Search Results for "dependency core"
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Showing 12 open source projects for "dependency core"
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1
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. ... -
2
BlackSheep
Fast ASGI web framework for Python
BlackSheep is an asynchronous web framework to build event-based web applications with Python. A rich code API, based on dependency injection and inspired by Flask and ASP.NET Core. A typing-friendly codebase, which enables a comfortable development experience thanks to hints when coding with IDEs. Built-in generation of OpenAPI Documentation, supporting version 3, YAML, and JSON. A cross-platform framework, using the most modern versions of Python. BlackSheep supports automatic binding of values for request handlers, by type annotation or by conventions. -
3
GQL
A GraphQL client in Python
...GQL supports multiple transports to communicate with the backend. Each transport can necessitate specific dependencies. If you only need one transport you might want to install only the dependency needed for your transport, instead of using the “all” extra dependency as described above, which installs everything. -
4
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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5
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... -
6
TelcoChisel OS
Advanced Telecom Security Live Linux OS for 5G/4G Cellular Auditing, S
TelcoChisel is an advanced, bootable live Linux operating system purpose-built for cellular security researchers, Software Defined Radio (SDR) engineers, and telecommunications penetration testers. Eliminating dependency conflicts and driver compilation issues, TelcoChisel delivers an out-of-the-box, carrier-grade laboratory equipped with 88 pre-configured telecommunications security tools across 10 specialized domains. Built on Ubuntu 24.04 LTS (Noble Numbat) with the Linux... -
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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. ... -
8
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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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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10
Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who... -
11
pyfolio
Portfolio and risk analytics in Python
pyfolio is a Python library for performance and risk analysis of financial portfolios developed by Quantopian Inc. It works well with the Zipline open source backtesting library. At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple tear sheet analyzing a strategy. Quantopian also offers a fully managed service for professionals that includes... -
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PythonRobotics
Python sample codes and textbook for robotics algorithms
PythonRobotics is a Python code collection and textbook for learning robotics algorithms through readable examples. It covers practical topics such as localization, mapping, path planning, path tracking, control, SLAM, and autonomous navigation. The project is written to make each algorithm’s core idea easy to understand, rather than hiding the logic behind large frameworks. It keeps dependencies minimal so learners can focus on the math, implementation, and behavior of each robotics method....
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