importos os.environ["HF_ENDPOINT"]="https://hf-mirror.com"fromdatasetsimportload_dataset dataset=load_dataset(path='squad',split='train')print(dataset) 因为原网址是不可用的,如图 hf 原网址 上面修改的环境变量是在 datasets 库中的 config.py 文件中的变量,如下图: 环境变量...
1. 安装datasets库 在终端中运行以下命令来安装datasets库: ```bash pip install datasets ``` 2. 从datasets模块中导入load_dataset方法 在你的Python脚本或Jupyter笔记本中,使用以下代码导入load_dataset方法: ```python from datasets import load_dataset ``` 这一步将允许你使用load_dataset方法来加载数据集。
import os from torch import nn from torch.nn import functional as F from torch.autograd import Variable import matplotlib.pyplot as plt from torchvision.datasets import ImageFolder import torch.optim as optim import torch.utils.data from PIL import Image import torchvision.transforms as transforms # ...
from datasets import load_dataset , Dataset datasets = load_dataset('cail2018') # 导入数据 datasets_sample = datasets[ "exercise_contest_train" ].shuffle(seed= 42 ).select( range ( 1000 )) datasets_sample = datasets_sample.sort('punish_of_money') # 按照被罚金额排序,是从大到小的,这个排...
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...
cudnn.benchmark =Trueprint("===> Loading datasets") train_set =DatasetFromHdf5("path_to_dataset.h5") training_data_loader = DataLoader(dataset=train_set, num_workers=opt.threads, batch_size=opt.batchSize, shuffle=True) print("===> Building model") ...
from tensorflow import keras (X_train, y_train), (X_test, y_test) = keras.datasets.mnist.load_data() X_train = X_train.reshape(-1, 784) X_test = X_test.reshape(-1, 784) Since, I had tensorflow installed on my machine, I used keras to extract the mnist dataset. However, I ...
$ git clone https://huggingface.co/datasets/severo/test-parquet $ python -c 'from datasets import load_dataset; ds=load_dataset("test-parquet"); \ ds.save_to_disk("my_dataset"); load_dataset("my_dataset")' [...] Traceback (most recent call last): File "<string>", line 1, in...
# Datasets and Dataloaders train_data = TripletData(PATH_TRAIN, train_transforms) val_data = TripletData(PATH_VALID, val_transforms) train_loader = torch.utils.data.DataLoader(dataset = train_data, batch_size=32, shuffle=True, num_workers=4) ...
_dataset = tf.keras.utils.image_dataset_from_directory(train_dir, shuffle=True, batch_size=BATCH_SIZE, image_size=IMG_SIZE) validation_dataset = tf.keras.utils.image_dataset_from_directory(validation_dir, shuffle=True, batch_size=BATCH_SIZE, image_size=IMG_SIZE) class_names = train_...