需要在训练开始前,修改llm_train/AscendSpeed/yi/3_training.sh文件,并添加--tokenizer-not-use-fast参数。修改后如图1所示。 图1 修改Yi 模型3_training.sh文件 上一篇:AI开发平台MODELARTS-训练tokenizer文件说明:ChatGLMv3-6B 下一篇:AI开发平台MODELARTS-训练的权重转换说明:用户自定义执行权重转换参数修改说明...
需要在训练开始前,修改llm_train/AscendSpeed/yi/3_training.sh文件,并添加--tokenizer-not-use-fast参数。修改后如图1所示。 图1 修改Yi 模型3_training.sh文件 ChatGLMv3-6B 在训练开始前,针对ChatGLMv3-6B模型中的tokenizer文件,需要修改代码。修改文件chatglm3-6b/tokenization_chatglm.py 。 文件最后几...
tokenizer_not_use_fast ... False tokenizer_padding_side ... right tokenizer_type ... PretrainedFromHF top_k ... 50 top_p ... 0.9 tp_comm_bulk_dgrad ...
use_fast_tokenizer是一个布尔值参数,用于指定是否使用快速的tokenizer。在某些情况下,使用快速的tokenizer可以加快模型训练和推理速度。 其原理主要在于快速tokenizer的设计和实现方式。一般来说,传统的tokenizer需要进行复杂的词法分析,逐字符或逐词进行解析和编码,这个过程可能会消耗较多的计算资源。而快速tokenizer则采用了...
* :obj:`False` or :obj:`'do_not_truncate'` (default): No truncation (i.e., can output batch with sequence lengths greater than the model maximum admissible input size). max_length (:obj:`int`, `optional`): Controls the maximum length to use by one of the truncation/padding paramete...
构造Tokenizer 时,可以通过传入use_fast=False强制构造 Slow Tokenizer # 设置 use_fast=False 来构造 SlowTokenizer slow_tokenizer = AutoTokenizer.from_pretrained("uer/roberta-base-finetuned-dianping-chinese", use_fast=False) slow_tokenizer # 类型名无后缀 Fast ...
Prefer not to use FastTokenizer even it is available. (When you want to load TokenizerFast through AutoTokenizer, you should explicitly set use_fast=True ) Use LazyMapping to load keys and values when it is accessed. Modify tests/transformers/test_modeling_common.py to support LlamaTokenizerFas...
# if we removed everything like smiles `:)`, use the whole text as 1 token if not words: words = [text] # the ._convert_words_to_tokens() method is from the parent class. tokens = self._convert_words_to_tokens(words, text) ...
False means it’s not but [SEP] will be appended, None means it dependents on input[-1] == [EOS]. do_basic_tokenize –Whether to do basic tokenization before wordpiece. use_fast –Whether or not to try to load the fast version of the tokenizer. dict_force –A dictionary doing ...
当前行为 | Current Behavior 准备将本地词表合并到Qwen的词表,但是发现Qwen tokenizer无论是fast还是普通的use_fast=False,也就是tokenization_qwen2.py和tokenization_qwen2_fast.py,均不支持“sp_model”,导入报错: 1.AttributeError: 'Qwen2Tokenizer' object has