理解datasets.load_from_disk的运作机制需要拆解数据存储与加载的全链路。这个函数背后依赖ApacheArrow内存数据结构，通过预先生成的二进制文件实现快速读取，避免反复解析原始数据带来的性能损耗。数据集存储路径下通常包含data-00000-of-00001.arrow这样的核心数据文件，配套dataset_info.json记录字段类型、特征描述等元数据。
DatasetGenerationError: An error occurred while generating the dataset 普通解决方案 然后可以使用pandas的方法进行全量加载:(过程比较慢) import pandas as pd df = pd.read_json(jsonl_path, lines=True) df.head() from datasets import Dataset dataset = Dataset.from_pandas(df) 加载后的dataset也能使用,...
load_from_disk#7268 New issue Open Description ghaith-mq Hello, It's an interesting issue here. I have the same problem, I have a local dataset and I want to push the dataset to the hub but huggingface does a copy of it. fromdatasetsimportload_datasetdataset=load_dataset("webdataset",...
data_files=["s3://<bucket name>/<data folder>/data-parquet"],storage_options=fs.storage_options,streaming=True)File~/.../datasets/src/datasets/load.py:1790,inload_dataset(path,name,data_dir,data_files,split,cache_dir,features,download_config,download_mode,verification_mode,ignore_verification...
Datasets提供了许多工具来修改数据集的结构和内容。这些工具对于整理数据集、创建附加列、在特征和格式之间进行转换以及更多操作非常重要。 本指南将向您展示如何: 重新排列行并拆分数据集。 重命名和删除列以及其他常见的列操作。 对数据集中的每个示例应用处理函数。 连接数据集。 应用自定义格式转换。 保存和导出处理...
You can also load text datasets in the same way. dataset_url="http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz"local_file_path=keras.utils.get_file(fname="text_data",origin=dataset_url,extract=True,)# The file is extracted in the same directory as the downloaded file....
llamafactory报错:磁盘不足 | LLama-factory训练时报错:OSError: Not enough disk space. Needed: Unknown size (download: Unknown size, generated: Unknown size, post-processed: Unknown size) 解决: 给出一个临时解决方案,参考:huggingface/datasets#1785 ...
Steps to reproduce the bug fromdatasetsimportload_datasetdataset=load_dataset("art")dataset.save_to_disk("mydir")d=Dataset.load_from_disk("mydir") Expected results It is expected that these two functions be the reverse of each other without more manipulation ...