Search Results for "k-stor"
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Showing 376 open source projects for "k-stor"
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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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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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k-skill
Skill collection for Koreans - SRT, KTX, KakaoTalk, Hangul
...The project emphasizes simplicity and modularity, making it easier to manage large collections of skills in complex environments. It also supports extensibility, enabling users to define custom skills tailored to their needs. Overall, k-skill serves as a foundational layer for building structured and scalable AI agent capabilities. -
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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Kronos
A Foundation Model for the Language of Financial Markets
Kronos is a specialized open-source foundation model designed for analyzing and predicting financial market data using time-series representations of candlestick patterns. It is built as a decoder-only Transformer model trained specifically on K-line data, which captures open, high, low, close, and volume information across multiple global exchanges. The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process market behavior similarly to language. This allows Kronos to perform a variety of quantitative tasks such as forecasting, pattern recognition, and anomaly detection within financial datasets. ... -
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VimFx
Vim keyboard shortcuts for Firefox
VimFx brings Vim-inspired navigation and command mode to Firefox via WebExtensions. It allows users to control the browser with keyboard shortcuts (h/j/k/l), open tabs, follow links, find text, and execute commands—all without a mouse. It mimics Vim’s Normal/Insert modes, enabling power users to browse efficiently. It is open-source and integrates seamlessly with Firefox. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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Hotkey
Trigger an action on an element with a keyboard shortcut
Trigger an action on a target element when the hotkey (key or sequence of keys) is pressed on the keyboard. This triggers a focus event on form fields or a click event on other elements. By default, hotkeys are extracted from a target element's data-hotkey attribute, but this can be overridden by passing the hotkey to the registering function (install) as a parameter. -
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bitsandbytes
Accessible large language models via k-bit quantization for PyTorch
bitsandbytes is an open-source library designed to make training and inference of large neural networks more efficient by dramatically reducing memory usage. Built primarily for the PyTorch ecosystem, the library introduces advanced quantization techniques that allow models to operate using reduced numerical precision while maintaining high accuracy. These optimizations enable large language models and other deep learning architectures to run on hardware with limited memory resources,... -
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Canvas LMS
The open LMS by Instructure, Inc.
Canvas LMS is a full-featured learning management system designed for K–12, higher-ed, and professional training, with a strong emphasis on usability and openness. Instructors build courses from modular content—pages, assignments, discussions, quizzes—and organize them into learning paths with prerequisites and due dates. Rich grading tools like SpeedGrader streamline assessment with rubrics, inline annotations, and audio/video feedback, while the gradebook supports weighting, outcomes, and late/missing policies. ... -
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Nebula libp2p DHT
A libp2p DHT crawler, monitor, and measurement tool
A libp2p DHT crawler and monitor that tracks the liveness of peers. The crawler connects to DHT bootstrap peers and then recursively follows all entries in their k-buckets until all peers have been visited. The crawler supports the IPFS, Filecoin, Polkadot, Kusama, Rococo, Westend networks and more. The crawler can store its results as JSON documents or in a postgres database - the --dry-run flag prevents it from doing either. Nebula will print a summary of the crawl at the end instead. A crawl takes ~5-10 min depending on your internet connection. ... -
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GoAWK
A POSIX-compliant AWK interpreter written in Go, with CSV support
GoAWK now uses a bytecode compiler and includes native support for CSV files. AWK is a fascinating text processing language, and The AWK Programming Language is a wonderfully concise book describing it. The A, W, and K in AWK stand for the surnames of the three original creators: Alfred Aho, Peter Weinberger, and Brian Kernighan. Kernighan is also an author of The C Programming Language (“K&R”), and the two books have that same each-page-packs-a-punch feel. AWK was released in 1977, which makes it over 40 years old! Not bad for a domain-specific language that’s still used for one-liners on Unix command lines everywhere. ... -
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Zinnia
Runtime for worker nodes executing modules
Zinnia is a runtime for Filecoin Station modules. It provides a sandboxed environment to execute untrusted code on consumer-grade computers. Zinnia is a sandboxed and resource-limited runtime for distributed workers. This crate provides the zinnia executable to run modules locally, e.g. while developing. -
