Addon to Django apps that allows to retrain Spacy NER with active learning.
Project description
Django app that uses active learning (deliberately picking the examples to annotate) to retrain the spacy NER module more effectively.
Prerequisites
For spacyal to run you need a working Celery installation. Something along the lines of:
from __future__ import absolute_import, unicode_literals import os from celery import Celery app = Celery('tasks') # Using a string here means the worker doesn't have to serialize # the configuration object to child processes. # - namespace='CELERY' means all celery-related configuration keys # should have a `CELERY_` prefix. app.config_from_object('django.conf:settings', namespace='CELERY') # Load task modules from all registered Django app configs. app.autodiscover_tasks() @app.task(bind=True) def debug_task(self): print('Request: {0!r}'.format(self.request))
Installation
Install the package
include spacyal.urls and spacyal.api_urls in your main url definition
ensure that you have a base temnplate called base.html
run python manage.py makemigrations spacyal
run python manage.py migrate
and you should be good to go
Project details
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acdh-spacyal-0.2.18.tar.gz
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