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This repository was archived by the owner on Jan 15, 2024. It is now read-only.
GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you load the text data,
process the text data, and train models.
First of all, install the MXNet 2 release such as MXNet 2 Alpha. You may use the
following commands:
# Install the version with CUDA 10.2
python3 -m pip install -U --pre "mxnet-cu102>=2.0.0a"# Install the version with CUDA 11
python3 -m pip install -U --pre "mxnet-cu110>=2.0.0a"# Install the cpu-only version
python3 -m pip install -U --pre "mxnet>=2.0.0a"
To install GluonNLP, use
python3 -m pip install -U -e .# Also, you may install all the extra requirements via
python3 -m pip install -U -e ."[extras]"
If you find that you do not have the permission, you can also install to the user folder:
To facilitate both the engineers and researchers, we provide command-line-toolkits for
downloading and processing the NLP datasets. For more details, you may refer to
GluonNLP Datasets and GluonNLP Data Processing Tools.
# CLI for downloading / preparing the dataset
nlp_data help# CLI for accessing some common data processing scripts
nlp_process help# Also, you can use `python -m` to access the toolkits
python3 -m gluonnlp.cli.data help
python3 -m gluonnlp.cli.process help
Run Unittests
You may go to tests to see how to run the unittests.
Use Docker
You can use Docker to launch a JupyterLab development environment with GluonNLP installed.
# GPU Instance
docker pull gluonai/gluon-nlp:gpu-latest
docker run --gpus all --rm -it -p 8888:8888 -p 8787:8787 -p 8786:8786 --shm-size=2g gluonai/gluon-nlp:gpu-latest
# CPU Instance
docker pull gluonai/gluon-nlp:cpu-latest
docker run --rm -it -p 8888:8888 -p 8787:8787 -p 8786:8786 --shm-size=2g gluonai/gluon-nlp:cpu-latest
For more details, you can refer to the guidance in tools/docker.