Add explanation about the different subsets

README.md

@@ -163,6 +163,17 @@ The wikipedia articles were split into multiple, disjoint text blocks of 100 wor
 
 The wikipedia dump is the one from Dec. 20, 2018.
 
+There are two types of DPR embeddings based on two different models:
+- `nq`: the model is trained on the Natural Questions dataset
+- `multiset`: the model is trained on multiple datasets
+
+Additionally, a FAISS index can be created from the embeddings:
+- `exact`: with an exact FAISS index (high RAM usage)
+- `compressed`: with a compressed FAISS index (approximate, but lower RAM usage)
+- `no_index`: without FAISS index
+
+Finally, there is the possibility of generating the dataset without the embeddings:
+- `no_embeddings`
 
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