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Merge branch 'website/curated-docs' of github.com:vin-ivar/spaCy into pr/vin-ivar/12677

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@ -497,10 +497,10 @@ Construct an ALBERT transformer model.
| `vocab_size` | Vocabulary size. ~~int~~ |
| `with_spans` | Callback that constructs a span generator model. ~~Callable~~ |
| `piece_encoder` | The piece encoder to segment input tokens. ~~Model~~ |
| `attention_probs_dropout_prob` | Dropout probabilty of the self-attention layers. ~~float~~ |
| `attention_probs_dropout_prob` | Dropout probability of the self-attention layers. ~~float~~ |
| `embedding_width` | Width of the embedding representations. ~~int~~ |
| `hidden_act` | Activation used by the point-wise feed-forward layers. ~~str~~ |
| `hidden_dropout_prob` | Dropout probabilty of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_dropout_prob` | Dropout probability of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_width` | Width of the final representations. ~~int~~ |
| `intermediate_width` | Width of the intermediate projection layer in the point-wise feed-forward layer. ~~int~~ |
| `layer_norm_eps` | Epsilon for layer normalization. ~~float~~ |
@ -524,9 +524,9 @@ Construct a BERT transformer model.
| `vocab_size` | Vocabulary size. ~~int~~ |
| `with_spans` | Callback that constructs a span generator model. ~~Callable~~ |
| `piece_encoder` | The piece encoder to segment input tokens. ~~Model~~ |
| `attention_probs_dropout_prob` | Dropout probabilty of the self-attention layers. ~~float~~ |
| `attention_probs_dropout_prob` | Dropout probability of the self-attention layers. ~~float~~ |
| `hidden_act` | Activation used by the point-wise feed-forward layers. ~~str~~ |
| `hidden_dropout_prob` | Dropout probabilty of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_dropout_prob` | Dropout probability of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_width` | Width of the final representations. ~~int~~ |
| `intermediate_width` | Width of the intermediate projection layer in the point-wise feed-forward layer. ~~int~~ |
| `layer_norm_eps` | Epsilon for layer normalization. ~~float~~ |
@ -549,9 +549,9 @@ Construct a CamemBERT transformer model.
| `vocab_size` | Vocabulary size. ~~int~~ |
| `with_spans` | Callback that constructs a span generator model. ~~Callable~~ |
| `piece_encoder` | The piece encoder to segment input tokens. ~~Model~~ |
| `attention_probs_dropout_prob` | Dropout probabilty of the self-attention layers. ~~float~~ |
| `attention_probs_dropout_prob` | Dropout probability of the self-attention layers. ~~float~~ |
| `hidden_act` | Activation used by the point-wise feed-forward layers. ~~str~~ |
| `hidden_dropout_prob` | Dropout probabilty of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_dropout_prob` | Dropout probability of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_width` | Width of the final representations. ~~int~~ |
| `intermediate_width` | Width of the intermediate projection layer in the point-wise feed-forward layer. ~~int~~ |
| `layer_norm_eps` | Epsilon for layer normalization. ~~float~~ |
@ -574,9 +574,9 @@ Construct a RoBERTa transformer model.
| `vocab_size` | Vocabulary size. ~~int~~ |
| `with_spans` | Callback that constructs a span generator model. ~~Callable~~ |
| `piece_encoder` | The piece encoder to segment input tokens. ~~Model~~ |
| `attention_probs_dropout_prob` | Dropout probabilty of the self-attention layers. ~~float~~ |
| `attention_probs_dropout_prob` | Dropout probability of the self-attention layers. ~~float~~ |
| `hidden_act` | Activation used by the point-wise feed-forward layers. ~~str~~ |
| `hidden_dropout_prob` | Dropout probabilty of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_dropout_prob` | Dropout probability of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_width` | Width of the final representations. ~~int~~ |
| `intermediate_width` | Width of the intermediate projection layer in the point-wise feed-forward layer. ~~int~~ |
| `layer_norm_eps` | Epsilon for layer normalization. ~~float~~ |
@ -599,9 +599,9 @@ Construct a XLM-RoBERTa transformer model.
| `vocab_size` | Vocabulary size. ~~int~~ |
| `with_spans` | Callback that constructs a span generator model. ~~Callable~~ |
| `piece_encoder` | The piece encoder to segment input tokens. ~~Model~~ |
| `attention_probs_dropout_prob` | Dropout probabilty of the self-attention layers. ~~float~~ |
| `attention_probs_dropout_prob` | Dropout probability of the self-attention layers. ~~float~~ |
| `hidden_act` | Activation used by the point-wise feed-forward layers. ~~str~~ |
| `hidden_dropout_prob` | Dropout probabilty of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_dropout_prob` | Dropout probability of the point-wise feed-forward and embedding layers. ~~float~~ |
| `hidden_width` | Width of the final representations. ~~int~~ |
| `intermediate_width` | Width of the intermediate projection layer in the point-wise feed-forward layer. ~~int~~ |
| `layer_norm_eps` | Epsilon for layer normalization. ~~float~~ |
@ -632,7 +632,7 @@ weighted representation of the same.
Construct a listener layer that communicates with one or more upstream
Transformer components. This layer extracts the output of the last transformer
layer and performs pooling over the individual pieces of each Doc token,
layer and performs pooling over the individual pieces of each `Doc` token,
returning their corresponding representations. The upstream name should either
be the wildcard string '\*', or the name of the Transformer component.
@ -644,7 +644,7 @@ with more than one Transformer component in the pipeline.
| Name | Description |
| --------------- | ---------------------------------------------------------------------------------------------------------------------- |
| `layers` | The the number of layers produced by the upstream transformer component, excluding the embedding layer. ~~int~~ |
| `layers` | The number of layers produced by the upstream transformer component, excluding the embedding layer. ~~int~~ |
| `width` | The width of the vectors produced by the upstream transformer component. ~~int~~ |
| `pooling` | Model that is used to perform pooling over the piece representations. ~~Model~~ |
| `upstream_name` | A string to identify the 'upstream' Transformer component to communicate with. ~~str~~ |