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Young's Sequence-Sequence Research Toolkit Extended on FAIRSeq

Project description

For fairseq software

Copyright (c) 2017-present, Facebook, Inc. All rights reserved.

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Description:

# YoungSeq Young’s Sequence-Sequence Research Toolkit Extended on FAIRSeq

### Preparation #### Requirements: * A [PyTorch installation](http://pytorch.org/) * For training new models, you’ll also need an NVIDIA GPU and [NCCL](https://github.com/NVIDIA/nccl) * Python version 3.6

Currently YoungSeq and FAIRSeq requires PyTorch version >= 1.0.0. Please follow the instructions here: https://github.com/pytorch/pytorch#installation.

If you use Docker make sure to increase the shared memory size either with –ipc=host or –shm-size as command line options to nvidia-docker run.

#### Install FAIRSeq: ` pip install fairseq `

#### Install YoungSeq: 1. Install from PyPi ` pip install youngseq ` 2. Install from source ` https://github.com/Jason-Young-NLP/YoungSeq.git cd youngseq pip install --editable . `

### Experiments ` 1. youngseq-document-preprocess 2. youngseq-document-train 3. youngseq-document-generate `

Platform: UNKNOWN Classifier: Intended Audience :: Science/Research Classifier: Programming Language :: Python :: 3 Classifier: License :: OSI Approved :: Apache Software License Classifier: Operating System :: OS Independent Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence Description-Content-Type: text/markdown

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