Hello, I'm tring to train a new tokenizer on my own dataset, here is my code: from tokenizers import Tokenizer from tokenizers.models import BPE from tokenizers.trainers import BpeTrainer unk_token = '<UNK>' spl_tokens = ['<UNK>', '<SEP>...
tokenizer.json already includes all the configurations for the trained tokenizers. I tested usingTokenizer::from_file("tokenizer.json")directly, and the result was the same as that ofload_tokenizer_hf_hub.
AutoTokenizer.from_pretrained:从path/vocab.json中加载tokenizer AutoConfig.from_pretrained:从path/config.json中加载模型配置信息 更新模型配置信息:model = Model(config) PreTrainedModel.from_pretrained:加载模型结构和模型参数 load_checkpoint 从checkpoint 中加载模型 parameter,而不加载模型结构...
路径应该是包含tokenizer所需所有文件的文件夹的绝对路径。 例如,对于BERT tokenizer,你应该有一个包含config.json, pytorch_model.bin, tokenizer.json, tokenizer_config.json,和 vocab.txt等文件的文件夹。然后,你可以使用如下代码加载它: python from transformers import BertTokenizer tokenizer = BertTokenizer.from...
在掌握了Tokenizer的基本使用之后,就可以来做数据集部分的工作了。 数据集部分的工作,一部分在于数据集的收集,另一部分在于数据集的处理。Datasets库的出现,一定程度上也使得这两部分的工作变得简单了许多。 关于datasets库的使用,这里将介绍四部分,分别是Datasets包安装、加载公开数据集、数据集使用方法以及如何加载本地...
TypeError: expected str, bytes or os.PathLike object, not NoneType 参见上文中 OSError: Can't loadtokenizerfor 'openai/clip-vit-large-patch14' 板块,该问题在于程序无法正确读取 vocab_file,极有可能是因为 .json文件后缀在下载后被windows自动改成 .txt 了,改回去即可。
For example, the Llama3.1-8B tokenizer from Meta can be used instead by replacing both references of mistralai/Mixtral-8x7B-v0.1 in the script with the repo ID of the Llama3.1-8B model, meta-llama/Meta-Llama-3.1-8B and update the filename and path to the tokenizer in the model repo...
tokenizer = hanlp.load(‘RADICAL_CHAR_EMBEDDING_100’) 这些load还是会报:找不到:meta.json 具体例如: Traceback (most recent call last): File “”, line 1, in File “C:\Python36\lib\site-packages\hanlp_ init _.py”, line 51, in load return load_from_meta_file(save_dir, meta_file...
words = tokenizer.tokenize(line) w2c.update(words) #这段程序将文件中出现过的所有单词加载到字典类型变量w2c中,并存储了他们出现的次数 for w, c in w2c.items(): if c > 3 and w not in special_tokens: #依次为出现次数大于3,且不是那4种特殊信号的单词分配序号 ...
the tokenizer load makes sure the config.json is downloaded (LanguageModelConfigurationFromHub) this is also used by the model loading (it has the configuration for the model) this has to be run be...