Search Results for "simulation model library" - Page 3
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Showing 2885 open source projects for "simulation model library"
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SageMaker TensorFlow Training Toolkit
Toolkit for running TensorFlow training scripts on SageMaker
Toolkit for running TensorFlow training scripts on SageMaker. SageMaker TensorFlow Training Toolkit is an open-source library for using TensorFlow to train models on Amazon SageMaker. To use your TensorFlow Serving model on SageMaker, you first need to create a SageMaker Model. After creating a SageMaker Model, you can use it to create SageMaker Batch Transform Jobs for offline inference, or create SageMaker Endpoints for real-time inference. A SageMaker Model contains references to a model.tar.gz file in S3 containing serialized model data, and a Docker image used to serve predictions with that model. ... -
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Jolt Physics
A multi core friendly rigid body physics and collision detection lib
...We therefore place a lot of emphasis on concurrently accessing the physics simulation data outside of the main physics simulation update. Sections of the world can be loaded / unloaded in the background. A batch of physics bodies can be prepared on a background thread without locking or affecting the physics simulation and then inserted into the world all at once with a minimal impact on performance. -
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NeuroSploit
NeuroSploit is an advanced, AI-powered penetration testing framework
...The system performs reconnaissance, selects specialized agents for the discovered attack surface, and runs applicable assessments in parallel. Candidate findings are checked through cross-model validation and supporting tool evidence before being reported. It supports black-box, white-box, gray-box, infrastructure, and AI application security testing modes. NeuroSploit also provides a terminal interface, project memory, configurable model providers, structured reports, and a large library of specialized security agents. -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. ... -
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Monaco Editor
A browser based code editor
Monaco Editor is the rich, browser-based code editor that powers Visual Studio Code, providing advanced editing capabilities as a standalone embeddable library for web applications. Models are at the heart of Monaco editor. It's what you interact with when managing content. A model represents a file that has been opened. This could represent a file that exists on a file system, but it doesn't have to. For example, the model holds the text content, determines the language of the content, and tracks the edit history of the content. ... -
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AirLLM
AirLLM 70B inference with single 4GB GPU
AirLLM is an open source Python library that enables extremely large language models to run on consumer hardware with very limited GPU memory. The project addresses one of the main barriers to local LLM experimentation by introducing a memory-efficient inference technique that loads model layers sequentially rather than storing the entire model in GPU memory. This layer-wise inference approach allows models with tens of billions of parameters to run on devices with only a few gigabytes of VRAM. ... -
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gofeed
Parse RSS, Atom and JSON feeds in Go
The gofeed library is a robust feed parser that supports parsing both RSS, Atom and JSON feeds. The library provides a universal gofeed. Parser that will parse and convert all feed types into a hybrid gofeed.Feed model. You also have the option of utilizing the feed-specific atom. Parser or RSS. Parser or JSON. Parser parsers generate atoms. Feed, RSS.Feed and JSON. -
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CUDA-Q
C++ and Python support for the CUDA Quantum programming model
CUDA-Q is an open-source platform for developing hybrid quantum-classical applications using a unified programming model across CPUs, GPUs, and quantum processing units. It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum... -
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DSGE.jl
Solve and estimate Dynamic Stochastic General Equilibrium models
DSGE.jl is a Julia package developed by the Federal Reserve Bank of New York for estimating and analyzing dynamic stochastic general equilibrium (DSGE) models. It provides tools for Bayesian estimation, filtering, forecasting, and model comparison, supporting both academic research and policy applications. DSGE.jl includes pre-configured models used by central banks and offers extensibility for custom macroeconomic modeling. -
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TurboFieldfare
Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook
TurboFieldfare is a custom Swift and Metal runtime for running the instruction-tuned Gemma 4 26B-A4B model on Apple Silicon Macs with limited memory. Instead of loading the entire model, it keeps the shared core and KV cache in RAM while streaming only the routed experts required for each token from SSD. This approach reduces active memory use to roughly 2 GB while the installed model occupies about 14.3 GB of storage. The project includes a native Mac application, command-line tools, a streaming installer, a Swift library, and an experimental OpenAI-compatible local server. ... -
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Moon
