Search Results for "clear linux"
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Showing 111 open source projects for "clear linux"
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Pearl
A Production-ready Reinforcement Learning AI Agent Library
Pearl is a production-ready reinforcement learning and contextual bandit agent library built for real-world sequential decision making. It is organized around modular components—policy learners, replay buffers, exploration strategies, safety modules, and history summarizers—that snap together to form reliable agents with clear boundaries and strong defaults. The library implements classic and modern algorithms across two regimes: contextual bandits (e.g., LinUCB, LinTS, SquareCB, neural... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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mac-cleanup-py
Python cleanup script for macOS
mac-cleanup-py is a powerful cleanup script for macOS. This project is a rewrite of the original mac-cleanup-sh rewritten in Python. -
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Magika
Fast and accurate AI powered file content types detection
Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for... -
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FL4Health
Library to facilitate federated learning research
FL4Health is a Vector Institute toolkit for building modular, clinically-focused FL pipelines. Tailored for healthcare, it supports privacy-preserving FL, heterogeneous data settings, integrated reporting, and clear API design. -
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NoneBot
Asynchronous multi-platform robot framework written in Python
Use NB-CLI to quickly build your own robot. 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... -
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch. Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries,... -
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FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a fast, Pythonic framework for building servers and clients using the Model Context Protocol (MCP). It abstracts away protocol complexity like serialization, validation, and error handling, letting developers focus entirely on their business logic. With simple decorators, you can expose Python functions as tools, resources, or prompts that AI agents can safely and efficiently use. FastMCP introduces clear abstractions—components, providers, and transforms—that make it easy to... -
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HanLP
Han Language Processing
HanLP is a multilingual Natural Language Processing (NLP) library composed of a series of models and algorithms. Built on TensorFlow 2.0, it was designed to advance state-of-the-art deep learning techniques and popularize the application of natural language processing in both academia and industry. HanLP is capable of lexical analysis (Chinese word segmentation, part-of-speech tagging, named entity recognition), syntax analysis, text classification, and sentiment analysis. It comes with... -
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GTFOBins
GTFOBins is a curated list of Unix binaries
GTFOBins is a curated catalog of Unix / POSIX system binaries and how they can be misused to bypass restrictions, escalate privileges, exfiltrate data, spawn shells, or otherwise act as “living off the land” tools in a compromised environment. It collects documented techniques for how everyday binaries (e.g. awk, bash, tar, scp) can be abused under constrained conditions. Indexed list of Unix binaries and documented misuse techniques. Examples of command invocations to exploit... -
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Skyvern
Automate browser-based workflows with LLMs and Computer Vision
Skyvern uses a combination of computer vision and AI to understand content on a webpage, making it adaptable to any website. Skyvern takes instructions in natural language, allowing it to execute complex objectives with simple commands. Skyvern is an API-first product. Workflows execute in the cloud, allowing it to run hundreds of workflows at the same time. Skyvern's AI decisions come with built-in explanations, providing clear summaries and justifications for every action. Support for... -
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City Map Poster Generator
Transform your favorite cities into beautiful, minimalist designs
maptoposter is a code-driven poster generator that turns any city into a minimalist, print-style map artwork with consistent typography and themed color palettes. It is built around a simple command-line flow where you pass a city and country, and the tool fetches the relevant map geometry and renders it into a clean composition that looks like a design product rather than a raw GIS export. The repository includes a library of predefined themes that change the overall look (for example,... -
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Google Fonts
Font files available from Google Fonts, and a public issue tracker
This is the central GitHub repository for Google Fonts, containing font binaries, metadata, and tools for uploading new typeface families. It serves as the staging area for fonts and follows stringent licensing structures. The top-level directories indicate the license of all files found within them. Subdirectories are named according to the family name of the fonts within. The /catalog subdirectory contains additional metadata, such as profile texts and portrait/avatar images of font... -
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Scout Suite
Multi-cloud security auditing tool
Scout Suite is an open-source multi-cloud security-auditing tool, which enables security posture assessment of cloud environments. Using the APIs exposed by cloud providers, Scout Suite gathers configuration data for manual inspection and highlights risk areas. Rather than going through dozens of pages on the web consoles, Scout Suite presents a clear view of the attack surface automatically. Scout Suite was designed by security consultants/auditors. It is meant to provide a point-in-time... -
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Simple Evals
Lightweight framework for evaluating large language model performance
simple-evals is a lightweight evaluation framework developed by OpenAI for quickly testing models against small, focused benchmarks. It is designed to help researchers and developers run targeted evaluations without the complexity of large-scale pipelines. By emphasizing simplicity, the framework makes it easy to define new tasks, run evaluations, and interpret results in a reproducible way. It is particularly useful for sanity checks, exploratory research, and comparing performance across... -
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CloudEvents
CloudEvents Specification
Events are everywhere. However, event producers tend to describe events differently. The lack of a common way of describing events means developers must constantly re-learn how to consume events. This also limits the potential for libraries, tooling and infrastructure to aide the delivery of event data across environments, like SDKs, event routers or tracing systems. The portability and productivity we can achieve from event data is hindered overall. CloudEvents is a specification for... -
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IndexTTS2
Industrial-level controllable zero-shot text-to-speech system
IndexTTS is a modern, zero-shot text-to-speech (TTS) system engineered to deliver high-quality, natural-sounding speech synthesis with few requirements and strong voice-cloning capabilities. It builds on state-of-the-art models such as XTTS and other modern neural TTS backbones, improving them with a conformer-based speech conditional encoder and upgrading the decoder to a high-quality vocoder (BigVGAN2), leading to clearer and more natural audio output. The system supports zero-shot voice... -
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AI Runner
Offline inference engine for art, real-time voice conversations
AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a... -
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nbstripout
strip output from Jupyter and IPython notebooks
Opens a notebook, strips its output, and writes the outputless version to the original file. Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS. This does mostly the same thing as the Clear All Output command in the notebook UI. You can download and install the latest version of nbstripout from PyPI, the Python package index. Strip output from IPython / Jupyter / Zeppelin notebook (modifies the file in-place). Usually, nbstripout is installed per... -
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Aider
Aider is AI pair programming in your terminal
Aider is an AI pair programming tool that runs directly in your terminal, helping developers build new projects or extend existing codebases faster and more confidently. It works alongside you like a coding partner, using powerful large language models to understand your code and implement precise changes. Aider creates a structured map of your entire repository, allowing it to handle large and complex projects effectively. It supports over 100 programming languages, making it flexible for... -
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Shapash
Explainability and Interpretability to Develop Reliable ML models
Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria. -
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
The Mathematics Dataset, developed by Google DeepMind, is a synthetic dataset designed to evaluate and train machine learning models on mathematical reasoning and symbolic manipulation. It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear... -
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LLaMA 3
The official Meta Llama 3 GitHub site
This repository is the former home for Llama 3 model artifacts and getting-started code, covering pre-trained and instruction-tuned variants across multiple parameter sizes. It introduced the public packaging of weights, licenses, and quickstart examples that helped developers fine-tune or run the models locally and on common serving stacks. As the Llama stack evolved, Meta consolidated repositories and marked this one deprecated, pointing users to newer, centralized hubs for models,... -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well... -
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ZenML
Build portable, production-ready MLOps pipelines
A simple yet powerful open-source framework that scales your MLOps stack with your needs. Set up ZenML in a matter of minutes, and start with all the tools you already use. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code....
