一、Load dataset 本节参考官方文档:Load数据集存储在各种位置,比如 Hub 、本地计算机的磁盘上、Github 存储库中以及内存中的数据结构(如 Python 词典和 Pandas DataFrames)中。无论您的数据集存储在何处, Datasets 都为您提供了一种加载和使用它进行训练的方法。 本节将向您展示如何从以下位
datasets = load_dataset('cail2018',split='exercise_contest_test') # 如果知道数据的结构,在load的时候就可以用split只load进来一部分数据; # 从数据集里面取数据 datasets_sample = datasets[ "exercise_contest_train" ].shuffle(seed= 42 ).select( range ( 1000 )) # 这里就是从cail2018这个数据集里面...
ConnectionError Traceback (most recent call last)/tmp/ipykernel_21708/3707219471.py in <module>---> 1 dataset=datasets.load_dataset("yelp_review_full")myenv/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, downloa...
---> 1 dataset=datasets.load_dataset("yelp_review_full") myenv/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_...
加载Dataset数据集 Dataset数据集可以是HuggingFace Datasets网站上的数据集或者是本地路径对应的数据集,也可以同时加载多个数据集。 以下是加载英语阅读理解数据集squad, 该数据集的网址为:<https:///datasets/squad> ,也是本文中使用的主要数据集。 importdatasets# 加载单个数据集raw_datasets=datasets.load_dataset('...
For more details on using the library with these frameworks, check the quick start page in the documentation: https://huggingface.co/docs/datasets/quickstart Usage 🤗 Datasets is made to be very simple to use - the API is centered around a single function, datasets.load_dataset(dataset_name...
>>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') []...
宇树人形机器人,全身运动数据集开源适配 我们将动捕数据重新定位到Unitree H1、H1_2和G1人形机器人,使用数值优化方法,让轨迹更加自然。开源:https://huggingface.co/datasets/unitreerobo - Unitree宇树科技于20250103发布在抖音,已经收获了607.9万个喜欢,来抖音,记
然后用data_files指定文件名称,data_files可以是字符串,列表或者字典,data_dir指定数据集目录。如下case fromdatasetsimportload_dataset dataset = load_dataset('csv', data_files='my_file.csv') dataset = load_dataset('csv', data_files=['my_file_1.csv','my_file_2.csv','my_file_3.csv']) ...
Click to add a brief description of the dataset (Markdown and LaTeX enabled). Provide: a high-level explanation of the dataset characteristics explain motivations and summary of its content potential use cases of the dataset