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