将数据集下载到本地后,使用datasets进行加载,data_files文件指定路径 fromdatasetsimportload_datasetdataset=load_dataset("text",data_files=r"./toutiao_cat_data.txt") 查看数据可以看到一共有382688条数据,字段为text >>>dataset DatasetDict({ train: Dataset({ features: ['text'], num_rows: 382688 })...
首先使用datasets加载数据集: fromdatasetsimportload_dataset dataset = load_dataset('text', data_files={'train':'data/train_20w.txt','test':'data/val_2w.txt'}) 加载后的dataset是一个DatasetDict对象: DatasetDict({ train: Dataset({ features: ['text'], num_rows:3}) test: Dataset({ feature...
from datasets import load_dataset data_files = {"train":"train.txt", "test":"test.txt"} raw_datasets = load_dataset(".", data_files=data_files) 查看数据样式 print(raw_datasets) DatasetDict({ train: Dataset({ features: ['text'], num_rows: 5 }) test: Dataset({ features: ['text...
from datasets import load_dataset from transformers import AutoTokenizer, DataCollatorForSeq2Seq, AutoModelForSeq2SeqLM, Seq2SeqTrainingArguments, Seq2SeqTrainer """利用load_dataset()来读取数据: - 该方法支持.txt、.csv、.json等文件格式 - 返回结果是一个字典类型 - 读取.txt文件时,若不指定名称,这...
requests.head("https://www.dropbox.com/s/1pzkadrvffbqw6o/train.txt?dl=1") 1. 2. 3. <Response [301]> 1. from datasets import load_dataset emotions = load_dataset("emotion") 1. 2. 3. 0%| | 0/3 [00:00<?, ?it/s] ...
例如: datasets = load_dataset("text", data_files={"train": path_to_train.txt, "validation": path_to_validation.txt} 具体可以参考文档 load_dataset命令下载并缓存数据集,默认在 ~/.cache/huggingface/dataset 中。您可以通过设置 HF_HOME 环境变量来自定义缓存文件夹。
train_loader= DataLoader(train_dataset, batch_size=self.batch_size, shuffle=True) val_dataloader= DataLoader(val_dataset, batch_size=self.batch_size, shuffle=True) optim= AdamW(model.parameters(), lr=2e-5) loss_fn=nn.CrossEntropyLoss() ...
Evaluates the model on eval_dataset. Utility function to be used by the eval_model() method. Not intended to be used directly load_and_cache_examples(self, data, evaluate=False, no_cache=False, to_predict=None) Converts a list of InputExample objects to a TensorDataset containing InputFeatu...
importtensorflowastfimporttensorflow_datasetsfromtransformersimport*# Load dataset, tokenizer, model from pretrained model/vocabularytokenizer=BertTokenizer.from_pretrained('bert-base-cased')model=TFBertForSequenceClassification.from_pretrained('bert-base-cased')data=tensorflow_datasets.load('glue/mrpc')# Pre...
# re-load #SOTA examples for GLUE, SQUAD, text generation... Transformers 同时支持 PyTorch 和 TensorFlow2.0,用户可以将这些工具放在一起使用。如下为使用 TensorFlow2.0 和 Transformer 的代码: import tensorflow as tfimport tensorflow_datasetsfrom transformers import * #Load dataset, tokenizer, model from...