参数是存储库命名空间和数据集名称(epository mespace and dataset name) from datasets import load_dataset dataset = load_dataset('lhoestq/demo1') 根据revision加载指定版本数据集:(某些数据集可能有Git 标签、branches or commits多个版本) dataset = load_dataset( "lhoestq/custom_squad", revision="...
valid: Dataset({ features: ['headline', 'label', 'input_ids', 'attention_mask'], num_rows: 2850 }) }) 4、提取模型体并添加我们自己的层 代码如下: class CustomModel(nn.Module): def __init__(self,checkpoint,num_labels): super(CustomModel,self).__init__() self.num_labels = num_la...
#https://discuss.huggingface.co/t/how-to-create-custom-classlabels/13650# "basic_sentiment holds values [-1,0,1] from datasets import ClassLabel dataset_from_pandas = dataset_from_pandas.cast_column("label", ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, ...
My goal will be to perform multi-label text classification on my own custom dataset, which unfortunately I cannot share for privacy reasons. If anyone could point out what is wrong with this implementation, will be highly appreciated. tensorflow huggingface-transformers transfer-learning huggingface-to...
Hi there, I am trying to add my custom ag_news with its own loading script on the Hugging Face datasets hub. In particular, I would like to test the addition of a second configuration to the existing ag_news dataset. Once it works in my ...
我修复了你的代码,数据集不是pandas数据集,它是pyarrow表,它们有不同的列名,没有loc方法,你需要...
from datetime import timedelta from accelerate import InitProcessGroupKwargs # Create the custom configuration process_group_kwargs = InitProcessGroupKwargs(timeout=timedelta(seconds=5400)) # 1.5 hours # Instantiate Accelerator with the custom configuration accelerator = Accelerator(kwargs_handlers=[proces...
Huggingface的T5模型词汇表包括纯英语版本。T5(Text-to-Text Transfer Transformer)是一种基于Transformer架构的预训练模型,用于自然语言处理任务。T5模型的词汇表是根据训练数据集的语言分布而生成的,因此包括多种语言版本,包括纯英语版本。 T5模型的优势在于其通用性和灵活性,它可以应用于各种自然语言处理任务,...
使用df_pandas = train_data_s1.to_pandas(),请参阅文档。
Coming back to our custom loading script, let’s create a new file calledcrema.py. This is what a typical loading script will look like for any new dataset: Figure 1: Generated using the blanktemplateprovided by Huggingface. As you can see, there are three main functions that need modif...