Search Results for "dependency core"
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Showing 14 open source projects for "dependency core"
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NoneBot
Asynchronous multi-platform robot framework written in Python
...Plug-in development, modular management. Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and flexible support for your needs. NoneBot2 is written based on Python asyncio , and has a certain degree of synchronous function compatibility based on the asynchronous mechanism. ... -
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Applio
A simple, high-quality voice conversion tool focused on ease of use
...Within that interface, users can train and run voice conversion models for tasks like singing conversion, speech-to-speech transformation, and voice cloning. The project is structured to be flexible through plugins and configurations so users can extend functionality without touching the core code. Applio is considered stable and mature; ongoing development is now centered on security patches, dependency maintenance, and occasional improvements, which makes it attractive for production or repeatable workflows. It also includes TensorBoard helper scripts so people training custom models can monitor metrics and experiment more systematically. -
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ComfyUI Desktop
The desktop app for ComfyUI
ComfyUI Desktop is a packaged desktop application that simplifies the installation and usage of ComfyUI, a node-based interface for generative AI workflows such as image generation using diffusion models. It is designed to eliminate the complexity of manual setup by bundling all required dependencies, including Python environments, frontend components, and management tools, into a single installable application. Upon launch, the application automatically installs dependencies, initializes... -
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Stanford CoreNLP
Stanford CoreNLP, a Java suite of core NLP tools
CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text,... -
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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. Because... -
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.NET Agent Skills
Repository for skills to assist AI coding agents with .NET and C#
.NET Agent Skills is Microsoft’s curated skill repository for helping AI coding agents work more accurately with .NET and C# projects. It provides structured knowledge packs and custom agents that guide coding assistants through common development, debugging, migration, build, package, and performance tasks. The repository covers core .NET work as well as more specialized areas such as Entity Framework, MSBuild, NuGet, .NET upgrades, .NET MAUI, and AI-related .NET development. Its purpose is... -
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LLocal
Aiming to provide a seamless and privacy driven chatting experience
LLocal is an Electron-based desktop application that provides a simple and accessible interface for interacting with local large language models, particularly those served through frameworks like Ollama. It focuses on delivering a straightforward chat experience that eliminates the need for command-line interaction while maintaining compatibility with local-first AI workflows. The application leverages Electron to provide cross-platform support, enabling consistent usage across operating... -
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autoresearch-mlx
Apple Silicon (MLX) port of Karpathy's autoresearch
autoresearch-mlx is an Apple Silicon–optimized implementation of the autoresearch framework that enables autonomous AI research loops to run natively on MLX without requiring PyTorch or CUDA dependencies. It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging... -
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Polyaxon
MLOps tools for managing & orchestrating the ML LifeCycle
Polyaxon is an open-source machine learning operations (MLOps) platform built to help individuals, teams, and organizations develop, train, orchestrate, and monitor machine learning and deep learning workflows at scale with reproducibility and automation as core principles. It provides a unified solution for tracking experiments, managing datasets, scheduling jobs, and comparing results across runs, which greatly improves productivity and collaboration in data science teams. Polyaxon... -
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Core ML Stable Diffusion
Stable Diffusion with Core ML on Apple Silicon
Run Stable Diffusion on Apple Silicon with Core ML. python_coreml_stable_diffusion, a Python package for converting PyTorch models to Core ML format and performing image generation with Hugging Face diffusers in Python. StableDiffusion, a Swift package that developers can add to their Xcode projects as a dependency to deploy image generation capabilities in their apps. The Swift package relies on the Core ML model files generated by python_coreml_stable_diffusion. ... -
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textacy
NLP, before and after spaCy
textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals, tokenization, part-of-speech tagging, dependency parsing, etc., delegated to another library, textacy focuses primarily on the tasks that come before and follow after. -
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MXNet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning
...Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scalable to many GPUs and machines. Apache MXNet is more than a deep learning project. ... -
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NLP-progress
Repository to track the progress in Natural Language Processing (NLP)
...This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such as reading comprehension and natural language inference. The main objective is to provide the reader with a quick overview of benchmark datasets and the state-of-the-art for their task of interest, which serves as a stepping stone for further research. ... -
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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.3</version> </dependency> 2) If you want to check out the most recent source-code: git clone https://git.code.sf.net/p/teachingbox/core teachingbox-core Documentation: https://sourceforge.net/p/teachingbox/documentation/HEAD/tree/trunk/manual/
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