Search Results for "optimization" - Page 5
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Showing 982 open source projects for "optimization"
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. Agent-Lightning introduces a lightweight training pipeline that observes agents’ execution traces, converts them into structured data, and feeds them into training algorithms, enabling users to improve agent behaviors systematically. ... -
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Cloud Cost Handbook
Set of guides meant to help explain often-times complex pricing
...It’s intended as an educational resource for developers, finance teams, and FinOps practitioners who need to understand how cloud costs are structured, what drives pricing across services, and how to estimate, optimize, and forecast spend without wading through dense official documentation. The handbook covers core concepts, pricing examples, cost-optimization techniques, and billing models across providers such as AWS, Azure, and GCP, with each section curated to improve clarity and accessibility for readers without deep financial or cloud billing expertise. Because it’s hosted on GitHub and open to contributions, anyone from beginners to experts can add insights, examples, and updated pricing patterns as cloud offerings evolve. -
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Tunix
A JAX-native LLM Post-Training Library
...It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. Tunix also leans into research ergonomics: logging, checkpointing, and metrics are built in, and the code is written to be hackable rather than monolithic. ... -
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MuJoCo MPC
Real-time behaviour synthesis with MuJoCo, using Predictive Control
...MJPC integrates a high-performance GUI and multiple predictive control algorithms, including iLQG, gradient descent, and Predictive Sampling — a competitive, derivative-free method that achieves robust real-time control. The system supports multi-shooting optimization, enabling precise motion planning across diverse domains like quadruped locomotion, humanoid tracking, and dexterous manipulation. In addition to its C++ core, MJPC includes an experimental Python API, enabling integration with custom models and MuJoCo tasks for flexible scripting and experimentation. -
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OpenNext
Open-source Next.js adapter for AWS
This project packages Next.js applications to run natively on AWS’s serverless stack, mapping framework features onto services like Lambda, CloudFront, and S3. It translates routing, API handlers, and middleware into deployable artifacts, handling edge cases such as image optimization, ISR, and streaming responses. Static assets are uploaded to object storage and cached at the edge, while dynamic routes are executed in short-lived compute with cold-start-aware build settings. The adapter aims to preserve the Next.js developer experience—file-based routing, app/router features, and incremental builds—while producing infrastructure that scales automatically. ... -
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golang101
Programming explanation and instruction book focusing on Go syntax
...The current series includes "Go Language (Basic Knowledge) 101" is a programming guide book ( e-book download ) that focuses on Go syntax and semantics (except custom generics) and runtime-related knowledge points. "Go Custom Generics 101" introduces in detail all aspects of Go custom generics. "Go Programming Optimization 101" lists some performance optimization tips and suggestions in some Go programming. "Go Details and Tips 101" collects many details and tips in Go programming (e-book download). This series of books is suitable for both Go beginners and experienced Go programmers. Hope they can help Go programmers understand Go language more deeply and comprehensively. -
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Gonum
Set of numeric libraries for the Go programming language
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more. Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. ... -
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academicpages.github.io
Github Pages template based upon HTML and Markdown for personal
AcademicPages is a ready-made Jekyll theme for academics to build personal websites, blogs, and CV pages. It includes features like publication lists, project showcases, writing blogs, and optimized layouts for easier GitHub Pages deployment. With support for LaTeX rendering, RSS feeds, and responsive design, it's popular among students, researchers, and educators looking to create professional web presences without coding from scratch. -
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. We actively develop Codon... -
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Feishin
A modern self-hosted music player
...Built as a full-stack application, it provides backend APIs to handle user authentication, content delivery, and media storage alongside a frontend that dynamically renders feeds and playback experiences. The system also prioritizes scalability and media management, with mechanisms to handle large volumes of video content efficiently, including streaming optimization and caching. -
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AgensGraph
AgensGraph, a transactional graph database based on PostgreSQL
AgensGraph is a multi-model database that extends PostgreSQL with graph database capabilities, enabling users to work with both relational and graph data within a single system. It supports the Cypher query language alongside SQL, making it ideal for hybrid workloads. -
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TSW
Tencent Server Web
A Node.js-based monitoring and debugging platform developed by Tencent, designed for large-scale applications and performance optimization. -
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Spina
Spina CMS
