Many models have identical implementations of prune_heads it would be nice to store that implementation as a method on PretrainedModel and reduce the redundancy.

When you look at the variables in the pretrained base uncased BERT the varibles look like list 1. When you do the training from scratch, 2 additional variables per layer are introduced, with suffixes adam_m and adam_v. It would be nice for someone to explain what these variables are? and what is their significance to the process of training?
If one were to manually initialize variables from a pri

Prerequisites

Please fill in by replacing [ ] with [x].

• Are you running the latest bert-as-service?
• Did you follow the installation and the usage instructions in README.md?
• Did you check the [FAQ list in README.md](https://github.com/hanxiao/bert-as-se

Is your feature request related to a problem? Please describe.
Other related issues: #408 #251
I trained a Chinese model for spaCy, linked it to [spacy's package folder]/data/zh (using spacy link) and want to use that for ludwig. However, when I tried to set the config for ludwig, I received an error, which tell me that there is no way to load the Chinese model.

ValueError: Key ch

Description

Add a ReadMe file in the GitHub folder.
Explain usage of the Templates

Other Comments

Principles of NLP Documentation
Each landing page at the folder level should have a ReadMe which explains -
○ Summary of what this folder offers.
○ Why and how it benefits users
○ As applicable - Documentation of using it, brief description etc
Scenarios folder:
○

Spacy has customizable word level tokenizers with rules for multiple languages. I think porting that to rust would add nicely to this package. Having a customizable uniform word level tokenization across platforms (client web, server) and languages would be beneficial. Currently, idk any clean way or whether it's even possible to write bindings for spacy cython.

Spacy Tokenizer Code

https:

Run the code:

(use-modules
 (opencog)
 (opencog nlp)
 (opencog nlp relex2logic)
 (opencog ghost)
 (opencog ghost procedures)
 (opencog exec))

(define-public (where-somebody-work who-list)
 (display (string-append "argument: " (cog-name (car (cog-outgoing-set who-list))) "\n"))
 (Word "SomeCompany"))

;; Ghost Rules
(ghost-parse "
r: (where do _* work) '_0 work in ^where-

Parsing raw wiki text into structured format is hard, especially handling wiki documents that are not well-formed. This issue is for tracking problematic cases where the extraction is wrong or missing.

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(

Hi,
When we try to tokenize the following sentence:

If we use spacy

a = spacy.load('en_core_web_lg')

doc = a("I like the link http://www.idph.iowa.gov/ohds/oral-health-center/coordinator")

list(doc)

We got

[I, like, the, link, http://www.idph.iowa.gov, /, ohds, /, oral, -, health, -, center, /, coordinator]

But if we use the Spacy transformer tokenizer:

https://github.com/JayParks/tf-seq2seq/blob/master/seq2seq_model.py#L368
It gives that the dimension 0 of inputs and attention do not match (as we are tile_batching it to batch_size * beam_width). Didn't you get any error while running with beam_search?

HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization
Xingxing Zhang, Furu Wei, Ming Zhou
to appear in ACL 2019
https://arxiv.org/abs/1905.06566

Quite a few issues or offers of patches seem to be related to people wanting to do "developer access token" requests, as opposed to "client access token" requests.

Although you mention the word "client" in the name of the repo and as one of the class names, it could easily be mistaken as merely the opposite of "server" rather than the opposite of "developer". Would it be possible to add a sente