Search Results for "simulation model library" - Page 7
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Showing 2886 open source projects for "simulation model library"
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HY-World 2.0
A Multi-Modal World Model for Reconstructing, Generating, Simulation
HY-World 2.0 is a multi-modal world model framework for reconstructing, generating, and simulating navigable 3D worlds from diverse inputs. It accepts text prompts, single-view images, multi-view images, and videos, and produces 3D world representations rather than limiting output to flat video generation. For text and single-image inputs, it generates high-fidelity 3D Gaussian Splatting scenes through a multi-stage pipeline that includes panorama generation, trajectory planning, world... -
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Rust Programming Language
Empowering everyone to build reliable and efficient software
The Rust Programming Language is a language that empowers you to build reliable and efficient software. It runs blazingly fast and is memory-efficient, so it can power performance-critical services and run on embedded devices. It has a rich type system and ownership model, ensuring both thread and memory safety. Consisting of a standard library, great documentation and a friendly compiler, plus a top-notch build tool, package manager, auto-formatter and many other great tools, it’s the language of choice for increased productivity. Hundreds of companies the world over are using Rust to power an amazing range of cross-platform solutions. ... -
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Java API for GitHub
Java API for GitHub
This library defines an object oriented representation of the GitHub API. By "object oriented" we mean there are classes that correspond to the domain model of GitHub (such as GHUser and GHRepository), operations that act on them as defined as methods (such as GHUser.follow()), and those object references are used in favor of using string handle (such as GHUser.isMemberOf(GHOrganization) instead of GHUser.isMemberOf(String)) The library supports both github.com and GitHub Enterprise. ... -
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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. Achieve unprecedented low latency and high throughput for inference 5. Achieve extreme... -
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CadQuery
A python parametric CAD scripting framework based on OCCT
...Provide a non-proprietary, plain text model format that can be edited and executed with only a web browser. The scripts use a standard programming language, Python, and thus can benefit from the associated infrastructure. This includes many standard libraries and IDEs. CadQuery's CAD kernel Open CASCADE Technology (OCCT) is much more powerful than the CGAL used by OpenSCAD. -
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Epoxy
Android library for building complex screens in a RecyclerView
Epoxy is an Android library for building complex screens in a RecyclerView. Models are automatically generated from custom views or databinding layouts via annotation processing. These models are then used in an EpoxyController to declare what items to show in the RecyclerView. This abstracts the boilerplate of view holders, diffing items and binding payload changes, item types, item ids, span counts, and more, in order to simplify building screens with multiple view types. Additionally,... -
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carbon-components-svelte
Svelte implementation of the Carbon Design System
...Its styling model supports multiple official themes. -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. -
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Switchyard
Switchyard lets LLM applications route traffic across models
Switchyard is a Rust proxy and library for routing traffic between LLM clients and model backends. It translates among OpenAI Chat, OpenAI Responses, and Anthropic Messages formats so agents can keep using their native APIs. Requests can be distributed across vLLM, NVIDIA NIM, Ollama, OpenRouter, and other compatible endpoints. Routing strategies include random splits, LLM classification, signal-driven stage routing, escalation, and custom algorithms. -
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Koila
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code
Koila is a lightweight Python library designed to help developers avoid memory errors when training deep learning models with PyTorch. The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward pass of neural network training. ... -
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Elixir LangChain
Elixir implementation of a LangChain style framework
Elixir LangChain is an Elixir-native implementation of the LangChain concept, designed to help developers build applications powered by large language models using the Elixir ecosystem. The library focuses on enabling composable workflows where different processes, APIs, and services can be connected into structured pipelines driven by LLMs. It mirrors the architecture of traditional LangChain frameworks by providing abstractions for chains, tools, agents, and model integrations while adapting them to Elixir’s concurrency model. ... -
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Olmo-core
PyTorch building blocks for the OLMo ecosystem
OLMo-core is a Python library from AI2 that provides reusable PyTorch building blocks for training large language models at scale. It underpins the broader OLMo ecosystem and includes components for models, data loading, distributed execution, optimization, checkpointing, evaluation, and generation. Official scripts reproduce training configurations for released OLMo models. The library supports advanced attention backends, mixture-of-experts architectures, float8 training, and fused... -
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trackers
Multi-object tracking algorithms
trackers is a plug-and-play multi-object tracking library designed to work with virtually any object detection model, enabling developers to follow objects across video frames with minimal setup. The library provides clean, modular implementations of leading tracking algorithms and can be used either from the command line or embedded directly into Python pipelines. It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that include labels and trajectories. ... -
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KerasTuner
A Hyperparameter Tuning Library for Keras
KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search... -
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django-import-export
Django application and library for importing and exporting data
...Also, the report_skipped option controls whether skipped records appear in the import Result object, and if using the admin whether skipped records will show in the import preview page. Not all data can be easily extracted from an object/model attribute. In order to turn complicated data model into a (generally simpler) processed data structure on export, dehydrate_<fieldname> method should be defined. -
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
MLX-Audio is a speech library built on Apple’s MLX framework and optimized for Apple Silicon machines (M-series Macs). It focuses on text-to-speech and speech-to-speech workflows, with APIs and a command-line interface that make it easy to generate high-quality audio from text. Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI... -
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face.evoLVe
High-Performance Face Recognition Library on PaddlePaddle & PyTorch
face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. -
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Advanced AI explainability for PyTorch
Advanced AI Explainability for computer vision
...The library supports a wide variety of tasks including image classification, object detection, semantic segmentation, and similarity analysis. It also provides metrics and evaluation tools that help measure the reliability and quality of the generated explanations. By integrating easily with PyTorch models, the library allows developers to diagnose model errors, detect biases in datasets, and improve model transparency. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. ... -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. ... -
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Brick
A declarative Unix terminal UI library written in Haskell
...Event-handling is done by pattern-matching on incoming events and updating your application state. Under the hood, this library builds upon vty, so some knowledge of Vty will be necessary to use this library. Brick depends on vty-crossplatform, so Brick should work anywhere Vty works (Unix and Windows). Brick releases prior to 2.0 only support Unix-based systems. -
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Hivemind
Decentralized deep learning in PyTorch. Built to train models
...Train neural networks of arbitrary size: parts of their layers are distributed across the participants with the Decentralized Mixture-of-Experts. If you have succesfully trained a model or created a downstream repository with the help of our library, feel free to submit a pull request that adds your project to the list. -
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Passmark
The open-source Playwright library for AI browser regression testing
The Passmark project is an open-source AI-powered regression testing framework built on top of Playwright that enables developers to write end-to-end browser tests using natural language instead of traditional scripting. It is designed to simplify and accelerate testing workflows by allowing AI models to interpret human-readable instructions and translate them into executable browser actions. One of its defining features is a cache-first execution model, where AI is used initially to... -
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mlforecast
Scalable machine learning for time series forecasting
...Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates those automatically based on a simple configuration. It supports multi-series forecasting, meaning you can train one model that forecasts many time series at once (common in retail, demand forecasting, etc.), rather than one model per series. The library is built to scale: behind the scenes, it can leverage distributed computing frameworks (Spark, Dask, Ray) when datasets or the number of series grow large. -
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NetBird
Connect your devices into a secure WireGuard-based overlay network
NetBird is an open-source solution that builds a WireGuard®-based overlay network enabling seamless, encrypted peer-to-peer connectivity without the complexity of firewall rules, port forwarding, or centralized VPN gateways. It integrates access control features such as SSO and MFA for secure, policy-driven networking. Every machine in the network runs NetBird Agent (or Client) that manages WireGuard. Every agent connects to Management Service that holds network state, manages peer IPs, and...
