Remove embeddings and keep only the chunked docs

README.md

@@ -13,7 +13,7 @@ size_categories:
 
 ## Overview
 
-This dataset consists of chunked and embedded versions of a small subset of MongoDB's technical documentation. It contains 795 chunks from 498 documentation pages, sampled from 50 documentation sources.
+This dataset consists of chunked versions of a small subset of MongoDB's technical documentation. It contains 795 chunks from 498 documentation pages, sampled from 50 documentation sources.
 
 ## Dataset Structure
 
@@ -26,9 +26,8 @@ The dataset consists of the following fields:
 - url: Link to the documentation page.
 - title: Title of the documentation page.
 - text: Content of the chunk in Markdown format.
-- embedding: The embedding of the chunk's content, created using Voyage AI's [voyage-4-large](https://www.mongodb.com/docs/voyageai/models/text-embeddings/) model with 1024 dimensions.
 
-Pages were split into chunks of up to ~2,000 tokens at Markdown heading boundaries. Because the Voyage 4 models share an embedding space, you can embed queries for this dataset with `voyage-4-large`, `voyage-4`, or `voyage-4-lite`.
+Pages were split into chunks of up to ~2,000 tokens at Markdown heading boundaries.
 
 ## Usage
 
@@ -49,7 +48,7 @@ from pymongo import MongoClient
 client = MongoClient(os.environ["MONGODB_URI"])
 collection = client["your_database_name"]["mongodb_docs"]
 
-dataset = load_dataset("MongoDB/mongodb-docs-voyage-4-large", split="train")
+dataset = load_dataset("MongoDB/mongodb-docs-chunked", split="train")
 collection.insert_many(dataset.to_list())
 
 print(f"Ingested {len(dataset)} documents")

mongodb_docs_voyage_4_large.json

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7985d43559f567db1cc0175d0e7b8a4cf86b2c7fc69e9c1541847ffab63875f9
-size 22292835