Search Results for "fast" - Page 11
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Showing 836 open source projects for "fast"
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PyTorch3D
PyTorch3D is FAIR's library of reusable components for deep learning
...It’s designed to make it easy to build and train neural networks that work directly with 3D data such as meshes, point clouds, and implicit surfaces. The library provides fast GPU-accelerated implementations of rendering pipelines, transformations, rasterization, and lighting—making it possible to compute gradients through full 3D rendering processes. Researchers use it for tasks like shape generation, reconstruction, view synthesis, and visual reasoning. PyTorch3D also includes utilities for loading, transforming, and sampling 3D assets, so models can be trained end-to-end from 2D supervision or partial data. ... -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. ... -
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Infinity
Low-latency REST API for serving text-embeddings
Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers. -
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NeuralForecast
Scalable and user friendly neural forecasting algorithms.
NeuralForecast offers a large collection of neural forecasting models focusing on their performance, usability, and robustness. The models range from classic networks like RNNs to the latest transformers: MLP, LSTM, GRU, RNN, TCN, TimesNet, BiTCN, DeepAR, NBEATS, NBEATSx, NHITS, TiDE, DeepNPTS, TSMixer, TSMixerx, MLPMultivariate, DLinear, NLinear, TFT, Informer, AutoFormer, FedFormer, PatchTST, iTransformer, StemGNN, and TimeLLM. There is a shared belief in Neural forecasting methods'... -
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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Pants Build System
The Pants Build System
Pants 2 is a fast, scalable, user-friendly build system for codebases of all sizes. It's currently focused on Python, Go, Java, Scala, Kotlin, Shell, and Docker, with support for other languages and frameworks coming soon. A lot of effort has gone into making Pants easy to adopt, easy to use and easy to extend. We're super excited to bring Pants' distinctive features to Go, Java, Python, Scala, Kotlin, and Shell users. -
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Sippts
Set of tools to audit SIP based VoIP Systems
...Most security tools can be used for illegal purposes, but the purpose of this tool is to check the security of your own servers and not to use to do bad things. I am not responsible for the misuse of this tool. Sippts is a set of tools to audit VoIP servers and devices using SIP protocol. Sipscan is a fast scanner for SIP services that uses multithread. Sipscan can check several IPs and port ranges and it can work over UDP or TCP. Sipexten identifies extensions on a SIP server. Also tells you if the extension line requires authentication or not. Sipexten can check several IPs and port ranges. -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL benchmarks (similar to what has been done for torchvision). ... -
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AWX
A web-based user interface built on top of Ansible
AWX provides a web-based user interface, REST API, and task engine built on top of Ansible. It is one of the upstream projects for Red Hat Ansible Automation Platform. Starting in version 18.0, the AWX Operator is the preferred way to install AWX. AWX can also alternatively be installed and run in Docker, but this install path is only recommended for development/test-oriented deployments, and has no official published release. Uses naming and structure consistent with the AWX HTTP API.... -
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Powerline
Statusline plugin for vim with prompts for several other applications
Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome, i3 and Qtile. Powerline was completely rewritten in Python to get rid of as much vimscript as possible. This has allowed much better extensibility, leaner and better config files, and a structured, object-oriented codebase with no mandatory third-party dependencies other than a Python interpreter. Using Python has allowed unit testing of... -
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Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline... -
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fvcore
Collection of common code shared among different research projects
fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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TurboGears
Python web framework with full-stack layer
TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. TurboGears helps you get going fast and gets out of your way when you want it! TurboGears can be used both as a full stack framework or as a microframework in single-file mode. TurboGears 2 is built on top of the experience of several next-generation web frameworks including TurboGears 1 (of course), Django, and Rails. All of these frameworks had limitations that frustrated us, and TG2 was built as an answer to that frustration. ... -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. -
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Pelican
Static site generator that supports Markdown and reST syntax
