This is the Linux app named fairseq-lua whose latest release can be downloaded as fairseq-luasourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named fairseq-lua with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS
Ad
fairseq-lua
DESCRIPTION
fairseq-lua is the original Lua/Torch7 version of Facebook AI Research’s sequence modeling toolkit, designed for neural machine translation (NMT) and sequence generation. It introduced early attention-based architectures and training pipelines that later evolved into the modern PyTorch-based fairseq. The framework implements sequence-to-sequence models with attention, beam search decoding, and distributed training, providing a research platform for exploring translation, summarization, and language modeling. Its modular design made it easy to prototype new architectures by modifying encoders, decoders, or attention mechanisms. Although now deprecated in favor of the PyTorch rewrite, fairseq-lua played a key role in advancing large-scale NMT systems, such as early versions of Facebook’s production translation models. It remains an important historical reference for neural sequence learning frameworks.
Features
- Sequence-to-sequence architecture with attention mechanism
- Beam search decoding for accurate translation outputs
- Multi-GPU training and distributed parallelization
- Modular design for custom encoder–decoder experiments
- Support for translation, summarization, and language modeling tasks
- Historical foundation for the PyTorch-based fairseq framework
Programming Language
Lua
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/fairseq-lua.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
