@ -30,7 +30,7 @@ This model is based on [microsoft/deberta-v3-base](https://huggingface.co/micros
 
 ## Usage with Sentencer Transformers (Recommended)
 
-The model can be used like this:
+The model can be used like this, on pairs of documents, passed as a list of list of strings (```List[List[str]]]```):
 
 ```python
 from sentence_transformers import CrossEncoder
@@ -52,6 +52,9 @@ This returns a numpy array representing a factual consistency score. A score < 0
 array([0.61051559, 0.00047493709, 0.99639291, 0.00021221573, 0.99599433, 0.0014127002, 0.002.8262993], dtype=float32)
 ```
 
+Note that the model is designed to work with entire documents, so long as they fit into the 512 token context window (across both documents). 
+Also note that the order of the documents is important, the first document is the source document, and the second document is validated against the first for factual consistency, e.g. as a summary of the first or a claim drawn from the source.
+
 ## Usage with Transformers AutoModel
 You can use the model also directly with Transformers library (without the SentenceTransformers library):