处理完数据集后,您可以使用**save_to_disk()**保存并在以后重用它。 通过提供要保存到的目录的路径来保存数据集: >>> encoded_dataset.save_to_disk("path/of/my/dataset/directory") 使用**load_from_disk()**函数重新加载数据集: >>> from datasets import load_from_disk >>> reloaded_dataset = lo...
在LLaMA-Factory/src/llamafactory/data/loader.py 中的 from datasets import load_dataset, load_from_disk 后增加如下两行: import datasets datasets.builder.has_sufficient_disk_space = lambda needed_bytes, directory='.': True#知识分享#阅读分享 ...
If you don't manage to fix it you can useload_dataseton google colab and then save it usingdataset.save_to_disk("path/to/dataset"). Then you can download the directory on your machine and do fromdatasetsimportload_from_diskdataset=load_from_disk( split="train") I have the same proble...
Streaming support for load_from_disk #5838 Closed This was referenced May 24, 2023 load_dataset from s3 file system through streaming can't not iterate data #5880 Open Modify is_remote_filesystem to return True for FUSE-mounted paths #5885 Closed mayorblock commented Aug 7, 2023 ...
To bring data from a database to SAS is already considered a transformation. Having this in mind: 1- If you can, have a separate SAS environment for ETL (DI, BI,...) that will connect to database and load stuff into VA. 2- Maintain a local SAS datamart (in disk), in the...
from datasets import load_from_disk processed_datasets.save_to_disk("./news_data") disk_datasets = load_from_disk("./news_data") disk_datasets 加载本地数据集 前面介绍了加载公开数据集并进行处理,但是多数情况下,公开数据集并不能满足我们的需求,需要加载自行准备的数据集。下面来介绍如何加载本地的...
save_to_disk("path/of/my/dataset/directory") from datasets import load_from_disk reloaded_encoded_dataset = load_from_disk("path/of/my/dataset/directory") 2.6.2 Export导出 文件类型导出方式 CSV datasets.Dataset.to_csv() json datasets.Dataset.to_json() Parquet datasets.Dataset.to_parquet()...
Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic Python version: 3.7.12 PyArrow version: 6.0.1 is intended to be used to load a canonical dataset (wikipedia), a packaged dataset (csv,, useload_from_disk("path/to/dataset")....
import os.path from datasets import load_from_disk now_dir = os.path.dirname(os.path.abspath(__file__)) target_dir_path = os.path.join(now_dir,"my_cnn_dailymail") dataset = load_from_disk(target_dir_path) 前提:本机能连外网(如果本机也连不上外网,那就可以试试看第三方镜像战有没有...
from datasets import load_dataset datasets = load_dataset('cail2018') print(datasets) # 查看数据的结构 下面是打印出来看到的数据结构,整个数据集划分成了多个数据子集,包含train,valid以及test集。每个arrow_dataset都有多少条数据,以及这些数据的feature是什么。