Spina CMS is an easy-to-use CMS that features a clean interface without distractions. A Rails-based CMS designed for ease of use, with a clean and intuitive interface. -
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ml.js
Machine learning tools in JavaScript
This library is a compilation of the tools developed in the mljs organization. It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add to your dependencies only the libraries that you need, as they are usually published to npm more often. We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find. -
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MonoGame
One framework for creating powerful cross-platform games
One framework for creating powerful cross-platform games. The spiritual successor to XNA with thousands of titles shipped across desktop, mobile, and console platforms. MonoGame is a fully managed .NET open source game framework without any black boxes. Create, develop and distribute your games your way. By leveraging C# and other .NET languages on Microsoft and Mono platforms you can write modern, fast, and reliable game code. We currently support iOS, Android, MacOS, Linux, all Windows... -
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XMRig Proxy
Monero (XMR) Stratum protocol proxy
Extremely high-performance CryptoNote stratum protocol proxy. Works with any pool and any miner with nicehash support. Can easily handle over 100K connections on a cheap $5 (1024 MB) virtual machine. Reduce the number of pool connections up to 256 times, 100K workers become just 391 workers on the pool side. Written on C++/libuv same as XMRig miner. -
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The Minimal Light Theme
A simple and elegant Jekyll theme for an academic personal homepage
A simple and elegant Jekyll theme for an academic personal homepage. The compiled HTML files are available in the html_source_file folder. If you don't like Jekyll, you may directly edit and use the HTML version. -
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CogVideo
text and image to video generation: CogVideoX (2024) and CogVideo
...Current releases cover CogVideoX-2B, CogVideoX-5B, and the upgraded CogVideoX1.5-5B variants, plus image-to-video (I2V) models, with options for BF16/FP16/FP32—and INT8 quantized inference via TorchAO for memory-constrained setups. The codebase emphasizes practical deployment: prompt-optimization utilities (LLM-assisted long-prompt expansion), Colab notebooks, a Gradio web app, and multiple performance knobs (tiling/slicing, CPU offload, torch.compile, multi-GPU, and FA3 backends via partner projects). -
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LLM Course
Course to get into Large Language Models (LLMs)
...Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches that fit their hardware and budgets. The materials also cover inference optimization and quantization to make serving LLMs feasible on commodity GPUs or even CPUs, which is crucial for side projects and startups. Evaluation is treated as a first-class topic, with examples of automatic and human-in-the-loop methods to catch regressions and verify quality beyond simple loss values. By the end, students have a mental model and a practical toolkit for iterating on datasets, training configs, etc. -
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Axon
Nx-powered Neural Networks
...Functional API – A low-level API of numerical definitions (defn) of which all other APIs build on. Model Creation API – A high-level model creation API which manages model initialization and application. Optimization API – An API for creating and using first-order optimization techniques based on the Optax library. Training API – An API for quickly training models, inspired by PyTorch Ignite. Axon provides abstractions that enable easy integration while maintaining a level of separation between each component. You should be able to use any of the APIs without dependencies on others. ... -
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TensorRT Backend For ONNX
ONNX-TensorRT: TensorRT backend for ONNX
Parses ONNX models for execution with TensorRT. Development on the main branch is for the latest version of TensorRT 8.4.1.5 with full dimensions and dynamic shape support. For previous versions of TensorRT, refer to their respective branches. Building INetwork objects in full dimensions mode with dynamic shape support requires calling the C++ and Python API. Current supported ONNX operators are found in the operator support matrix. For building within docker, we recommend using and setting... -
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POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
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PowerGlitch
Tiny JS library to glitch anything on the web
PowerGlitch is a standalone library with no external dependencies. It leverages CSS animations to glitch anything on the web, without using a canvas. It weights less than 2kb minified and gzipped. -
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DeepSpeed
Deep learning optimization library: makes distributed training easy
DeepSpeed is an easy-to-use deep learning optimization software suite that enables unprecedented scale and speed for Deep Learning Training and Inference. With DeepSpeed you can: 1. Train/Inference dense or sparse models with billions or trillions of parameters 2. Achieve excellent system throughput and efficiently scale to thousands of GPUs 3. Train/Inference on resource constrained GPU systems 4. -
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Distributed Llama
Connect home devices into a powerful cluster to accelerate LLM
Distributed Llama is an open-source project that enables users to connect multiple home devices into a powerful cluster to accelerate Large Language Model (LLM) inference. By leveraging tensor parallelism and high-speed synchronization over Ethernet, it allows for faster performance as more devices are added to the cluster. The system supports various operating systems, including Linux, macOS, and Windows, and is optimized for both ARM and x86_64 AVX2 CPUs.
