  [nlp]
  lang = "en"
  vectors = null
  
  [nlp.pipeline.tok2vec]
  factory = "tok2vec"
  
  [nlp.pipeline.tok2vec.model]
  @architectures = "spacy.Tok2Vec.v1"
  
  [nlp.pipeline.tok2vec.model.extract]
  @architectures = "spacy.Doc2Feats.v1"
  columns = ["ID", "NORM", "PREFIX", "SUFFIX", "SHAPE", "ORTH"]
  
  [nlp.pipeline.tok2vec.model.embed]
  @architectures = "spacy.MultiHashEmbed.v1"
  columns = ${nlp.pipeline.tok2vec.model.extract:columns}
  width = 96
  rows = 2000
  use_subwords = true
  pretrained_vectors = null
  
  [nlp.pipeline.tok2vec.model.embed.mix]
  @architectures = "spacy.LayerNormalizedMaxout.v1"
  width = ${nlp.pipeline.tok2vec.model.embed:width}
  maxout_pieces = 3
  
  [nlp.pipeline.tok2vec.model.encode]
  @architectures = "spacy.MaxoutWindowEncoder.v1"
  width = ${nlp.pipeline.tok2vec.model.embed:width}
  window_size = 1
  maxout_pieces = 3
  depth = 2
  
  [nlp.pipeline.ner]
  factory = "ner"
  
  [nlp.pipeline.ner.model]
  @architectures = "spacy.TransitionBasedParser.v1"
 
</s> remove @architectures = "spacy.Tok2VecTensors.v1"
width = ${nlp.pipeline.tok2vec.model.embed:width}
 </s> add @architectures = "spacy.HashEmbedCNN.v1"
width = 128
depth = 4
embed_size = 7000
maxout_pieces = 3
window_size = 1
subword_features = true
pretrained_vectors = null </s> remove @architectures = "spacy.TransitionBasedParser.v1"
nr_feature_tokens = 6
hidden_width = 64
maxout_pieces = 2
 </s> add @architectures = "spacy.BiluoTagger.v1" </s> remove factory = "ner"
 </s> add factory = "simple_ner" </s> remove batch_size = 25
 </s> add [training.batch_size]
@schedules = "compounding.v1"
start = 3000
stop = 3000
compound = 1.001
 </s> remove scores = ["ents_f"]
 </s> add scores = ["ents_p", "ents_r", "ents_f"]
  [nlp]
  lang = "en"
  vectors = null
  






























  [nlp.pipeline.ner]
  factory = "ner"
  
  [nlp.pipeline.ner.model]
  @architectures = "spacy.TransitionBasedParser.v1"
keep keep keep keep replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 Adapt parser and NER for transformers (#5449)

* Draft layer for BILUO actions

* Fixes to biluo layer

* WIP on BILUO layer

* Add tests for BILUO layer

* Format

* Fix transitions

* Update test

* Link in the simple_ner

* Update BILUO tagger

* Update __init__

* Import simple_ner

* Update test

* Import

* Add files

* Add config

* Fix label passing for BILUO and tagger

* Fix label handling for simple_ner component

* Update simple NER test

* Update config

* Hack train script

* Update BILUO layer

* Fix SimpleNER component

* Update train_from_config

* Add biluo_to_iob helper

* Add IOB layer

* Add IOBTagger model

* Update biluo layer

* Update SimpleNER tagger

* Update BILUO

* Read random seed in train-from-config

* Update use of normal_init

* Fix normalization of gradient in SimpleNER

* Update IOBTagger

* Remove print

* Tweak masking in BILUO

* Add dropout in SimpleNER

* Update thinc

* Tidy up simple_ner

* Fix biluo model

* Unhack train-from-config

* Update setup.cfg and requirements

* Add tb_framework.py for parser model

* Try to avoid memory leak in BILUO

* Move ParserModel into spacy.ml, avoid need for subclass.

* Use updated parser model

* Remove incorrect call to model.initializre in PrecomputableAffine

* Update parser model

* Avoid divide by zero in tagger

* Add extra dropout layer in tagger

* Refine minibatch_by_words function to avoid oom

* Fix parser model after refactor

* Try to avoid div-by-zero in SimpleNER

* Fix infinite loop in minibatch_by_words

* Use SequenceCategoricalCrossentropy in Tagger

* Fix parser model when hidden layer

* Remove extra dropout from tagger

* Add extra nan check in tagger

* Fix thinc version

* Update tests and imports

* Fix test

* Update test

* Update tests

* Fix tests

* Fix test

Co-authored-by: Ines Montani <ines@ines.io> 
examples/experiments/tok2vec-ner/multihashembed_tok2vec.cfg