Update README.md

README.md

@@ -17,7 +17,7 @@ size_categories:
 license: etalab-2.0
 configs:
 - config_name: latest
-  data_files: data/legi-latest/*.parquet
+  data_files: "data/legi-latest/*/*.parquet"
   default: true
 ---
 
@@ -36,6 +36,8 @@ In this version, only versions of articles that are currently **in force** (`VIG
 
 Each article is chunked and vectorized using the [`BAAI/bge-m3`](https://huggingface.co/BAAI/bge-m3) embedding model, enabling use in **semantic search**, **retrieval-augmented generation (RAG)**, and **legal research** systems for example.
 
+The dataset is splitted in subfolders by 'category' and 'CODE', so that the dataset is more usable for specifics use cases.
+
 ---
 
 ## 🗂️ Dataset Contents
@@ -129,12 +131,12 @@ import json
 from datasets import load_dataset
 # The Pyarrow library must be installed in your Python environment for this example. By doing => pip install pyarrow
 
-dataset = load_dataset("AgentPublic/legi")
+dataset = load_dataset("AgentPublic/legi") # Loading the full dataset
 df = pd.DataFrame(dataset['train'])
 df["embeddings_bge-m3"] = df["embeddings_bge-m3"].apply(json.loads)
 ```
 
-Otherwise, if you have already downloaded all parquet files from the `data/legi-latest/` folder : 
+Otherwise, if you have already downloaded some parquet files from the `data/legi-latest/` folder : 
 ```python
 import pandas as pd
 import json