Text Tutorials¶

These tutorials will help you learn how to create and use models that work with text and other natural language processing tasks.

Word Embedding¶

Pre-trained Word Embeddings

Basics on how to use word embedding with vocab in GluonNLP and apply it on word similarity and analogy problems.

Word Embeddings Training and Evaluation

Learn how to train fastText and word2vec embeddings on your own dataset, and determine embedding quality through intrinsic evaluation.

LSTM-based Language Models

Learn what a language model is, what it can do, and how to train a word-level language model with truncated back-propagation-through-time (BPTT).

Google Neural Machine Translation

Learn how to train Google Neural Machine Translation, a seq2seq with attention model.

Machine Translation with Transformer

Learn how to use a pre-trained transformer translation model for English to German translation.

ELMo: Deep Contextualized Word Representations

See how to use GluonNLP’s model API to automatically download the pre-trained ELMo model from NAACL2018 best paper, and extract features with it.

A Structured Self-attentive Sentence Embedding

See how to use GluonNLP to build more advanced model structure for extracting sentence embeddings to predict Yelp review rating.

BERT: Bidirectional Encoder Representations from Transformers

See how to use GluonNLP to fine-tune a sentence pair classification model with pre-trained BERT parameters.

Sentiment Analysis by Fine-tuning Word Language Model

See how to fine-tune a pre-trained language model to perform sentiment analysis on movie reviews.

Sequence Generation with Sampling and Beam Search

Learn how to generate sentence from pre-trained language model through sampling and beam search.

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