OpenNMT-py
  • Overview
  • بداية سريعة
  • Doc: Framework
  • Doc: Modules
  • Doc: Translation
  • Doc: Data Loaders
  • Library: Example
  • Options: preprocess.py:
  • Options: train.py:
  • Options: translate.py:
  • Example: Translation
  • Example: Summarization
  • Example: Image to Text
  • Example: Speech to Text
  • اسئلة متكررة 
  • Contributors
  • References
OpenNMT-py
  • Docs »
  • Contents
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Contents¶

  • Overview
    • التركيب
    • Citation
    • Additional resources
  • بداية سريعة
    • الخطوة 1: Preprocess the data
    • الخطوة 2: تدريب النموذج 
    • الخطوة 3: الترجمة
  • Doc: Framework
    • Model
    • Trainer
    • Loss
    • Optim
  • Doc: Modules
    • Core Modules
    • Encoders
    • Decoders
    • Attention
    • Architecture: Transfomer
    • Architecture: Conv2Conv
    • Architecture: SRU
    • Alternative Encoders
    • Copy Attention
    • Structured Attention
  • Doc: Translation
    • Translations
    • Translator Class
    • Beam Search
  • Doc: Data Loaders
    • Datasets
  • Library: Example
  • Options: preprocess.py:
    • Data:
    • Vocab:
    • Pruning:
    • Random:
    • Logging:
    • Speech:
  • Options: train.py:
    • Model-Embeddings:
    • Model-Embedding Features:
    • Model- Encoder-Decoder:
    • Model- Attention:
    • General:
    • Initialization:
    • Optimization- Type:
    • Optimization- Rate:
    • Logging:
    • Speech:
  • Options: translate.py:
    • Model:
    • Data:
    • Beam:
    • Logging:
    • Efficiency:
    • Speech:
  • Example: Translation
  • Example: Summarization
    • Preprocessing the data
    • Training
    • Inference
    • Evaluation
    • Scores and Models
    • References
  • Example: Image to Text
    • Dependencies
    • Quick Start
    • Options
  • Example: Speech to Text
    • Dependencies
    • Quick Start
    • Options
    • Acknowledgement
  • اسئلة متكررة 
    • How do I use Pretrained embeddings (e.g. GloVe)?
    • How do I use the Transformer model?
    • Do you support multi-gpu?
  • Contributors
  • References
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