--- title: Model Architectures teaser: Pre-defined model architectures included with the core library source: spacy/ml/models menu: - ['Tok2Vec', 'tok2vec'] - ['Transformers', 'transformers'] - ['Parser & NER', 'parser'] - ['Text Classification', 'textcat'] - ['Entity Linking', 'entitylinker'] --- TODO: intro and how architectures work, link to [`registry`](/api/top-level#registry), [custom models](/usage/training#custom-models) usage etc. ## Tok2Vec architectures {#tok2vec source="spacy/ml/models/tok2vec.py"} ### spacy.HashEmbedCNN.v1 {#HashEmbedCNN} ### spacy.HashCharEmbedCNN.v1 {#HashCharEmbedCNN} ### spacy.HashCharEmbedBiLSTM.v1 {#HashCharEmbedBiLSTM} ## Transformer architectures {#transformers source="github.com/explosion/spacy-transformers/blob/master/spacy_transformers/architectures.py"} ### spacy-transformers.TransformerModel.v1 {#TransformerModel} ## Parser & NER architectures {#parser source="spacy/ml/models/parser.py"} ### spacy.TransitionBasedParser.v1 {#TransitionBasedParser} > #### Example Config > > ```ini > [model] > @architectures = "spacy.TransitionBasedParser.v1" > nr_feature_tokens = 6 > hidden_width = 64 > maxout_pieces = 2 > > [model.tok2vec] > # ... > ``` | Name | Type | Description | | ------------------- | ------------------------------------------ | ----------- | | `tok2vec` | [`Model`](https://thinc.ai/docs/api-model) | | | `nr_feature_tokens` | int | | | `hidden_width` | int | | | `maxout_pieces` | int | | | `use_upper` | bool | | | `nO` | int | | ## Text classification architectures {#textcat source="spacy/ml/models/textcat.py"} ### spacy.TextCatEnsemble.v1 {#TextCatEnsemble} ### spacy.TextCatBOW.v1 {#TextCatBOW} ### spacy.TextCatCNN.v1 {#TextCatCNN} ### spacy.TextCatLowData.v1 {#TextCatLowData} ## Entity linking architectures {#entitylinker source="spacy/ml/models/entity_linker.py"} ### spacy.EntityLinker.v1 {#EntityLinker}