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TranslatedChinese word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, constituency parsing, semantic dependency parsing, semantic role labeling, coreference resolution, style transfer, semantic similarity, new word discovery, keyword and keyphrase extraction, automatic summarization, text classification and clustering, pinyin and Simplified/Traditional Chinese conversion, natural language processing
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
💫 Industrial-strength Natural Language Processing (NLP) in Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Topic Modelling for Humans
Style and Grammar Checker for 25+ Languages
Pretrained models for TensorFlow.js
NLTK Source
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
modest natural-language processing
Unsupervised text tokenizer for Neural Network-based text generation.
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
general natural language facilities for node
CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more
TranslatedChinese characters to pinyin converter (pypinyin)
VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
State of the Art Natural Language Processing
Module for automatic summarization of text documents and HTML pages.
📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.