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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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anomaly-detection | ||
df-analytics/apis | ||
images | ||
trained-models/apis | ||
ml-shared.asciidoc |