Update README.md

README.md

@@ -29,7 +29,11 @@ Below is an example and a set of functions to compute the cosine similarity betw
 loads the model and tokenizer based on `model_name`. It returns a tuple containing the loaded model and tokenizer.
 
 ```python
-from transformers import AutoModelForTextEncoding, AutoTokenizer
+from typing import List, Tuple
+
+import torch
+from transformers import AutoModel, AutoTokenizer
+from transformers import AutoModelForTextEncoding
 
 def load_model_and_tokenizer(model_name: str) -> Tuple[AutoModel, AutoTokenizer]:
     """
@@ -114,6 +118,8 @@ Helper fn to compute and print out cosine similarity
 
 
 ```python
+from scipy.spatial.distance import cosine
+
 def calculate_cosine_similarity(embeddings: torch.Tensor, texts: List[str]) -> None:
     """
     Calculate and print the cosine similarity between the first text and all other texts.