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Update README.md
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README.md
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README.md
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@ -33,24 +33,18 @@ Extract model archive:
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tar -xzf models.tar.gz
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tar -xzf models.tar.gz
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```
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```
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Copy [config file](qurator/sbb_ner/webapp/config.json) into working directory.
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Set USE_CUDA environment variable to True/False depending on GPU availability.
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Run webapp directly:
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Run webapp directly:
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```
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```
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env FLASK_APP=qurator/sbb_ner/webapp/app.py env FLASK_ENV=development env USE_CUDA=True flask run --host=0.0.0.0
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env CONFIG=config.json env FLASK_APP=qurator/sbb_ner/webapp/app.py env FLASK_ENV=development env USE_CUDA=True/False flask run --host=0.0.0.0
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```
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```
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Set USE_CUDA=False, if you do not have a GPU available/installed.
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For production purposes rather use
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For production purposes rather use
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```
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```
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env USE_CUDA=True/False gunicorn --bind 0.0.0.0:5000 qurator.sbb_ner.webapp.wsgi:app
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env CONFIG=config.json env USE_CUDA=True/False gunicorn --bind 0.0.0.0:5000 qurator.sbb_ner.webapp.wsgi:app
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```
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If you want to use a different model configuration file:
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```
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env USE_CUDA=True/False env CONFIG=`realpath ./my-config.json` gunicorn --bind 0.0.0.0:5000 qurator.sbb_ner.webapp.wsgi:app
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```
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```
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# Docker
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# Docker
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@ -69,7 +63,6 @@ docker run -ti --rm=true --mount type=bind,source=data/konvens2019,target=/usr/s
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Make sure that your GPU is correctly set up and that nvidia-docker has been installed.
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Make sure that your GPU is correctly set up and that nvidia-docker has been installed.
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```
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```
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docker build --build-arg http_proxy=$http_proxy -t qurator/webapp-ner-gpu -f Dockerfile .
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docker build --build-arg http_proxy=$http_proxy -t qurator/webapp-ner-gpu -f Dockerfile .
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```
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```
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