Search Results for "processor"
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Showing 77 open source projects for "processor"
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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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yq JSON
Command-line YAML, XML, TOML processor
Before using yq, you also have to install its dependency, jq. See the jq installation instructions for details and directions specific to your platform. On macOS, yq is also available on Homebrew use brew install python-yq. -
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iptv-api
IPTV live stream source automatic update tool
...Results can be categorized, cached, logged, analyzed, frozen, and restored as source quality changes. Deployment options include GitHub Actions workflows, a command-line interface, a graphical interface, and Docker images for several processor architectures. -
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Qiskit
Qiskit is an open-source SDK for working with quantum computers
...Qiskit includes a comprehensive set of quantum gates and a variety of pre-built circuits so users at all levels can use Qiskit for research and application development. The transpiler translates Qiskit code into an optimized circuit using a backend’s native gate set, allowing users to program for any quantum processor or processor architecture with minimal inputs. Users can run and schedule jobs on real quantum processors, and employ Qiskit Runtime to orchestrate quantum programs on cloud-based CPUs, QPUs, and GPUs. -
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GenAI Processors
GenAI Processors is a lightweight Python library
GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. ... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It... -
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Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement... -
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Swirl
Swirl queries any number of data sources with APIs
Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank... -
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pyexpander
A powerful macro processor based on python
Pyexpander is a powerful macro processor based on python. Instead of simple macro replacement it offers evaluation of arbitrary python expressions and execution of python code. Pyexpander is Turing Complete. -
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KherveTeX
Visual LaTeX editor: edit like Word, output like LaTeX, track with Git
KherveTeX is a document editor that produces real LaTeX and tracks every change with Git — giving you the ease of a word processor and the typesetting quality of LaTeX, without ever touching a .tex file by hand. Write documents visually with familiar formatting tools. KherveTeX maintains a clean document model and serializes it to LaTeX, then compiles to PDF via the bundled Tectonic engine — no external LaTeX installation required. The PDF preview updates as you work. -
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This project delivers Linux support (USB driver and Tools) for a Digital Signal Processor (DSP) cards of the Signal Ranger series, see http://www.softdb.com/product_dsp.shtml for details) connected to a Linux host via USB.
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AIMi AI Aimbot
AIMi its an AI aimbot, it work by real-time object detection
...It is built around neural network detection and OpenCV processing rather than direct modification of game files. The project presents itself as a beta implementation, with current behavior depending heavily on processor performance, model accuracy, and screen conditions. It includes a simple object-detector interface so users can see how the system recognizes targets during testing. The repository describes a CPU-heavy version with limited GPU usage and notes plans for faster GPU-oriented improvements. Because it is designed around game targeting behavior, it should only be discussed and used in authorized, accessibility-focused, private, or noncompetitive environments. -
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openWrt-snort
Image of OpenWrt OS, with snort community featured in.
Image of OpenWrt OS, with snort community featured in, for Raspberry Pi 4/ 4B+ and 400, basically for Processor BCM2711. Installed Snort Community Model to Intrusion Detection system. Prevention system not installed. eth0 used as output/ LAN socket, to run internet and access router. eth1, which can be USB -> Ethernet port, is used as WAN port, to connect Pi board to Internet IP. to flash img file, you can restore in SD card, or use Balena Etcher to flash. or you can use DD commend of UNIX. ... -
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eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original... -
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LibreOffice
A free and powerful office suite
LibreOffice is a free and powerful office suite, and a successor to OpenOffice. Its clean interface and feature-rich tools help you unleash your creativity and enhance your productivity. LibreOffice is Free and Open Source Software (FOSS) – development is open to new talent and new ideas, and our software is tested and used daily by a large and devoted user community. Your documents will look professional and clean, regardless of their purpose: a letter, a master thesis, a brochure,... -
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VAMS
Virtual Assistant Maintenance System
Virtual Assistant Maintenance System also knowns as VAMS is an AI software application, that helps users with some computer maintenance issues. Application Requirements: Operating System: Windows 8.1/10 /11 Processor: Intel Core i5 or equivalent RAM: 4GB or higher Free Disk Space: 500MB -
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gjots2
hierarchical note jotter - organise your ideas, notes, facts in a tree
2023/04/04: MIGRATED TO https://gitlab.com/wef/gjots2 gjots2 is a fairly simple jotter (outline processor) application for your desktop. See http://bhepple.freeshell.org/gjots -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
...Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. The Docker images are built from the Dockerfiles in docker/. The Dockerfiles are grouped based on the version of TensorFlow Serving they support. Each supported processor type (e.g. "cpu", "gpu", "ei") has a different Dockerfile in each group. If your are testing locally, building the image is enough. But if you want to your updated image in SageMaker, you need to publish it to an ECR repository in your account. You can also run your container locally in Docker to test different models and input inference requests by hand. -
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FARM
Fast & easy transfer learning for NLP
...Switch between heads or combine them for multitask learning. Full Compatibility with HuggingFace Transformers' models and model hub. Smooth upgrading to newer language models. Integration of custom datasets via Processor class. Powerful experiment tracking & execution. -
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
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EasyArch
Arch Linux Installer ISO
A simple yet full featured Archlinux installer ISO. Minimum system requirements- Processor - 2 core 64 bit Ram - 1 GB HDD space - 10 GB If you are looking for another linux distro, then you are at wrong place, this is not a new or separate distribution. It is just a live ISO to provide simple and easy way to get Archlinux up and running in very little time and with or without internet connection. Yes, you read it right, you can install Archlinux without internet with this ISO. ... -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
...The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python version and processor type. The Docker images, used to run training & inference jobs, are built from both corresponding "base" and "final" Dockerfiles. The "base" Dockerfile encompasses the installation of the framework and all of the dependencies needed. All "final" Dockerfiles build images using base images that use the tagging scheme. -
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stage0
A set of minimal dependency bootstrap binaries
This is a set of manually created hex programs in a Cthulhu Path to madness fashion. Which only have the goal of creating a bootstrapping path to a C compiler capable of compiling GCC, with only the explicit requirement of a single 1 KByte binary or less. Additionally, all code must be able to be understood by 70% of the population of programmers. If the code can not be understood by that volume, it needs to be altered until it satisfies the above requirement. -
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Deepvoice3_pytorch
PyTorch implementation of convolutional neural networks
An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning. -
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TeXML is an XML vocabulary for TeX. The processor transforms the TeXML markup into the TeX markup, escaping special and out-of-encoding characters. The intended audience is developers who automatically generate [La]TeX or ConTeXt files.
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pyspider
A powerful Spider(Web Crawler) system in Python
...Every component, including message queue, is running in their own process/thread, and replaceable. That means, when process is slow, you can have many instances of processor and make full use of multiple CPUs, or deploy to multiple machines. This architecture makes pyspider really fast. benchmarking. Since pyspider has various components, you can just run pyspider to start a standalone and third service free instance. Or using MySQL or MongoDB and RabbitMQ to deploy a distributed crawl cluster. To deploy pyspider in product environment, running component in each process and store data in database service is more reliable and flexible. ...