A lightweight game server framework implemented with Actor Model
Moon is a lightweight game server framework based on the actor model. One worker thread can have one or more actors (services), which communicate with each other through message queues. There are many features for game server development. -
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anydoc
Convert Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV
anydoc is a fast Rust library for converting office documents and publications into clean GitHub-Flavored Markdown. It supports Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, and text-based PDF files through one shared document model. The converter preserves headings, formatting, links, lists, tables, notes, footnotes, internal references, and embedded asset metadata. -
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CodeIgniter 4
Open Source PHP Framework (originally from EllisLab)
CodeIgniter4 is a powerful PHP framework designed for building web applications. It is a next-generation version of the popular CodeIgniter framework, offering enhanced features and improved performance. CodeIgniter4 follows the MVC (Model-View-Controller) pattern and is built to be lightweight, with a focus on simplicity and speed. It comes with a rich set of libraries and tools for developing dynamic web applications. -
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mergekit
Tools for merging pretrained large language models
mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. ... -
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MCP Go
A Go implementation of the Model Context Protocol (MCP)
mcp-go is a Go implementation of the Model Context Protocol (MCP), designed to enable seamless integration between Large Language Model (LLM) applications and external data sources and tools. It abstracts the complexities of the protocol and server management, allowing developers to focus on building robust tools. The library is high-level and user-friendly, facilitating the development of MCP servers in Go. -
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BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
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Node-RED
Low-code programming for event-driven applications
...Node-RED provides a browser-based flow editor that makes it easy to wire together flows using the wide range of nodes in the palette. Flows can be then deployed to the runtime in a single-click. JavaScript functions can be created within the editor using a rich text editor. A built-in library allows you to save useful functions, templates or flows for re-use. The light-weight runtime is built on Node.js, taking full advantage of its event-driven, non-blocking model. This makes it ideal to run at the edge of the network on low-cost hardware such as the Raspberry Pi as well as in the cloud. -
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FLUX.2-klein-4B
Flux 2 image generation model pure C inference
FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. ... -
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uqlm
Uncertainty Quantification for Language Models, is a Python package
...The library includes both black-box and white-box approaches to uncertainty estimation. Black-box methods evaluate model outputs through multiple generations or comparative analysis, while white-box methods rely on token probabilities produced during inference. UQLM also supports ensemble strategies and model-as-judge approaches for evaluating responses. -
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asio is a cross-platform C++ library for network and low-level I/O programming that provides developers with a consistent asynchronous model using a modern C++ approach.
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LangChain Open Deep Research
Fully open source deep research agent
Open Deep Research is a configurable, fully open-source agent for producing detailed research reports from complex questions. It separates work across models used for summarization, active research, information compression, and final report generation. Users can select from multiple language model providers as long as the chosen models support tool calling and structured outputs. Search can be powered by several APIs, native provider search, or external tools connected through MCP. The agent... -
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OllamaSharp
The easiest way to use Ollama in .NET
...It supports both local and remote Ollama instances, enabling developers to run AI models on their own hardware or connect to remote model servers. The library is designed to simplify integration by allowing developers to interact with AI models using just a few lines of code while still supporting advanced functionality. OllamaSharp also includes real-time streaming capabilities that allow applications to display generated responses incrementally as they are produced. -
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FoundationDB
Open source, distributed, transactional key-value store
...FoundationDB has been running in production for years and been hardened with lessons learned. Backing FoundationDB up is an unmatched testing system based on a deterministic simulation engine. Developers on an OS for which there is no binary package, or who would like to start hacking on the code, can get started by compiling from source. -
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promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
...Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API.
