From_preset()
from_preset() is a constructor that loads a pretrained model and its associated configuration, weights, and tokenizer assets from a named preset.
Deep Learning with R, Third Edition
from_preset() is a KerasHub constructor that loads a pretrained model together with its configuration, weights, and tokenizer assets.
- How it is used
- Loads compatible pretrained model components for language modeling and image feature extraction.
- How deep it goes
- Defines the constructor and demonstrates tokenizer, backbone, preprocessing, and freezing, without explaining checkpoint internals.
- Examples
- Uses RoBERTa text loading and Xception image loading, preprocessing, feature extraction, and frozen-backbone classification.
- What you can do after
- Apply it via KerasHub to instantiate pretrained tokenizers, backbones, and preprocessing layers from named presets.
Read how Deep Learning with R, Third Edition explains from_preset() →
Deep Learning with Python, Third Edition
A constructor used to load a pretrained model’s weights, configuration, and tokenizer assets from a preset.
- How it is used
- Loads pretrained KerasHub components for language modeling or image feature extraction without recreating their implementation.
- How deep it goes
- Explains constructor behavior and practical pairing, but stops short of preset-file formats or asset-resolution internals.
- Examples
- Uses RoBERTa tokenization, RoBERTa backbone loading, Xception feature extraction, and frozen convolutional bases.
- What you can do after
- Apply it via KerasHub to load pretrained backbones, tokenizers, and preprocessing components for downstream models.
Read how Deep Learning with Python, Third Edition explains from_preset() →
Related concepts
- KerasHubused by · KerasHub is a Keras library providing reusable components, pretrained models, and utilities for machine-learning and generative-modeling tasks.
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