Update README.md

README.md

@@ -18,12 +18,10 @@ Embeddings is the engine that delivers semantic search. Data is transformed into
 An embeddings index generated by txtai is a fully encapsulated index format. It DOESN'T require a database server.
 
 This index is built from the [Wikipedia Februari 2024 dataset](https://huggingface.co/datasets/burgerbee/wikipedia-sv-20240220).
-Only the first two paragraph from each article is included. The Wikipedia index works well as a fact-based context source for retrieval augmented generation (RAG).
-
-It also uses [Wikipedia Page Views](https://dumps.wikimedia.org/other/pageviews/readme.html) data to add a `percentile` field. The `percentile` field can be used
+Only the first two paragraph from each article is included. The Wikipedia index works well as a fact-based context source for retrieval augmented generation (RAG). It also uses [Wikipedia Page Views](https://dumps.wikimedia.org/other/pageviews/readme.html) data to add a `percentile` field. The `percentile` field can be used
 to only match commonly visited pages.
 
-txtai must be [installed](https://neuml.github.io/txtai/install/) to use this model.
+txtai must be (pip) [installed](https://neuml.github.io/txtai/install/) to use this model.
 
 ## Example
 
@@ -44,7 +42,7 @@ for x in embeddings.search("SELECT id, text, score, percentile FROM txtai WHERE
   print(json.dumps(x, indent=2))
 ```
 
-# Source
+# Data source
 
 https://dumps.wikimedia.org/svwiki/20240220/dumpstatus.json