Search Results for "model-builder" - Page 31
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Showing 2013 open source projects for "model-builder"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). ... -
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Blankly
Easily build, backtest and deploy your algo in just a few lines
...Blankly is the first framework to enable developers to backtest, paper trade, and go live across exchanges without modifying a single line of trading logic on stocks, crypto, and forex. Every model needs to figure out how to buy and sell. We make it super easy for you so you can focus on building better trading algos. Your models can run on any platform, and on any supported exchange. We make that as easy as just changing one line of code. -
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Real-ESRGAN ncnn Vulkan
NCNN implementation of Real-ESRGAN
...Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. The Vulkan backend enables fast execution on GPUs from different vendors (Intel/AMD/Nvidia) with broad support, making it suitable for non-Python environments, production systems, or performance-constrained setups. -
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CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
...It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their understanding of Spark by not only using it as a data processing engine but also exploring how its internals function. Through code analysis and commentary, CoolplaySpark helps readers connect theoretical concepts with practical implementation details. ... -
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FlatCC FlatBuffers in C for C
FlatBuffers Compiler and Library in C for C
flatcc has no external dependencies except for build and compiler tools, and the C runtime library. With concurrent Ninja builds, a small client project can build flatcc with libraries, generate schema code, link the project and execute a test case in a few seconds, produce binaries between 15K and 60K, read small buffers in 30ns, build FlatBuffers in about 600ns, and with a larger executable also handle optional json parsing or printing in less than 2 us for a 10 field mixed type message.... -
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Model Search
Framework that implements AutoML algorithms
...The framework logs trials, metrics, and artifacts so you can analyze what the search learned and why certain designs dominate. It’s intended as a platform for method development as much as for model discovery. -
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apl-library
Useful stuff for APL programmers
This collection of APL libraries have been contributed to GNU APL and should be downloaded here: https://gnu.org/software/apl. -
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Provider
InheritedWidgets, but simple
...Because it relies on Flutter’s core mechanisms, it integrates seamlessly with common architectural styles and existing widgets. Many apps use provider as a baseline pattern, and later evolve toward more advanced solutions as complexity grows—without discarding the conceptual model provider introduces. -
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Django REST Framework User
This Django User Model is customised user model
This Django User Model is a customized user model keeping in mind the practical need. JWT Support (Using Simple JWT) Mobile Number, single field for full name, REST API to register, REST API to login, MultiModelBackend: User can login using either of mobile, email or username. REST API to login with OTP (Same API endpoint as for OTP Verification; Set is_login: true while sending JSON request). -
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TARS
Markup builder on gulp
...To bypass dependency installation for every TARS project, TARS-CLI was created. As such, TARS is not a npm package by itself. This decision was made so that everyone could comfortably customize the builder for themselves. TARS-CLI is just a simple builder interface, which includes all dependencies for TARS. It is strongly recommended to use TARS-CLI for development. -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. ... -
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graphql-client
A Ruby library for declaring, composing and executing GraphQL queries
...If you haven't already, familiarize yourself with the GraphQL query syntax. Queries are declared with the same syntax inside of a <<-'GRAPHQL' heredoc. There isn't any special query builder Ruby DSL. This client library encourages all GraphQL queries to be declared statically and assigned to a Ruby constant. If you're using Ruby on Rails ERB templates, theres a ERB extension that allows static queries to be defined in the template itself. In standard Ruby you can simply assign queries and fragments to constants and they'll be available throughout the app. ... -
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SwagGen
OpenAPI/Swagger 3.0 Parser and Swift code generator
...Templates for any language can be written that leverage this generator. SwagGen includes a bundled template for generating a client-side Swift library for interfacing with the Swagger spec. It includes support for model inheritance, shared enums, discrete and mutable request objects, inline schemas, Codable and Equatable models, configurable options, generic networking stack, and many other niceties. -
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Unet
Source code for unet-pytorch, which can train its own model
...The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. ... -
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Vale
Compiler for the Vale programming language
Vale is a systems programming language and compiler that strives to combine performance, safety, and ease in a way that avoids many of the complexities of traditional memory management techniques. It is ahead-of-time (AOT) compiled, targeting LLVM as a backend, and is statically typed. The language introduces a concept called generational references to provide memory safety without relying on a garbage collector, and aims for “safe without a borrow checker” (i.e. reducing the burden on the... -
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Node.js express.js MongoDB JWT REST API
Node.js express.js MongoDB JWT REST API - Basic Project Skeleton
This is a basic API REST skeleton written on JavaScript using async/await. Great for building a starter web API for your front-end (Android, iOS, Vue, react, angular, or anything that can consume an API) This project is created to help other developers create a basic REST API in an easy way with Node.js. This basic example shows how powerful and simple JavaScript can be. Do you want to contribute? Pull requests are always welcome to show more features. Custom email/password user system with... -
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AngularJS
AngularJS - HTML enhanced for web apps
...as your template language and lets you extend HTML’s syntax to express your application’s components clearly and succinctly. It automatically synchronizes data from your UI (view) with your JavaScript objects (model) through 2-way data binding. To help you structure your application better and make it easy to test, AngularJS teaches the browser how to do dependency injection and inversion of control. -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2 and Xception backbones and notes that the correct backbone should be selected during training and prediction. The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. ... -
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AugLy
A data augmentations library for audio, image, text, and video
...These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity. AugLy is a great library to utilize for augmenting your data in model training, or to evaluate the robustness gaps of your model! We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. While AugLy contains more generic data augmentations as well, it will be particularly useful to you if you're working on a problem like copy detection, hate speech detection, etc. -
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Statistical Rethinking 2022
Statistical Rethinking course winter 2022
...The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a direct hands-on reference for students following the 2022 recorded lecture series. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting. -
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Botkit
Tool for building chat bots, apps and custom integrations
An open source developer tool for building chat bots, apps and custom integrations for major messaging platforms. Part of the Microsoft Bot Framework. We love bots, and want to make them easy and fun to build! Include Botkit into your Node application and boot up a controller that will define your bot's behaviors. In this case, we're setting up a bot to use with the Bot Framework Emulator. Tell the bot to listen for users saying "hello," and use `bot.reply` to send an immediate response.... -
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Unified Code Generation
Open-source code generator for Simulink/Stateflow
...Some of the strengths of UCGN: - Clearly readable source-code - Separation of functionality and parameters ("tunable parameters") - Robust data storage (compile-time static structures in favor of pointer run-time constructs) - Clear software architecture, direct correspondence to the model architecture - Separation of reusable library code - Simplicity and uniformity of software interfaces (for testing etc.) The following features are supported by the Simulink/UCGN - Discrete single-rate Simulink models and libraries - Block library with 50+ standard Simulink blocks - Periodic, condition-driven Stateflow charts (including flowgraphs, loops) - Structured data types through bus objects - Simulink native enumer -
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PPet
Put a cute girl on your desktop for a little more fun
Put a cute girl on your desktop for a little more fun, supports Mac, Win and Linux. Download the latest version, use .dmg for Mac, .exe for Windows, and .deb for Linux. Drag the local model folder into the window, and it will be updated to the model list if the import is successful. Add files (local models start with) jsonin Settings -> Models list .file://. -
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NetworkResponse Retrofit adapter
Retrofit call adapter to model success/failed responses as sealed type
This library provides a Kotlin Coroutines-based Retrofit call adapter for wrapping your API responses in a NetworkResponse sealed type.
