2021-06-14 记事训练seq2seq

2021-06-14 记事 使用 #transformers 的各种模型训练 #seq2seq ，参考这里： 摘要生成 摘要生成核心…

transformers中使用BertTokenizer编码文本

使用BertTokenizer编码文本 ``` from transformers import BertTokenizer, BertModel tokenizer = BertTokenizer.from_pretrained('uer/chinese_roberta_L-2_H-128') model = BertModel.from_pret…

解决add_code_sample_docstrings() got an unexpecte…

``` /opt/conda/lib/python3.7/site-packages/transformers/utils/import_utils.py in __getattr__(self, name) 845 846 # Needed for autocompletion in an IDE --> 847 de…

transformers 在seq2seq 模型中的decoder_input_ids

decoder\_input\_ids 是来自 huggingface 的labels decoder\_input\_ids（可选）对应标签，labels是提供decoder\_input\_ids的首选方式。 这是因为如果 decoder\_input\_ids 为 None，它们将通过将labels向右移动来派生，因此您不必自己进行移动。 …

How to tokenize text data using HuggingFace tok…

To tokenize text data using the HuggingFace tokenizer, you can use the `tokenizer.encode` or `tokenizer.encode_plus` methods, which take a string of text as input and return a lis…

How To pad sequences of tokenized input to equa…

To tokenize text data using the HuggingFace tokenizer, you can use the `Tokenizer` class provided by the transformers library. Here is an example: ``` from transformers import …