SpaCy: Difference between revisions
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The preferred option is to install it using the python [https://pythonwheels.com/ wheel] that we compile, as follows: | The preferred option is to install it using the python [https://pythonwheels.com/ wheel] that we compile, as follows: | ||
:1. Load | :1. Load python 3.6 module: <tt>python/3.6</tt> | ||
:2. Create and start a [[Python#Creating_and_using_a_virtual_environment|virtual environment]]. | :2. Create and start a [[Python#Creating_and_using_a_virtual_environment|virtual environment]]. | ||
:3. Install <tt>spaCy</tt> in the virtual environment with <code>pip install</code>. For both GPU and CPU support: | :3. Install <tt>spaCy</tt> in the virtual environment with <code>pip install</code>. For both GPU and CPU support: |
Revision as of 15:54, 13 November 2018
spaCy is a Python package that provides industrial-strength natural language processing.
Installation
Latest available wheels
To see the latest version of spaCy that we have built:
[name@server ~]$ avail_wheels spacy thinc thinc_gpu_ops
For more information on listing wheels, see listing available wheels.
Pre-build
The preferred option is to install it using the python wheel that we compile, as follows:
- 1. Load python 3.6 module: python/3.6
- 2. Create and start a virtual environment.
- 3. Install spaCy in the virtual environment with
pip install
. For both GPU and CPU support: -
(venv) [name@server ~] pip install spacy[cuda] --no-index
- If you only need CPU support:
-
(venv) [name@server ~] pip install spacy --no-index
GPU version: for the moment, you need to point out where the CUDA libraries live:
(venv) [name@server ~] module load gcc/5.4.0 cuda/9
(venv) [name@server ~] export LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH
Note: if you want to use thinc Pytorch wrapper, you'll also need to install torch_cpu or torch_gpu wheel.