Showing 1232 open source projects for "optimization"

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  • 1
    Marketing Skills for Claude Code

    Marketing Skills for Claude Code

    Marketing skills for Claude Code and AI agents

    Marketing Skills for Claude Code is an extensive library of structured “skills” designed to empower Claude Code and similar AI coding agents to perform specialized marketing tasks with strategic depth, helping technical marketers and founders apply best practices in areas such as conversion rate optimization, SEO, analytics, copywriting, and growth engineering directly in an AI-assisted workflow. Each skill in the repository is expressed as a Markdown file that encapsulates specific marketing frameworks, workflows, and context, enabling AI agents to recognize and execute domain-targeted tasks like “analytics-tracking” setup, “seo-audit,” conversion testing plans, launch strategies, email sequence creation, and more. ...
    Downloads: 21 This Week
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  • 2
    ET-Optimizer

    ET-Optimizer

    ET is a powerful application to improve performance

    ET-Optimizer is a performance optimization tool designed to enhance system responsiveness and efficiency by applying targeted configurations and tweaks to operating system settings and background processes. It focuses on improving performance in specific use cases such as gaming or real-time applications where latency and system overhead are critical factors. The tool typically includes scripts or automated routines that adjust system parameters, disable unnecessary services, and optimize resource allocation. ...
    Downloads: 38 This Week
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  • 3
    RyTuneX

    RyTuneX

    RyTuneX is a cutting-edge optimizer built with the WinUI 3 framework

    RyTuneX is a comprehensive Windows-system optimization tool aimed at users who want to enhance performance, privacy and usability on systems running Windows 10 (20H1 +) and Windows 11. It is built using the WinUI 3 framework and .NET 8 to provide a modern, responsive interface and native Windows look and feel. The application lets users “debloat” their system by removing pre-installed apps and Windows features that may be unnecessary or resource-heavy, helping free up resources and storage. ...
    Downloads: 44 This Week
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  • 4
    GameMode

    GameMode

    Optimise Linux system performance on demand

    GameMode is a daemon/lib combo for Linux that allows games to request a set of optimizations be temporarily applied to the host OS and/or a game process. GameMode was designed primarily as a stop-gap solution to problems with the Intel and AMD CPU power save or on-demand governors but is now host to a range of optimization features and configurations.
    Downloads: 2 This Week
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  • 5
    ort

    ort

    Fast ML inference & training for ONNX models in Rust

    ...One of its key strengths is its flexibility, as it supports multiple backends and allows developers to configure execution providers depending on available hardware. ort also includes advanced capabilities such as model compilation and optimization, reducing startup time and improving runtime performance in production systems.
    Downloads: 0 This Week
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  • 6
    mllm

    mllm

    Fast Multimodal LLM on Mobile Devices

    ...Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies such as ARM NEON and x86 AVX2 instructions. The system supports multiple optimization techniques including quantization, pruning, and speculative decoding to improve performance while reducing computational overhead. It also provides tools to convert models from popular formats like PyTorch checkpoints into optimized runtime formats that can be executed on supported hardware platforms.
    Downloads: 0 This Week
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  • 7
    LightLLM

    LightLLM

    LightLLM is a Python-based LLM (Large Language Model) inference

    ...The framework enables developers to run and serve modern language models with significantly improved speed and resource efficiency compared to many traditional inference systems. Built primarily in Python, the project integrates optimization techniques and ideas from several leading open-source implementations, including FasterTransformer, vLLM, and FlashAttention, to accelerate token generation and reduce latency. LightLLM is designed to handle large-scale model workloads in production environments, supporting efficient batching and GPU utilization for fast inference across multiple requests. ...
    Downloads: 0 This Week
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  • 8
    PyTorch-Tutorial-2nd

    PyTorch-Tutorial-2nd

    CV, NLP, LLM project applications, and advanced engineering deployment

    ...The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization strategies. It also introduces practical machine learning techniques such as convolutional neural networks, recurrent networks, and other architectures commonly used in modern AI applications. Each tutorial focuses on step-by-step implementation so learners can understand how theoretical concepts translate into working code. The materials are designed for both beginners and intermediate developers who want to gain practical experience building deep learning models using PyTorch.
    Downloads: 0 This Week
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  • 9
    Xtuner

