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,但后续用dataset.map进行处理也会非常慢。 高效解决方案 一种方法是先将jsonl文件转换成arrow格式,然后使用load_from_disk进行加载: # ...
from datasets import load_dataset dataset = load_dataset("squad", split="train") dataset.features {'answers': Sequence(feature={'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int32', id=None)}, length=-1, id=None), 'context': Value(dtype='string', id=None...
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",...
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 ...
Load Texts from Disk 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...
Error: FileStream will not open Win32 devices such as disk partitions... Error: Invalid token '=' in class, struct, or interface member declaration Error: property or indexer cannot be assigned to it is read only error: System.FormatException: 'Input string was not in a correct format Erro...
In my last post we saw how to clean, transform and join datasets. I also mentioned I had trouble... Date: 09/25/2014 How to Train your MAML–Refining the data In my last post we looked at how to load data into Microsoft Azure Machine Learning using the... Date: 09/18/2014 How ...
Fluid launches JuiceFS-related components, including FUSE and Worker Pod, where FUSE Pod provides caching capabilities for JuiceFS clients and Worker Pod enables cache lifecycle management. Nodes, while users are able to visualize cache usage (e.g., size of cached datasets, percentage of cache, ca...
Combined with REST APIs and Regular Expressions (RegEx) enablement, developers can now enrich, validate, and manipulate their datasets with external data sources. This allows for building more dynamic, enterprise-grade applications with richer functionality and enhanced ...
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