Please provide a barebones "pick up and go" GPT-2 colab notebook for text generation, just like gpt-2-simple does

• [x ] Are you running the latest bert-as-service?
• [x ] Did you follow the installation and the usage instructions in README.md?
• [x ] Did you check the FAQ list in README.md?
• [x ] Did you perform [a cursory searc

The position embedding in the BERT is not the same as in the transformer. Why not use the form in bert?

The main README is completely out-of-date.

We also want to provide documentation in order to prepare for the crate release. This covers the Rust documentation only, not bindings.

Target objective:

Steps to objective:

nlp_architect/models/cross_doc_coref/system/cdc_utils.py

def load_mentions_vocab(mentions_files, filter_stop_words=False):
    logger.info('Loading mentions files...')
    mentions = []
    logger.info('Done loading mentions files, starting local dump creation...')
    for _file in mentions_files:
        mentions.extend(Menti

1. Add CI test for building documentations (Do not ignore warnings and add spellcheck).
2. Fix docstrings with incorrect/inconsistent Sphinx format. Currently, such issues are treated as warnings in the docs building.

e.g. some short methods may contain a description in the return tag, but not a description of the method itself. (to avoid redundancy).

Doing this would extract more methods, but they may be of lower quality if incorrectly parsed or automatically generated. I'd expect a description such as @return bool STARTDESCRIPTION true if this is a float to be extracted (I'm not familiar with how the dat

On home page of website: https://nlp.johnsnowlabs.com/ I read "Full Python, Scala, and Java support"

Unfortunately it's 3 days now I'm trying to use Spark NLP in Java without any success.

• I cannot find Java API (JavaDoc) of the framework.
• not event a single example in Java is available
• I do not know Scala, I do not know how to convert things like:
  val testData = spark.createDataFrame(

can you explain the code where you exactly changed to suit Ner in Bert
I am very much interested ,it will be much helpful.

Ideally, we'd support something like mnli += {pretrain_data_fraction = 0.5}, pretrain_tasks = {mnli,boolq}. Currently, pretrain_data_fraction is just a global argument for all pretraining tasks.

If I want to use both of them, how to modify code in aen.py? Thanks a lot.

Trying to use SpaCy for SQUAD.

name = "bert-large-uncased-whole-word-masking-finetuned-squad"
nlp = TransformersLanguage(trf_name=name, meta={"lang": "en"})
nlp.add_pipe(nlp.create_pipe("sentencizer"))
nlp.add_pipe(TransformersWordPiecer.from_pretrained(nlp.vocab, path))
nlp.add_pipe(TransformersTok2Vec.from_pretrained(nlp.vocab, path))

qa = nlp(question....
[and I need help furt