The most accurate natural language detection library for Go, suitable for short text and mixed-language text
- natural-language-processing
- language-detection
- language-recognition
- language-classification
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The most accurate natural language detection library for Go, suitable for short text and mixed-language text
Natural language processing framework for Ruby.
Neural question generation using transformers
Pretrained model hub for Keras 3.
Self-contained Japanese Morphological Analyzer written in pure Go
The Classical Language Toolkit
An R package for the Quantitative Analysis of Textual Data
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Java API for Natural Language Generation. Originally developed by Ehud Reiter at the University of Aberdeen’s Department of Computing Science and co-founder of Arria NLG. This git repo is the official SimpleNLG version.
Ruby gem to calculate the similarity between texts using tf*idf
Parse human names into title, given, middle, family, suffix, nickname and maiden name. Typed, zero-dependency, CJK-aware.
A Modern C++ Data Sciences Toolkit
Natural language detection library for Go
Onnx transformer pipelines in Golang
Pragmatic Segmenter is a rule-based sentence boundary detection gem that works out-of-the-box across many languages.
Translated斑海豹 (Spotted Seal) — Phocinae-Largha-150M-v1: a 144.3M bilingual decision model. Tiny model. Big decisions.
RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
CogComp's Natural Language Processing Libraries and Demos: Modules include lemmatizer, ner, pos, prep-srl, quantifier, question type, relation-extraction, similarity, temporal normalizer, tokenizer, transliteration, verb-sense, and more.
Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang
A tool for holistic analysis of language generations systems
A multilingual command line sentence tokenizer in Golang
Simple sentiment analysis with Ruby
An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)