Part 2: Abstractions, Design, and Testing
Representing text as features: Tokenizers, TextFields, and TextFieldEmbedders
A deep dive into AllenNLP's core abstraction: how exactly we represent textual inputs, both on the data side and the model side.
1Language to features
2Tokenizers and TextFields
3TokenIndexers
4The model side: TextFieldEmbedders
5Coordinating the three parts
6Using pretrained contextualizers and embeddings
7Doing word-level modeling with a wordpiece transformer
8How padding and masking works
9Interacting with TextField outputs in your model code
10How to upload transformer weights and tokenizers to HuggingFace
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See the
↩BucketBatchSamplerfor AllenNLP's built-in way to organize batches