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DocArray
The data structure for multimodal data
...Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases. -
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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
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kubeinvaders
Gamified Chaos Engineering Tool for Kubernetes
This project is part of the landscape of Cloud Native Computing Foundation in the Observability and Analysis - Chaos Engineering section. Backed by the teams at platform engineering.it and devopstribe.it, which provides enterprise-grade features and certified resilience services for your Kubernetes infrastructure. -
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Hotkeys JS
A robust Javascript library for capturing keyboard input
hotkeys-js is a tiny, framework-agnostic library for binding keyboard shortcuts in the browser, from simple key presses to complex combos and sequences. It provides a declarative API to register handlers like ctrl+k, shift+alt+p, or g g, and it normalizes key behavior across major browsers. The library includes scoping, so the same shortcut can trigger different actions depending on page context, and it offers filters to ignore inputs when the user is typing in form fields. You can enable or disable groups of shortcuts dynamically, making it well suited for SPAs and dashboard apps. ... -
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better-escape.nvim
Map keys without delay when typing
A lot of people have mappings like jk or jj to escape insert mode. The problem with these mappings is that whenever you type a j, neovim wait about 100-500ms (depending on your timeoutlen) to see if you type a j or a k because these are mapped. Only after that time, the j will be inserted. Then you always get a delay when typing a j. -
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TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question... -
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DashMap
Blazing fast concurrent HashMap for Rust
...DashMap tries to implement an easy-to-use API similar to std::collections::HashMap with some slight changes to handle concurrency. DashMap tries to be very simple to use and to be a direct replacement for RwLock<HashMap<K, V>>. To accomplish these goals, all methods take &self instead of modifying methods taking &mut self. This allows you to put a DashMap in an Arc<T> and share it between threads while still being able to modify it. DashMap puts great effort into performance and aims to be as fast as possible. If you have any suggestions or tips do not hesitate to open an issue or a PR. -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on... -
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Kubie
A more powerful alternative to kubectx and kubens
kubie is an alternative to kubectx, kubens, and the k on prompt modification script. It offers context switching, namespace switching, and prompt modification in a way that makes each shell independent from others. It also has support for split configuration files, meaning it can load Kubernetes contexts from multiple files. You can configure the paths where Kubie will look for contexts, see the settings section. -
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Machine learning basics
Plain python implementations of basic machine learning algorithms
...Instead of relying on external machine learning libraries, the algorithms are implemented from scratch so that users can explore the mathematical logic and computational structure behind each technique. The repository includes notebooks that demonstrate classic algorithms such as linear regression, logistic regression, k-nearest neighbors, decision trees, support vector machines, and clustering techniques. Each notebook typically combines explanatory text, Python code, and visualizations to illustrate how the algorithm operates and how it can be applied to datasets. -
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HyperTools
A Python toolbox for gaining geometric insights
...Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot. -
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MetaVoice-1B
Foundational model for human-like, expressive TTS
MetaVoice — in the form of its source repository “metavoice-src” — is a large-scale text-to-speech (TTS) model. Specifically, the base model (MetaVoice-1B) uses around 1.2 billion parameters and has been trained on a massive dataset — reportedly around 100,000 hours of speech data. The goal is to provide human-like, expressive, and flexible TTS: able to generate natural-sounding speech that can handle diverse inputs and likely generalize over voice styles, intonation, prosody, and perhaps... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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MARS5
MARS5 speech model (TTS) from CAMB.AI
MARS5-TTS is CAMB.AI’s open-source English speech model designed for high-quality text-to-speech and voice emulation. It uses a two-stage architecture that combines an autoregressive (AR) model with a non-autoregressive (NAR) model, giving it both expressiveness and speed. The model is built to handle prosodically challenging content such as sports commentary, anime dialogue, and other high-energy or highly varied speech patterns with realistic rhythm and intonation. To control speaker...
