Rethinking-Large-scale-Dataset-Compression
Collection
Distilled and pruning datasets used in the paper "Rethinking Large-scale Dataset Compression: Shifting Focus From Labels to Images"
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Dataset used for paper -> "Rethinking Dataset Compression: Shifting Focus From Labels to Images"
Dataset created according to the paper An Empirical Study of Example Forgetting during Deep Neural Network Learning.
Basic Usage
from datasets import load_dataset
dataset = load_dataset("he-yang/2025-rethinkdc-imagenet-forgetting-ipc-100")
For more information, please refer to the Rethinking-Dataset-Compression
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Size of downloaded dataset files:
7.58 GB
Size of the auto-converted Parquet files:
7.58 GB
Number of rows:
100,000