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datasets-library

Manage ML datasets with the datasets ecosystem — loading, streaming, preprocessing, versioning, and sharing. Use when data handling (not modeling) is the bottleneck.

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# Datasets Library

Models get the glory; datasets decide the outcome. The datasets ecosystem gives you: one-line 
loading of thousands of public datasets, memory-mapped access to data bigger than RAM, streaming 
for internet-scale corpora, and versioned, shareable dataset artifacts.

## Overview

The core abstractions: Dataset (an Arrow-backed table — fast, memory-mapped, sliceable), 
DatasetDict (train/validation/test splits together), and streaming mode (iterate without 
downloading). Processing is functional: `map` for transforms, `filter` for selection, `shuffle`, 
`select`, `train_test_split` — all returning new dataset objects, lazily evaluated and cached. 
Push to the hub to version and share.