Popular GitHub Repositories for Liquid Glass

Liquid: Language Models are Scalable and Unified Multi-modal Generators

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

Glass Keep is Keep Notes alternative using Glass design. Made in React + Tailwind

Live real-time avatars from your webcam in the browser. No dedicated hardware or software installation needed. A pure Google Colab wrapper for live First-order-motion-model, aka Avatarify in the browser. And other Colabs providing an accessible interface for using FOMM, Wav2Lip and Liquid-warping-GAN with your own media and a rich GUI.

Liquid Audio - Speech-to-Speech audio models by Liquid AI

Live-bending a foundation model’s output at neural network level.

An open source implementation of LFMs from Liquid AI: Liquid Foundation Models

This repository hosts a stock market prediction model for Tesla and Apple using Liquid Neural Networks. It showcases data-driven forecasting techniques, feature engineering, and machine learning to enhance the accuracy of financial predictions.

Implementation of Liquid Nets in Pytorch

The Spiking Reservoir (Liquid State Machine - LSM) Simulator

Control of a nonlinear liquid level system using a new artificial neural network based reinforcement learning approach

isingLenzMC: Monte Carlo for Classical Ising Model (with core C library)

SageMaker implementation of liquid neural networks (LNNs) for time series forecasting.

Parallel random matrix tools and complexity for deep learning

Reservoir computing for short-and long-term prediction of chaotic systems, with tasks Lorenz and Mackey-Glass systems. Bayesian optimization (hyperparameter optimization algorithm) is used to tune the hyperparameters and improve the performance.

Sustain-LC is a benchmarking environment for traditional and reinforcement learning based controls as well as LLM based control

Convenient Interface to Inverse Ising (ConIII)

A simple and minimal open source implementation of "Introducing LFM2: The Fastest On-Device Foundation Models on the Market" from Liquid AI in Pytorch

Custom YOLO11m model for detecting and classifying car body damage (99% shattered glass, 96% flat tire detection accuracy)—optimized for high-capacity inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.

A Liquid State Machine using quantized neurons that are operating on lower-bit representations and fixed point computations. It provides a next step towards the implementation of efficient accelerators that can be used in the field of neuromorphic computing.