    Xtuner

    A Next-Generation Training Engine Built for Ultra-Large MoE Models

    ...Its architecture incorporates memory-efficient optimizations that allow researchers to train large models even when computational resources are limited. XTuner is also designed to integrate with modern AI ecosystems, supporting multimodal training, reinforcement learning optimization, and instruction tuning pipelines.
    Downloads: 0 This Week
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  • 10
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    ...Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. The system operates in a ReAct-style loop where the agent profiles baseline implementations, writes CUDA code, compiles it in a sandbox, and iteratively refines performance. CUDA-Agent has demonstrated strong benchmark results, achieving high pass rates and significant speedups compared with compiler baselines such as torch.compile.
    Downloads: 0 This Week
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  • 11
    Coze Loop

    Coze Loop

    Next-generation AI Agent Optimization Platform

    ...The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also includes automated evaluation capabilities that assess agent performance across multiple quality dimensions such as accuracy and compliance. Its observability layer captures detailed execution traces, enabling teams to understand how inputs, prompts, and tools interact during runtime. ...
    Downloads: 0 This Week
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  • 12
    Web Quality Skills

    Web Quality Skills

    Agent Skills for optimizing web quality based on Lighthouse

    This repository is a curated set of AI agent skills that encapsulate best practices for improving web quality, performance, accessibility, search engine optimization, and general best practices for web projects. It encodes knowledge drawn from Google Lighthouse audits, Core Web Vitals heuristics, WCAG accessibility guidelines, and real-world engineering experience, allowing coding agents to automatically assess and suggest improvements. These skills are framework-agnostic, meaning they apply to React, Vue, Svelte, Angular, Astro, or even plain HTML projects. ...
    Downloads: 0 This Week
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  • 13
    Agent Lightning

    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. ...
    Downloads: 0 This Week
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  • 14
    Agent Reinforcement Trainer

    Agent Reinforcement Trainer

    Train multi-step agents for real-world tasks using GRPO

    Agent Reinforcement Trainer, or ART is an open-source reinforcement learning framework tailored to training large language model agents through experience, making them more reliable and performant on multi-turn, multi-step tasks. Instead of just manually crafting prompts or relying on supervised fine-tuning, ART uses techniques like Group Relative Policy Optimization (GRPO) to let agents learn from environmental feedback and reward signals. The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks.
    Downloads: 0 This Week
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  • 15
    Cloud Cost Handbook

    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.
    Downloads: 0 This Week
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  • 16
    Tunix

    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. ...
    Downloads: 0 This Week
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  • 17
    OpenNext

    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. ...
    Downloads: 0 This Week
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  • 18
    golang101

    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.
    Downloads: 0 This Week
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  • 19
    Gonum

    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. ...
    Downloads: 0 This Week
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  • 20
    PyMC3

    PyMC3

    Probabilistic programming in Python

    ...A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets.
    Downloads: 0 This Week
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  • 21
    Yoast WordPress SEO

    Yoast WordPress SEO

    Yoast SEO for WordPress

    The Yoast SEO plugin is the most popular SEO tool for WordPress, offering comprehensive tools to optimize content for search engines. It provides real-time page analysis, readability checks, and automated metadata handling to improve website visibility.
    Downloads: 1 This Week
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  • 22
    AgensGraph

    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.
    Downloads: 0 This Week
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  • 23
    TSW

    TSW

    Tencent Server Web

    A Node.js-based monitoring and debugging platform developed by Tencent, designed for large-scale applications and performance optimization.
    Downloads: 0 This Week
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  • 24
    Spina

    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.
    Downloads: 0 This Week
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  • 25
    Prompt Optimizer

    Prompt Optimizer

    A prompt word optimizer to help write high-quality prompt words

    Prompt-Optimizer is a high-impact AI prompt engineering tool designed to help users craft better, more effective prompts for large language models, boosting the quality and relevance of AI responses. It focuses on automating and streamlining the iterative refinement of prompts by analyzing examples, comparing original and optimized text, and guiding users through multi-round improvements that surface clarity, structure, and specificity. With support for different deployment modes including...
    Downloads: 14 This Week
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