from datasets import load_datasetsquad_it_dataset= load_dataset("json", data_files="./data/SQuAD_it-train.json", field="data") #也可以加载文本文件 dataset = load_dataset('text', data_files={'train': ['my_text_1.txt', 'my_text_2.txt'], 'test': 'my_test_file.txt'}) 1.2 加...
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...
在PyTorch中,torch.utils.data 模块包含 Dataset 和DataLoader 两个类,但在导入时需要使用正确的类名。你的导入语句 from torch.utils.data import dataloader, dataset 中的dataloader 和dataset 是错误的,应该是 DataLoader 和Dataset。 正确的导入语句: python from torch.utils.data import DataLoader, Dataset ...
# This script needs these libraries to be installed: # numpy, transformers, datasets import wandb import os import numpy as np from datasets import load_dataset from transformers import TrainingArguments, Trainer from transformers import AutoTokenizer, AutoModelForSequenceClassification def tokenize_functio...
frompaddlenlp.trlimportSFTConfig,SFTTrainerfromdatasetsimportload_datasetdataset=load_dataset("ZHUI/alpaca_demo",split="train")training_args=SFTConfig(output_dir="Qwen/Qwen2.5-0.5B-SFT",device="gpu")trainer=SFTTrainer(args=training_args,model="Qwen/Qwen2.5-0.5B-Instruct",train_dataset=dataset, )...
import tensorflow as tf from tensorflow import keras def load_dataset(): # Step0 准备数据集, 可以是自己动手丰衣足食, 也可以从 tf.keras.datasets 加载需要的数据集(获取到的是numpy数据) # 这里以 mnist 为例 (x, y), (x_test, y_test) = keras.datasets.mnist.load_data() ...
Did you like using Folium to visualize your data? Did you work with a different dataset? What features of the library would you like to learn more about? Leave a note in the comments below and keep on mapping! Free Source Code:Click here to download the free source codefor building web...
from sklearn.cluster import DBSCAN DBSCAN主要参数: (1)eps: 两个样本被看作邻居节点的最大距离 (2)min_samples: 簇的样本数 (3)metric:距离计算方式 例:sklearn.cluster.DBSCAN(eps=0.5, min_samples=5, metric='euclidean') #*===1. 建立工程,导入sklearn相关包===** import numpy as np import ...
import tensorflow as tf from tensorflow import keras def load_dataset(): # Step0 准备数据集, 可以是自己动手丰衣足食, 也可以从 tf.keras.datasets 加载需要的数据集(获取到的是numpy数据) # 这里以 mnist 为例 (x, y), (x_test, y_test) = keras.datasets.mnist.load_data() # Step1 使用 ...
-- 1. Create an OSS external table for MaxCompute to store processing results of data in a public GitHub dataset. -- The OSS external table is named odps_external and is stored in the previously created OSS bucket. The OSS bucket is named xc-bucket-demo2. Yo...