Search Results for "model train design"
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Showing 281 open source projects for "model train design"
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. -
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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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Model Context Protocol TypeScript SDK
The official Typescript SDK for Model Context Protocol servers
The TypeScript SDK for Model Context Protocol simplifies integration with the Model Context Protocol, enabling developers to interact with AI models effectively. -
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Understrap WordPress Theme Framework
The renowned open-source WordPress starter theme
Fully designed, beautifully implemented themes for quick site builds. The premier starter theme for custom WordPress development. Parent and Child Theme. Free and Open-Source. Train your team to become Understrap experts in record time. Start with simple, powerful theme code based on Underscores, the best-practices starter theme from Automattic, the creators of WordPress. Add beautiful, flexible styles, components, grids and responsive design with Bootstrap, the industry standard for mobile-first development. ... -
Smart Business Texting that Generates PipelineTextUs is the leading text messaging service provider for businesses that want to engage in real-time conversations with customers, leads, employees and candidates. Text messaging is one of the most engaging ways to communicate with customers, candidates, employees and leads. 1:1, two-way messaging encourages response and engagement. Text messages help teams get 10x the response rate over phone and email. Business text messaging has become a more viable form of communication than traditional mediums. The TextUs user experience is intentionally designed to resemble the familiar SMS inbox, allowing users to easily manage contacts, conversations, and campaigns. Work right from your desktop with the TextUs web app or use the Chrome extension alongside your ATS or CRM. Leverage the mobile app for on-the-go sending and responding.
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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. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. ... -
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tlaplus
TLC is an explicit state model checker for specifications in TLA+
TLC is an explicit state model checker for specifications written in TLA+. The TLA+Toolbox is an IDE for TLA+. TLA+ is a high-level language for modeling programs and systems--especially concurrent and distributed ones. It's based on the idea that the best way to describe things precisely is with simple mathematics. TLA+ and its tools are useful for eliminating fundamental design errors, which are hard to find and expensive to correct in code. -
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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PyG
Graph Neural Network Library for PyTorch
...All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
...It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network is needed after all. And so research continues. For simpler training, you can directly supply text strings instead of precomputing text encodings. ... -
Nonprofit Budgeting SoftwareMartus' collaborative and easy-to-use budgeting and reporting platform will save you hundreds of hours each year. It's designed to make the entire budgeting process easier and create unlimited financial transparency.
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
...You can also do your own language model pretraining via the spacy pre train command. You can even share your transformer or another contextual embedding model across multiple components, which can make long pipelines several times more efficient. To use transfer learning, you’ll need at least a few annotated examples for what you’re trying to predict. -
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Lobe Chat
An open-source, modern-design AI chat framework
LobeChat, unlock the superpower of your brain. Pioneering the new age of thinking and creating. Built for you, the Super Individual. LobeChat supports file upload and knowledge base functionality. You can upload various types of files including documents, images, audio, and video, as well as create knowledge bases, making it convenient for users to manage and search for files. Additionally, you can utilize files and knowledge base features during conversations, enabling a richer dialogue... -
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Axon Framework
Framework for Evolutionary Message-Driven Microservices on the JVM
Axon provides a unified, productive way of developing Java applications that can evolve without significant refactoring from a monolith to Event-Driven microservices. Axon includes both a programming model as well as specialized infrastructure to provide enterprise-ready operational support for the programming model - especially for scaling and distributing mission-critical business applications. Axon is composed of the following concepts and products. Domain-Driven Design (DDD) defines many concepts and patterns that help design software effectively, in line with the business requirements. ... -
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zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite... -
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Sortable behaviour for Eloquent models
Sortable behaviour for Eloquent models
This package provides a trait that adds sortable behavior to an Eloquent model. The value of the order column of a new record of a model is determined by the maximum value of the order column of all records of that model + 1. The package also provides a query scope to fetch all the records in the right order. Spatie is a web design agency in Antwerp, Belgium. You'll find an overview of all our open source projects on our website. -
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ASP.NET Boilerplate
A web application framework
ASP.NET Boilerplate is a general purpose application framework especially designed for new modern web applications. It uses already familiar tools and implements best practices around them to provide you a SOLID development experience. Provides a layered architectural model based on Domain Driven Design. Designed as modular and extensible. Provides infrastructure to build your own modules too. SaaS applications made easy! Integrated multi-tenancy from database to UI. Designed and developed DDD in mind. Provides a SOLID model for your application. Compherensive documentation and jump start tutorials. ... -
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ComfyUI
The most powerful and modular diffusion model GUI, api and backend
The most powerful and modular diffusion model is GUI and backend. This UI will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart-based interface. We are a team dedicated to iterating and improving ComfyUI, supporting the ComfyUI ecosystem with tools like node manager, node registry, cli, automated testing, and public documentation. -
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Opacus
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,... -
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. ... -
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Draper
Decorators/view-models for Rails applications
Draper adds an object-oriented layer of presentation logic to your Rails application. Without Draper, this functionality might have been tangled up in procedural helpers or adding bulk to your models. With Draper decorators, you can wrap your models with presentation-related logic to organize and test this layer of your app much more effectively. Imagine your application has an Article model. With Draper, you'd create a corresponding ArticleDecorator. The decorator wraps the model, and deals... -
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SageMaker Spark
A Spark library for Amazon SageMaker
...With SageMaker Spark you construct Spark ML Pipelines using Amazon SageMaker stages. These pipelines interleave native Spark ML stages and stages that interact with SageMaker training and model hosting. With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting your trained models, and, if you have your own ML algorithms built into SageMaker compatible Docker containers, you can use SageMaker Spark to train and infer on DataFrames with your own algorithms -- all at Spark scale. ... -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your... -
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AI4U
Multi-engine plugin to specify agents with reinforcement learning
...AI4U can be integrated into Imitation Learning through Behavioral Cloning or Generative Adversarial Imitation Learning present on stable-baslines. Train using multiple concurrent Unity/Godot environment instances. Unity/Godot environment partial control from Python. Wrap Unity/Godot learning environments as a gym. -
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Gorse Recommender System Engine
An open source recommender system service written in Go
...Gorse aims to be a universal open-source recommender system that can be easily introduced into a wide variety of online services. By importing items, users and interaction data into Gorse, the system will automatically train models to generate recommendations for each user. -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. 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,...
