Update README.md

README.md

@@ -81,8 +81,8 @@ The following fields were extracted and/or transformed from the original source:
 
 The Langchain's `RecursiveCharacterTextSplitter` function was used to make these chunks, which correspond to the `text` value. The parameters used are :
 
-- `chunk_size` = 1500 (in order to maximize the compability of most LLMs context windows)
-- `chunk_overlap` = 200
+- `chunk_size` = 1500
+- `chunk_overlap` = 0
 - `length_function` = len
 
 The value of `chunk_text` includes the `title` and the textual content chunk `text`. This strategy is designed to improve document search.
@@ -94,7 +94,7 @@ The resulting embedding is stored as a JSON stringified array of 1024 floating p
 
 ## 🔄 The chunking doesn't fit your use case?
 
-[**SOON AVAILABLE FOR THIS DATASET**] ~~If you need to reconstitute the original, un-chunked dataset, you can follow [this tutorial notebook available on our GitHub repository](https://github.com/etalab-ia/mediatech/blob/main/docs/reconstruct_vector_database.ipynb).~~
+If you need to reconstitute the original, un-chunked dataset, you can follow [this tutorial notebook available on our GitHub repository](https://github.com/etalab-ia/mediatech/blob/main/docs/reconstruct_vector_database.ipynb).
 
 ⚠️ The tutorial is only relevant for datasets that were chunked **without overlap**.