近期在看模型的时候，因为README.md文件里涉及到了代码，但是markdown文件里代码的变量为Python的关键字str，如下所示，

import time
from bert_base.client import BertClient

with BertClient(show_server_config=False, check_version=False, check_length=False, mode='NER') as bc:
   start_t = time.perf_counter()
   str = '1月24日，新华社对外发布了中央对雄安新区的指导意见，洋洋洒洒1.2万多字，17次提到北京，4次提到天津，信息量很大，其实也回答了人们关心的很多问题。'
   rst = bc.encode([str, str])
   pri

I have prepared my test file containing this 3 lines :

Survey B-DOC
Report I-DOC
Geographic I-DOC

when I make run, I get this error :

default = tags[NONE]
KeyError: 'O'
makefile:7: recipe for target 'run' failed
make: *** [run] Error 1

Could you please help me.

Following the instructions on the grobid site, I cannot embed grobid into my JAVA project due to poor instructions regarding Gradle and Maven. Also, I do not know how to use the APIs because the Java documentation has different parameters for the methods. Specifically, fullTextToTei take in different arguments than what is shown in the Java docs.

usaddress supports the label "CountryName", as can be seen by parsing
123 Cedar Ave Salt Lake City Utah 84105 USA
yet the label "CountryName" is missing from the list of component names in usaddress.readthedocs.io and in README.md.

Hi,

The documentation states that "By using this class it is possible to save some time if the same input sequence is passed to trainers/taggers more than once"; however I am struggling to find any examples of it being used. What is the recommended approach to train and predict with ItemSequence objects?

Many thanks

As of PyTorch 1.1.0, the inputs to pack_padded_sequence do not need to be sorted by length if enforce_sorted=False:

https://pytorch.org/docs/master/nn.html#torch.nn.utils.rnn.pack_padded_sequence

enforce_sorted (bool, optional) – if True, the input is expected to contain sequences sorted by length in a decreasing order. If False, this condition is not checked. Default: True.

Thanks fo