diff --git a/README.md b/README.md
index 6e81d2f6617047154c7d698c19848117d4ced1c5..42e0ba578cd2e6ccce768baa1edcc89c3c991da0 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,25 @@ language:
 - uk
 size_categories:
 - 10B<n<100B
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: compound_id
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 118180394141
+    num_examples: 38941863
+  download_size: 57328717488
+  dataset_size: 118180394141
 ---
 ## Malyuk [mɐˈlʲuk]
 
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diff --git a/malyuk.py b/malyuk.py
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index a5c92fcef742fb9b414ce63bbed264c0e6917b5b..0000000000000000000000000000000000000000
--- a/malyuk.py
+++ /dev/null
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-import json
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_DESCRIPTION = """\
-Malyuk — a large, compiled corpus of ukrainian language texts.
-113GB of text data in jsonl format.
-Combination of UberText 2.0, Ukrainian part of the Oscar, and Ukrainian News.
-
-Nothing is guaranteed. Use at your own risk.
-"""
-
-
-_URLS = [
-    "combined_ds_pt00.jsonlines",
-    "combined_ds_pt01.jsonlines",
-    "combined_ds_pt02.jsonlines",
-    "combined_ds_pt03.jsonlines",
-    "combined_ds_pt04.jsonlines",
-    "combined_ds_pt05.jsonlines",
-    "combined_ds_pt06.jsonlines",
-    "combined_ds_pt07.jsonlines",
-    "combined_ds_pt08.jsonlines",
-    "combined_ds_pt09.jsonlines",
-    "combined_ds_pt10.jsonlines",
-    "combined_ds_pt11.jsonlines",
-    "combined_ds_pt12.jsonlines",
-    "combined_ds_pt13.jsonlines",
-    "combined_ds_pt14.jsonlines",
-    "combined_ds_pt15.jsonlines",
-    "combined_ds_pt16.jsonlines",
-    "combined_ds_pt17.jsonlines",
-    "combined_ds_pt18.jsonlines",
-    "combined_ds_pt19.jsonlines",
-    "combined_ds_pt20.jsonlines",
-    "combined_ds_pt21.jsonlines",
-    "combined_ds_pt22.jsonlines",
-]
-
-
-class MalyukDataset(datasets.GeneratorBasedBuilder):
-    """
-    Malyuk Dataset
-
-    ~^^^^^^:::^?7!!!!!~~~~~~~~~~~~~~^^^^^^::::::.............:::::::::^^:::::::^^^^^~~~~~~~~~~!:........
-    ~^^^^^^:::^7!~!!!!!~~~~~~~^^^^^^^~~~~^^^^^^^::::::::::::^^^^^^^^^^:::::::::::^^~~~~~!!!~~!!:........
-    ~~~^^^^:::^7!~!!!~~~~~~^^^^^^^^^~~~~~~~~~~~~~~~~~~~!!~~~~!~~~~~~~~~~~~~~~^^:::^^~~~~~~!!~!7^........
-    ~~~^^^^^^:~7!!!~~!~~~~~~~~!!!!!!!!777777777777!!!~~!777???JJYY55YYJ?7?777777!~~~^~~~~~!77??^........
-    !~~~^^^^^:~?!!!!!!!!!!7?Y55555555PBGPPPPPPPP5YJJ?777JY5PPPG########BBBBGGGGGP5Y?!~!~~~~77??:........
-    7!~~^^^^^:^7!!!!!!!7?YPGBBGGGGGGGBB########BBGGPP5YY5GB####&&&&&##BGGGBB####BBG5?!!~~~~~!?7.........
-    7!~~^~~~~~^!!!!!!!!?YPGGGP55PPGBB####&&&&&&##BBPJ7!~!75##&&&&&#BB###BBGGGB###BGPY?7~~~~^~7~:::^^^...
-    ?7~~^JPJ7!7?~!!!77?J5PPPGBB#BGG&&@&#PG#&&&##BBGJ!^::::!5BBB###GY5#&&&#GG##BBBBGP5?7~~^^^^~~^~!?P5:..
-    J7~~^JBGJ??7~!!!!7?JJ5PGGBBBG5J5GBG5Y5GBBGGGPPJ7!~::.:^!J555GPP5JY555JJ5GGGP55Y?!~~^^^^^^~!JY5B#?...
-    J7!~~7PY?J??7!!!!!!7?JYYYYY5555555PPPP55YYYYYJ?!~~^:::^~!?JJJJY55YY555555Y?7!~~^^^^^^~~~^7Y55JYP~...
-    J7!~~!J7?YYJ7!!!!!!!!777???JJY55555YYJJ????????7!~^:::^~!777!!!7??????77!~^^::::::^^^~!~~7PP5J7?~...
-    J7!~~~!?Y5PG?7!!!!~~~~~~~~!!777777??777777????77!!~^::^!!777!~~^~~!!~~^:::...::::^^~~~!!!7GGPY!~:...
-    ?7!!~~~7YPGGJ7!!!!!~~~~~~~~~~~~~~!!~~~~!77????77!!~^^:^~!77?7!~^^::^^^^^^^:^^^^^^~~~!!!77?PPY7~^....
-    ?77!~~~!?5PPJ77!!!!!!~!!!!~~~~~~~^^^~~~!7?J?777!!~^^:::^!!7?J!~^^::::::^^~~~~~~~~~!!!!7??7YY?~~^....
-    """
-
-    VERSION = datasets.Version("1.0.0")
-    DEFAULT_CONFIG_NAME = "default"
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="default", version=VERSION, description=""),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "compound_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                }
-            ),
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(_URLS)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}
-            )
-        ]
-
-    def _generate_examples(self, filepaths):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepaths)
-        key = 0
-        for path in filepaths:
-            with open(path, encoding="utf-8") as f:
-                for instruction_str in f:
-                    instruction = json.loads(instruction_str)
-                    yield key, instruction
-                    key += 1