有没有一种方法可以让我只从 Huggingface 下载数据集的一部分？

Question

我正在尝试加载（人民语音）数据集，但它太大了，有没有办法只下载其中的一部分？

from datasets import load_dataset

from datasets import load_dataset

train = load_dataset("MLCommons/peoples_speech", "clean",split="train[:10%]")
test = load_dataset("MLCommons/peoples_speech", "clean",split="test[:10%]")

使用 ("train [: 10%]") 没有帮助，它仍在尝试下载整个数据集......

Answer 1

您是否考虑过使用中的流功能Datasets？它允许您从 HuggingFace 的 Hub 流式传输数据，而无需在本地下载数据集。

from datasets import load_dataset
from torch.utils.data import DataLoader
# you get a dict of {"split": IterableDataset}
dataset = load_dataset("MLCommons/peoples_speech", "clean", streaming=True)
# your preprocessing and filtering
...
train_dataloader = DataLoader(dataset["train"], batch_size=4)
valid_dataloader = DataLoader(dataset["validation"], batch_size=4)
train_steps_per_epoch = 500
# training loop
for n in range(5):
    for i, batch in enumerate(train_dataloader):
        # if you only want to do a limited amount of optimization steps per epoch
        if i == train_steps_per_epoch:
            break
        # train step
        ...

我希望它有帮助。