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spaCy

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spaCy is a free library for advanced Natural Language Processing (NLP) in Python. It’s designed specifically for production use and helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems.

Here are 1,112 public repositories matching this topic...

rasa

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

  • Updated Jun 7, 2022
  • Python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

  • Updated Oct 1, 2020
  • Jupyter Notebook
DayalStrub
DayalStrub commented Jul 7, 2021

Intro

I am getting TypeError: can not serialize 'BaseTextRank' object when trying to use spaCy's multiprocessing in nlp.pipe with a textrank pipeline component.

Sorry if this a known/expected feature/limitation - I couldn't find anything by searching repo. I generally find (spaCy's) multiprocessing a bit temperamental anyhow, but this seems to just not work.

_PS. thanks for all

bug enhancement help wanted good first issue
text-analytics-with-python

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

  • Updated Dec 24, 2020
  • Jupyter Notebook
keithrozario
keithrozario commented Feb 6, 2021

Hey guys,

I recently switched jobs, and a bit busy these days, and for some reason the volume of issues/requests has increased slightly over the last few weeks.

I'm looking for someone to help me manage the repo, verify pull requests, answer some issues? All I can offer is your name somewhere in the readme (and a coffee/beer if you're in Singapore !)

If you're interested let me know, it'

good first issue
rubrix
frascuchon
frascuchon commented Oct 18, 2021

The default RubrixLogHTTPMiddleware record mapper for token classification expect a structured including a text field for inputs. This could make prediction model inputs a bit cumbersome. Default mapper could accepts also flat strings as inputs:

def token_classification_mapper(inputs, outputs):
    i
good first issue help wanted