Update README.md

README.md

@@ -114,9 +114,9 @@ The following fields were extracted and/or transformed from the original source:
 Each article is naturally isolated and has its own `cid` value. But in case the article is too long, we have to split it in several chunks.
 The Langchain's `RecursiveCharacterTextSplitter` function was used to make these chunks, which correspond to the `text` value. The parameters used are :
 
-- `chunk_size` = 5000
-- `chunk_overlap` = 250
-- `length_function` = len
+- `chunk_size` = 1024
+- `chunk_overlap` = 0
+- `length_function` = bge_m3_tokenizer
 
 For each chunk (`text`), a `chunk_text` is constructed as follows:
 
@@ -133,7 +133,7 @@ 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**.