OpenNMT-py

Getting Started

  • Overview
  • Краткое руководство
  • Вопросы и ответы
  • Contributors
  • References

Examples

  • Library
  • Translation
  • Summarization
  • Image to Text
  • Speech to Text

Scripts

  • Preprocess
  • Train
  • Translate
  • Server

API

  • Framework
  • Modules
  • Translation
  • Server
  • Data Loaders
OpenNMT-py
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Contents¶

Getting Started

  • Overview
    • Installation
    • Citation
    • Additional resources
  • Краткое руководство
    • Step 1: Preprocess the data
    • Step 2: Train the model
    • Step 3: Translate
  • Вопросы и ответы
    • How do I use Pretrained embeddings (e.g. GloVe)?
    • How do I use the Transformer model? Do you support multi-gpu?
    • How can I ensemble Models at inference?
  • Contributors
    • Guidelines
  • References

Examples

  • Library
  • Translation
  • Summarization
    • Preprocessing the data
    • Training
    • Inference
    • Evaluation
    • Scores and Models
    • References
  • Image to Text
    • Dependencies
    • Quick Start
    • Options
  • Speech to Text
    • Dependencies
    • Quick Start
    • Options
    • Acknowledgement

Scripts

  • Preprocess
    • Named Arguments
    • Data
    • Vocab
    • Pruning
    • Random
    • Logging
    • Speech
  • Train
    • Named Arguments
    • Model-Embeddings
    • Model-Embedding Features
    • Model- Encoder-Decoder
    • Model- Attention
    • General
    • Initialization
    • Optimization- Type
    • Optimization- Rate
    • Logging
    • Speech
  • Translate
    • Named Arguments
    • Model
    • Data
    • Random Sampling
    • Beam
    • Logging
    • Efficiency
    • Speech
  • Server
    • Named Arguments

API

  • Framework
    • Model
    • Trainer
    • Loss
    • Optimizer
  • Modules
    • Core Modules
    • Encoders
    • Decoders
    • Attention
    • Architecture: Transfomer
    • Architecture: Conv2Conv
    • Architecture: SRU
    • Alternative Encoders
    • Copy Attention
    • Structured Attention
  • Translation
    • Translations
    • Translator Class
    • Decoding Strategies
    • Scoring
  • Server
    • Models
    • Core Server
  • Data Loaders
    • Data Readers
    • Dataset
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