PyText
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Getting Started

  • Installation
  • Train your first model
  • Execute your first model
  • Visualize Model Training with TensorBoard
  • Use PyText models in your app
  • Serve Models in Production
  • Config Files Explained
  • Config Commands

Training More Advanced Models

  • Train Intent-Slot model on ATIS Dataset
  • Hierarchical intent and slot filling
  • Multitask training with disjoint datasets
  • Data Parallel Distributed Training
  • XLM-RoBERTa
  • Semantic parsing with sequence-to-sequence models

Extending PyText

  • Architecture Overview
  • Custom Data Format
  • Custom Tensorizer
  • Using External Dense Features
  • Creating A New Model
  • Hacking PyText

References

  • pytext
    • config
    • data
      • batch_sampler
      • bert_tensorizer
      • data
      • data_handler
      • dense_retrieval_tensorizer
      • disjoint_multitask_data
      • disjoint_multitask_data_handler
      • dynamic_pooling_batcher
      • featurizer
        • featurizer
        • simple_featurizer
      • packed_lm_data
      • roberta_tensorizer
      • sources
      • squad_for_bert_tensorizer
      • squad_tensorizer
      • tensorizers
      • tokenizers
    • exporters
    • loss
    • metric_reporters
    • models
    • optimizer
    • task
    • torchscript
    • trainers
  • pytext package
PyText
  • Docs »
  • pytext »
  • data »
  • featurizer
  • Edit on GitHub

featurizerΒΆ

  • featurizer
    • Featurizer.Config
  • simple_featurizer
    • SimpleFeaturizer.Config
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