How to Download

README.md

@@ -64,7 +64,7 @@ configs:
 
 **Industrial-scale music recommendation dataset with organic/recommendation interactions and audio embeddings**
 
- [📌 Overview](#overview) • [🔑 Key Features](#key-features) • [📊 Statistics](#statistics) • [📝 Format](#data-format) • [🏆 Benchmark](#benchmark) • [❓ FAQ](#faq)
+ [📌 Overview](#overview) • [🔑 Key Features](#key-features) • [📊 Statistics](#statistics) • [📝 Format](#data-format) • [🏆 Benchmark](#benchmark) • [⬇️ Download](#download) • [❓ FAQ](#faq)
 
 ## Overview
 
@@ -169,6 +169,62 @@ Each dataset is also available in a user-aggregated sequential format with the f
 
 Code for the baseline models can be found in `benchmarks/` directory, see [Reproducibility Guide](benchmarks/README.md)
 
+### Download
+
+Simplest way:
+```python
+from datasets import load_dataset
+
+ds = load_dataset("yandex/yambda", data_dir="flat/50m", data_files="likes.parquet")
+```
+
+Also, we provide simple wrapper for convenient
+usage
+```python
+from typing import Literal
+
+from datasets import Dataset, DatasetDict, load_dataset
+
+
+class YambdaDataset:
+    INTERACTIONS = frozenset(["likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"])
+
+    def __init__(
+        self, dataset_type: Literal["flat", "sequential"] = "flat", dataset_size: Literal["50m", "500m", "5b"] = "50m"
+    ):
+        assert dataset_type in {"flat", "sequential"}
+        assert dataset_size in {"50m", "500m", "5b"}
+
+        self.dataset_type = dataset_type
+        self.dataset_size = dataset_size
+
+    def interaction(
+        self, type: Literal["likes", "listens", "multi_event", "dislikes", "unlikes", "undislikes"]
+    ) -> Dataset:
+        assert type in YambdaDataset.INTERACTIONS
+
+        return YambdaDataset._download(f"{self.dataset_type}/{self.dataset_size}", type)
+
+    def audio_embeddings(self) -> Dataset:
+        return YambdaDataset._download("", "embeddings")
+
+    def album_item_mapping(self) -> Dataset:
+        return YambdaDataset._download("", "album_item_mapping")
+
+    def artist_item_mapping(self) -> Dataset:
+        return YambdaDataset._download("", "artist_item_mapping")
+
+    @staticmethod
+    def _download(data_dir: str, file: str) -> Dataset:
+        data = load_dataset("yandex/yambda", data_dir=data_dir, data_files=f"{file}.parquet")
+        assert isinstance(data, DatasetDict)
+        return data["train"]
+
+dataset = YambdaDataset("flat", "50m")
+
+likes = dataset.interaction("likes")
+```
+
 ## FAQ
 
 ### Are test items presented in training data?
@@ -201,4 +257,4 @@ A track is considered "listened" if over 50% of its duration is played.
 
 A played_ratio_pct greater than 100% indicates that the user rewound and 
 replayed sections of the track—so the total time listened exceeds the original track length. 
-These values are expected behavior and not log noise. See [discussion](https://huggingface.co/datasets/yandex/yambda/discussions/10)
+These values are expected behavior and not log noise. See [discussion](https://huggingface.co/datasets/yandex/yambda/discussions/10)