Update README.md

README.md

@@ -100,7 +100,7 @@ No recursive split was necessary as legal articles and memos are inherently stru
 If needed, the Langchain's `RecursiveCharacterTextSplitter` function was used to make these chunks (`text` value). The parameters used are : 
 
 - `chunk_size` = 8000
-- `chunk_overlap` = 400
+- `chunk_overlap` = 0
 - `length_function` = len
 
 ---
@@ -112,7 +112,7 @@ The resulting embedding vector is stored in the `embeddings_bge-m3` column as a
 
 ## 🔄 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**.