Update README.md

README.md

@@ -7,7 +7,7 @@ task_categories:
 - sentence-similarity
 language:
 - en
-pretty_name: Embeddings for Books
+pretty_name: FAISS Vector Store of Embeddings for Books
 tags:
 - faiss
 - langchain
@@ -27,13 +27,15 @@ Creating these embeddings can take a while so here's a convenient, downloadable
 
 ## How to use
 
-1. Specify the book
-   - `1984`
-   - `The Almanac of Naval Ravikant`
+1. Specify the book from one of the following:
+   - `"1984"`
+   - `"The Almanac of Naval Ravikant"`
 3. Download data
 4. Load to use with LangChain
 
+```
 pip install -qqq langchain InstructorEmbedding sentence_transformers faiss-cpu huggingface_hub
+```
 
 ```python
 import os
@@ -43,11 +45,11 @@ from huggingface_hub import snapshot_download
 
 # download the vectorstore for the book you want
 book="1984"
-cache_dir="orwell_faiss"
-vectorstore = snapshot_download(repo_id="calmgoose/orwell-1984_faiss-instructembeddings",
+cache_dir=f"{book}_cache"
+vectorstore = snapshot_download(repo_id="calmgoose/book-embeddings",
                                 repo_type="dataset",
                                 revision="main",
-                                allow_patterns=f"books/{book}/*",
+                                allow_patterns=f"books/{book}/*", # to download only the one book
                                 cache_dir=cache_dir,
                                 )