...Publication of articles in multiple languages. Generation of Atom and RSS feeds. Code syntax highlighting via Pygments. Import existing content from WordPress, Dotclear, or RSS feeds. Fast rebuild times due to content caching and selective output writing. Extensible via a rich plugin ecosystem, Pelican Plugins. Pelican considers “articles” to be chronological content, such as posts on a blog, and thus associated with a date. The idea behind “pages” is that they are usually not temporal in nature and are used for content that does not change very often (e.g., “About” or “Contact” pages). ... -
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marqo
Tensor search for humans
...Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and text-to-image search and analytics. Marqo adapts and stores your data in a fully schemaless manner. It combines tensor search with a query DSL that provides efficient pre-filtering. ... -
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DocArray
The data structure for multimodal data
...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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Jina
Build cross-modal and multimodal applications on the cloud
...Intuitive design pattern for high-performance microservices. Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. Improved engineering efficiency thanks to the Jina AI ecosystem, so you can focus on innovating with the data applications you build. -
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fastai
Deep learning library
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying... -
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OAGI Python SDK
Python SDK for the Computer Use model Lux, developed by OpenAGI
OAGI Python SDK is a Python client library for the Lux computer-use model that turns Lux into a programmable automation layer for operating human-facing software via vision and actions. It exposes the OAGI API in an ergonomic way, letting you trigger Lux in three main modes: Tasker for precise scripted sequences, Actor for fast one-shot tasks, and Thinker for open-ended, multi-step objectives. The SDK is designed around “computer use” as a paradigm, where the AI actually navigates interfaces, clicks, types, scrolls, and reads the screen through screenshots instead of only calling APIs. It provides high-level asynchronous agents (like AsyncDefaultAgent and AsyncActor) that encapsulate the loop of capturing screenshots, sending them to Lux, interpreting responses, and executing UI actions with PyAutoGUI. ... -
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Image-Editor
AI based photo editing website for changing image background
Welcome to Image-Editor, the AI-based photo editing website that lets you change backgrounds, colors, crop, sharpen images, and much more with just a single click. With exceptional image quality and fast processing times, Image-Editor is the ultimate tool for all your photo editing needs. To get started, simply run pip install -r requirements.txt to download all the necessary libraries. Then to, create a new Django project using django-admin startproject Website1, replacing 'Website1' with the name of your choice. Image-Editor uses Python's cv2 library, which provides an easy and efficient way to work with images and videos, including a wide range of image processing and computer vision algorithms. ... -
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AutoClicker
A Modern Fully-Fledged Mouse and Keyboard AutoClicker
ZClicker (AutoClicker) is a fast and modern autoclicker for Windows. Bored of old-looking autoclickers? ZClicker provides a clean, easy-to-use interface with powerful features for fast and reliable automation. The free version includes essential autoclicking features, while ZClicker Pro unlocks advanced functionality such as background window clicking, click position control, and customizable hotkeys -
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Little cms color engine
An ICC-based CMM for color management
Little cms is a color management library. Implements fast transforms between ICC profiles. It is focused on speed, and is portable across several platforms (MIT license) -
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DESERT OS Linux
Beautiful XFCE distribution
DESERT OS Linux is a fast, elegant Ubuntu-based Linux from Ukraine. It offers a refined XFCE experience optimized for both modern and legacy hardware. Key Features: - Lightweight: Fast performance with low resource usage. - Beautiful UI: Polished, modern look right out of the box. - Tiling Support: Integrated Cortile for easy window management. - Package Choice: Deb, Flatpak, Pacstall, Appimage, Windows msi/exe -
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CachyOS
Blazingly Fast & Customizable Linux distribution
CachyOS - Arch Linux Based Distribution With Heavy Optimizations & Multi-Architectures For Ultimate Desktop Experience Filesystems: - btrfs - zfs - ext4 - xfs - f2fs Our installer will auto detect which micro architecture your machine got, if x86-64-v3 or x86-64-v4 is detected it will automatically use the optimized packages, which is around a 10 % performance improvement. Desktop Environments: - KDE - CuteFish - i3 - Gnome - Openbox - Wayfire - Xfce - LXQT -...
