入门: Huggingface模型卡

Question

我最近刚开始研究huggingface转换库。当我尝试开始使用模型卡代码时，例如community model

from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")
model = AutoModel.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")

但是，我得到了以下错误：

Traceback (most recent call last):
  File "test.py", line 2, in <module>
    tokenizer = AutoTokenizer.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")
  File "/Users/Lukas/miniconda3/envs/nlp/lib/python3.7/site-packages/transformers/tokenization_auto.py", line 124, in from_pretrained
    "'xlm', 'roberta', 'ctrl'".format(pretrained_model_name_or_path))
ValueError: Unrecognized model identifier in emilyalsentzer/Bio_ClinicalBERT. Should contains one of 'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', 'xlm', 'roberta', 'ctrl'

如果我尝试一个不同的标记器，比如"baykenney/bert-base-gpt2detector-topp92“，我会得到以下错误：

OSError: Model name 'baykenney/bert-base-gpt2detector-topp92' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased). We assumed 'baykenney/bert-base-gpt2detector-topp92' was a path or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.

开始的时候我错过了什么吗？我觉得模型卡片表明这三行代码应该足以开始使用。

我使用的是Python3.7和转换器库版本2.1.1和pytorch1.5。

Answer 1

请将您的transformers库至少更新到2.4.0。您应该创建一个新的conda环境，并使用pip直接从pypi安装所有包，以获得最新版本(当前为2.11.0)。