问题描述 / Problem Description 启动时出现报错: AttributeError: 'ChatGLMTokenizer' object has no attribute 'tokenizer' 复现问题的步骤 / Steps to Reproduce 按要求部署环境,并配置ChatGLM2-6B模型绝对地址 执行python startup.py -a 出现以下报错信息: (langchai
self.token_pad_id = tokenizer._token_pad_id AttributeError: 'Tokenizer' object has no attribute '_token_pad_id' ### 自我尝试 不管什么问题,请先尝试自行解决,“万般努力”之下仍然无法解决再来提问。此处请贴上你的努力过程。 已经确认词表有[PAD],换了几个模型和词表还是这样报错,求助大神们...
报错:AttributeError: 'ChatGLMTokenizer' object has no attribute 'tokenizer'. Did you mean: 'tokenize'? 解决办法:报错的transformers版本 transformers==4.34.0 修改后的transformers版本transformers==4.33.2 pip uninstall transformers pip install transformers==4.33.2 ...
使用keras包实现NLP问题时,报错 /lib/python3.5/dist-packages/keras/preprocessing/text.py”, line302,intexts_to_sequences_generator elif self.oov_tokenisnot None: AttributeError: ‘Tokenizer’objecthas no attribute ‘oov_token’ 报错的代码行为 train_sequences = tokenizer.texts_to_sequences(new_trai...
I’m importing tokenization, have installed via pip, and cannot instantiate the tokenizer. I’m using the following code below and continue to get an error message of “module ‘tokenization’ has no attribute ‘FullTokenizer’”. Anyone have a sense as to why?
最近在学习机器。在学习过程中使用kaggle中的Womens Clothing E-Commerce Reviews.csv数据集,用Keras分词器Tokenizer,使用tokenizer.fit_on_texts生成词典报'float' object has no attribute 'lower'错。 fromkeras.preprocessing.textimportTokenizer X_train_lst = df_train["Review Text"] ...
AttributeError: 'ChatGLMTokenizer' object has no attribute 'sp_tokenizer' 继续查看报错信息,发现该错误源于tokenization_chatglm.py中ChatGLMTokenizer类的__init__方法 super().__init__( 解决 该问题出现的原因是,在调用super().__init__()之后才设置self.sp_tokenizer属性,而父类的__init__方法中用到...
Attributes RegisterAttribute Remarks Returns the same value as the hasMoreTokens method. It exists so that this class can implement the Enumeration interface. Java documentation for java.util.StringTokenizer.hasMoreElements(). Portions of this page are modifications based on work created and shared by...
device=torch.device("cuda"iftorch.cuda.is_available()else"cpu")model=TextClassifier(vocab_size=len(tokenizer),embedding_dim=100,hidden_dim=256,output_dim=num_classes)model.to(device) 接下来,我们需要准备训练数据。在这里,我们使用了一个简单的文本数据集,该数据集包含了1000个文本样本以及它们的类别标...
RegisterAttribute Remarks Returns the same value as thehasMoreTokensmethod. It exists so that this class can implement theEnumerationinterface. Java documentation forjava.util.StringTokenizer.hasMoreElements(). Portions of this page are modifications based on work created and shared by theAndroid Open ...