update loading script

LICENSE

@@ -0,0 +1,2 @@
+/
+  This dataset is licensed under Creative Commons Attribution 4.0 International License.

dataset_info.json

@@ -0,0 +1 @@
+{"description": "  This dataset is an extraction from the OPENDATA/JADE. A list of case laws from the French court \"Conseil d'Etat\".\n", "citation": "", "homepage": "echanges.dila.gouv.fr", "license": "/\n  This dataset is licensed under Creative Commons Attribution 4.0 International License.\n", "features": {"title": {"dtype": "string", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}, "solution": {"dtype": "string", "id": null, "_type": "Value"}, "numero": {"dtype": "string", "id": null, "_type": "Value"}, "publi_receuil": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "french_open_fiscal_texts", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 790233334, "num_examples": 83591, "dataset_name": "french_open_fiscal_texts"}, "test": {"name": "test", "num_bytes": 198122747, "num_examples": 20898, "dataset_name": "french_open_fiscal_texts"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 988356081, "size_in_bytes": 988356081}

jade.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:912ced0c15447d25513b8275eb0708143de6744c6728f7db4991b933d8ff4aff
-size 441892975

jade.py

@@ -81,14 +81,19 @@ class FrenchOpenFiscalTexts(datasets.GeneratorBasedBuilder):
       )
 
     def _split_generators(self, dl_manager):
-      self.data_dir = dl_manager.download_and_extract(_URLS["jade"])
+      # self.data_dir = dl_manager.download_and_extract(_URLS["jade"])
+
+      print(dl_manager.download_config)
+      df = pd.read_parquet(dl_manager.download(_URLS["jade"]))
+
+      print(len(df))
+      print(df.head())
+
 
-      df = pd.read_parquet(self.data_dir)
 
       train = df.sample(frac=0.8,random_state=_SEED)
       test = df.drop(train.index)
 
-
       return [
         datasets.SplitGenerator(
           name=datasets.Split.TRAIN,