由于代理问题,Huggingface Bert Tokenizer 从源代码构建
Hugginface Bert Tokenizer build from source due to proxy issues
我遇到了类似的情况:
上面的link是关于下载Bert模型本身,但我只想使用Bert Tokenizer。
通常我会这样做:
from transformers import BertTokenizer
bert_tokenizer_en = BertTokenizer.from_pretrained("bert-base-uncased")
bert_tokenizer_de=BertTokenizer.from_pretrained("bert-base-german-cased")
但是我运行它是远程的,所以无法通过上面的方法下载。但我不知道我需要从这里获取哪些文件:https://huggingface.co/bert-base-uncased/tree/main,以便我可以构建分词器?
您需要 1) 下载词汇表和配置文件(vocab.txt
、config.json
),2) 将它们放入文件夹中,以及 3) 将文件夹路径传递给 BertTokenizer.from_pretrained(<path>)
函数.
这里是 vocab.txt
不同分词器型号的下载位置
PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt",
"bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt",
"bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/vocab.txt",
"bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/vocab.txt",
"bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt",
"bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt",
"bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt",
"bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt",
"bert-large-uncased-whole-word-masking": "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt",
"bert-large-cased-whole-word-masking": "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt",
"bert-large-uncased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt",
"bert-large-cased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt",
"bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt",
"bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt",
"bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt",
"TurkuNLP/bert-base-finnish-cased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt",
"TurkuNLP/bert-base-finnish-uncased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt",
"wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt",
}
config.json
的位置:
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
"bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/config.json",
"bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/config.json",
"bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/config.json",
"bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json",
"bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json",
"bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/config.json",
"bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/config.json",
"bert-large-uncased-whole-word-masking": "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json",
"bert-large-cased-whole-word-masking": "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json",
"bert-large-uncased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json",
"bert-large-cased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json",
"bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json",
"bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json",
"bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json",
"cl-tohoku/bert-base-japanese": "https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-whole-word-masking": "https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-char": "https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-char-whole-word-masking": "https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json",
"TurkuNLP/bert-base-finnish-cased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json",
"TurkuNLP/bert-base-finnish-uncased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json",
"wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json",
# See all BERT models at https://huggingface.co/models?filter=bert
}
步骤:
mkdir ~/german-tokenizer
cd german-tokenizer
wget https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt
wget https://huggingface.co/bert-base-german-cased/resolve/main/config.json
python
# Python Runtime:
>> import transformers
>> from transformers import BertTokenizer
>> BertTokenizer.from_pretrained('~/german-tokenizer')
我遇到了类似的情况:
上面的link是关于下载Bert模型本身,但我只想使用Bert Tokenizer。
通常我会这样做:
from transformers import BertTokenizer
bert_tokenizer_en = BertTokenizer.from_pretrained("bert-base-uncased")
bert_tokenizer_de=BertTokenizer.from_pretrained("bert-base-german-cased")
但是我运行它是远程的,所以无法通过上面的方法下载。但我不知道我需要从这里获取哪些文件:https://huggingface.co/bert-base-uncased/tree/main,以便我可以构建分词器?
您需要 1) 下载词汇表和配置文件(vocab.txt
、config.json
),2) 将它们放入文件夹中,以及 3) 将文件夹路径传递给 BertTokenizer.from_pretrained(<path>)
函数.
这里是 vocab.txt
不同分词器型号的下载位置
PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt",
"bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt",
"bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/vocab.txt",
"bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/vocab.txt",
"bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt",
"bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt",
"bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt",
"bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt",
"bert-large-uncased-whole-word-masking": "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt",
"bert-large-cased-whole-word-masking": "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt",
"bert-large-uncased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt",
"bert-large-cased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt",
"bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt",
"bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt",
"bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt",
"TurkuNLP/bert-base-finnish-cased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt",
"TurkuNLP/bert-base-finnish-uncased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt",
"wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt",
}
config.json
的位置:
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
"bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/config.json",
"bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/config.json",
"bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/config.json",
"bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json",
"bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json",
"bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/config.json",
"bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/config.json",
"bert-large-uncased-whole-word-masking": "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json",
"bert-large-cased-whole-word-masking": "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json",
"bert-large-uncased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json",
"bert-large-cased-whole-word-masking-finetuned-squad": "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json",
"bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json",
"bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json",
"bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json",
"cl-tohoku/bert-base-japanese": "https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-whole-word-masking": "https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-char": "https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json",
"cl-tohoku/bert-base-japanese-char-whole-word-masking": "https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json",
"TurkuNLP/bert-base-finnish-cased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json",
"TurkuNLP/bert-base-finnish-uncased-v1": "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json",
"wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json",
# See all BERT models at https://huggingface.co/models?filter=bert
}
步骤:
mkdir ~/german-tokenizer
cd german-tokenizer
wget https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt
wget https://huggingface.co/bert-base-german-cased/resolve/main/config.json
python
# Python Runtime:
>> import transformers
>> from transformers import BertTokenizer
>> BertTokenizer.from_pretrained('~/german-tokenizer')