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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.
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
tiktoken is a fast BPE tokeniser for use with OpenAI's models.
Topic Modelling for Humans
Pretrained models for TensorFlow.js
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Open-source offline translation library written in Python
Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining
A full spaCy pipeline and models for scientific/biomedical documents.
Self-contained Machine Learning and Natural Language Processing library in Go
The most accurate natural language detection library for Go, suitable for short text and mixed-language text
Pretrained model hub for Keras 3.
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.
A Modern C++ Data Sciences Toolkit
Translated斑海豹 (Spotted Seal) — Phocinae-Largha-150M-v1: a 144.3M bilingual decision model. Tiny model. Big decisions.
Implementation of various topic models
Natural language detection package in pure Go
This repository is a proof of concept toolbox for using Deep Belief Nets for Topic Modeling in Python.
An NLP library for Uralic languages such as Finnish, Skolt Sami, Moksha and so on. Also supporting some non-Uralic languages such as Spanish, French, Arabic, Swedish, Norwegian, Russian and English. LLMs, FSTs and More!
A flexible and general-purpose ngrams library written in Ruby. Raingrams supports ngram sizes greater than 1, text/non-text grams, multiple parsing styles and open/closed vocabulary models.
Swift framework for document classification using a Core ML model.