tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-yelp-polarity") model = BertForSequenceClassification.from_pretrained("textattack/bert-base-uncased-yelp-polarity", problem_type="multi_label_classification") inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") w...
BertTokenizerfromtransformersimportBertForSequenceClassification,BertTokenizerFast,Trainer,TrainingArgumentsos.environ["CUDA_VISIBLE_DEVICES"]="0"device=torch.device("cuda"iftorch.cuda.is_available()else"cpu")bert_path=r"D:\team_code\dataset\pre_triained_model\bert-base-uncased...
使用“BERT”作为编码器和解码器(BERT2BERT)来改进Seq2Seq文本摘要模型QueryableStates 允许用户对流的内部...
transformers中的一个类,用来记录BertModel的基本配置,继承自PretrainedConfig,用来初始化BERT模型,实例化bert-base-uncased模型。 from transformers import BertModel, BertConfig# 默认使用bert-based-uncased初始化configuration=BertConfig()# 初始化BertModelmodel=BertModel(configuration)# 获取模型的配置configura...
tokenizer= BertTokenizer.from_pretrained('bert-base-uncased') 我们使用的是tensorflow,所以引入的是TFBertModel。如果有使用pytorch的读者,可以直接引入BertModel。 通过from_pretrained() 方法可以下载指定的预训练好的模型以及分词器,这里我们使用的是bert-base-uncased。前面对bert-based 有过介绍,它包含12个堆叠的...
pytorch 如何在HuggingFace' BertTokenizerFast.from_pretrained(' bert-base-uncased ')中使用最大长度、...
Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.
OSError: Can't load tokenizer for 'bert-base-uncased'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'bert-base-uncased' is the correct path to a directory containing all releva...
model = BertLMHeadModel.from_pretrained('bert-base-uncased', config=config) inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") outputs = model(**inputs) prediction_logits = outputs.logits 1. 2. 3. 4. 5. 6.
convert_single_example函数。可以对一个InputExample转换为InputFeatures,里面调用了tokenizer进行一些句子清洗和预处理工作,同时截断了长度超过最大值的句子。 file_based_convert_example_to_features函数:将一批InputExample转换为InputFeatures,并写入到tfrecord文件中,相当于实现了从原始数据集文件到tfrecord文件的转换。