Transformer is a TensorFlow implementation of the architecture introduced in the Attention Is All You Need paper. It was created as a readable and relatively modular reference for understanding and experimenting with Transformer-based machine translation. The updated implementation corrects issues involving masking, positional encoding, and other parts of the original code. It adds components such as byte-pair encoding and shared weight matrices. Training and evaluation are demonstrated with the IWSLT 2016 German-to-English translation dataset. The repository includes preprocessing, training, inference, evaluation, configurable hyperparameters, pretrained checkpoints, and BLEU-based translation results.
Features
- Transformer attention architecture
- TensorFlow-based implementation
- Byte-pair encoding support
- Shared embedding weight matrices
- Training and inference scripts
- BLEU translation evaluation
Categories
LibrariesLicense
Apache License V2.0Follow transformer
Other Useful Business Software
Veeam Data Platform v13.1 - Get Your Free Trial
Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of transformer!