python-ia-markov

Markov chains in golang

Next-token prediction in JavaScript — build fast language and diffusion models.

Code for "A-NICE-MC: Adversarial Training for MCMC"

Traditional Machine Learning Models for Large-Scale Datasets in PyTorch.

An endless version of Erik Satie's Gnossiennes No. 1

A generic markov chain implementation in Rust.

Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)

Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Supervised training supported. Easily extendable with other types of probablistic models.

This repository contains Natural Language Generation (NLG) models aimed on generating text of fairy tales (Markov Chain, LSTM neural network, GPT-2 Transformers).

Self-contained, minimalistic implementation of a language model that generates coherent and normal sounding names. It uses an input dataset of names and probability distribution to generate new names based on the sequences of four characters.