This commit adds support for MPNet based models. MPNet models differ from BERT style models in that: - Special tokens are different - Input to the model doesn't require token positions. To configure an MPNet tokenizer for your pytorch MPNet based model: ``` "tokenization": { "mpnet": {...} } ``` The options provided to `mpnet` are the same as the previously supported `bert` configuration. |
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delete-trained-models-aliases.asciidoc | ||
delete-trained-models.asciidoc | ||
get-trained-models-stats.asciidoc | ||
get-trained-models.asciidoc | ||
index.asciidoc | ||
infer-trained-model-deployment.asciidoc | ||
ml-trained-models-apis.asciidoc | ||
put-trained-model-definition-part.asciidoc | ||
put-trained-model-vocabulary.asciidoc | ||
put-trained-models-aliases.asciidoc | ||
put-trained-models.asciidoc | ||
start-trained-model-deployment.asciidoc | ||
stop-trained-model-deployment.asciidoc |