Update README

README.md

@@ -22,11 +22,11 @@ This model can be used to build embeddings databases with [txtai](https://github
 ```python
 import txtai
 
-# New embeddings with requested number of dimensions
+# New embeddings with requested dimensionality
 embeddings = txtai.Embeddings(
   path="neuml/pubmedbert-base-embeddings-matryoshka",
   content=True,
-  dimensions=256
+  dimensionality=256
 )
 embeddings.index(documents())
 
@@ -45,10 +45,10 @@ sentences = ["This is an example sentence", "Each sentence is converted"]
 model = SentenceTransformer("neuml/pubmedbert-base-embeddings-matryoshka")
 embeddings = model.encode(sentences)
 
-# Requested matryoshka dimensions
-dimensions = 256
+# Requested dimensionality
+dimensionality = 256
 
-print(embeddings[:, :dimensions])
+print(embeddings[:, :dimensionality])
 ```
 
 ## Usage (Hugging Face Transformers)
@@ -82,11 +82,11 @@ with torch.no_grad():
 # Perform pooling. In this case, mean pooling.
 embeddings = meanpooling(output, inputs['attention_mask'])
 
-# Requested matryoshka dimensions
-dimensions = 256
+# Requested dimensionality
+dimensionality = 256
 
 print("Sentence embeddings:")
-print(embeddings[:, :dimensions])
+print(embeddings[:, :dimensionality])
 ```
 
 ## Evaluation Results