Universal LLM Deployment Engine with ML Compilation
- llm
- machine-learning-compilation
- language-model
- tvm
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Universal LLM Deployment Engine with ML Compilation
High-performance In-browser LLM Inference Engine
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
LIBSVM -- A Library for Support Vector Machines
Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
ThunderSVM: A Fast SVM Library on GPUs and CPUs
A research toolkit for particle swarm optimization in Python
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
DotRecast - a C# port of Recast & Detour, Industry-standard navigation mesh toolset for .NET, Unity3D, games, servers
Java Statistical Analysis Tool, a Java library for Machine Learning
Object detection system using deformable part models (DPMs) and latent SVM (voc-release5). You may want to use the latest tarball on my website. The github code may include code changes that have not been tested as thoroughly and will not necessarily reproduce the results on the website.
Ruby language bindings for LIBSVM
Lowest barrier of entry to Image Processing, Computer Vision and Neural Networks on the JavaVM
A platform independent tensor library with autograd for the JVM
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Anahata ASI - Artificial Super Intelligence - Cross-Platform, Modular, Enterprise Ready, Open Source, Pure Java, AGI and ASI Containers. Context Window Garbage Collector, Stateful Toolkits, Flight Recorder. Autonomous Observable Auditable JVM Agent with JIT java code execution. Anahata ASI SDK, Anahata ASI Desktop, Anahata ASI Studio - NetBeans.
Java Scientific Computing Library - Signal Processing, FFT, Filters, PSD, DCT, SciPy-like APIs for JVM & Android used in Machine Learning and Data Science.
Tensorflow style transfer in video
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