Update README.md

README.md

@@ -23,10 +23,12 @@ Below is an example and a set of functions to compute the cosine similarity betw
 
 ### load_model_and_tokenizer
 
+Loads the model and tokenizer based on `model_name`, returning a tuple containing the loaded model and tokenizer.
+
+
 <details>
 <summary><b>Details</b></summary>
 
-loads the model and tokenizer based on `model_name`. It returns a tuple containing the loaded model and tokenizer.
 
 ```python
 from typing import List, Tuple
@@ -161,11 +163,11 @@ embeddings = get_embeddings(model, tokenizer, texts)
 calculate_cosine_similarity(embeddings, texts)
 ```
 
-This will print the cosine similarity between the first text and all other texts in the `texts` list.
+This will print the cosine similarity between the first text and all other texts in the `texts' list.
 
 ## References
 
-This guide is based on the examples provided in the [sGPT repository](https://github.com/Muennighoff/sgpt#symmetric-semantic-search-be).
+Inference with this model/the example is based on the ideas and examples in the [SGPT repository](https://github.com/Muennighoff/sgpt#symmetric-semantic-search-be).
 
 ```
 @article{muennighoff2022sgpt,