Search Results for "artificial intelligence algorithm" - Page 19
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Showing 6653 open source projects for "artificial intelligence algorithm"
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Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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Aidea
Flutter-based cross-platform app integrating major AI models
AIdea is a comprehensive Flutter-based cross-platform app integrating major AI models—OpenAI GPT, Chinese models Tongyi Qianwen and Wenxin Yiyan, plus image models like Stable Diffusion for text-to-image, image-to-image, SDXL 1.0, super-resolution, and colorization. It includes a client app, server backend, and Docker deployment scripts for hosted setups. -
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Resume-Matcher
Improve your resumes with Resume Matcher
Resume-Matcher is a command-line application that compares resumes against job descriptions using natural language processing. It provides a compatibility score based on keyword relevance and highlights areas where the resume aligns—or doesn't—with the target role. Designed for job seekers and HR professionals, it helps improve resume tailoring and streamlines candidate screening. -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models -
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MCPHost
A CLI host application that enables Large Language Models (LLMs)
mcphost is a command-line host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). It provides a unified interface for engaging with various AI models and supports integration with multiple MCP servers, streamlining the development of AI-driven applications. -
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MCP Golang
Write Model Context Protocol servers in few lines of go code
mcp-golang is an unofficial Go implementation of the Model Context Protocol (MCP), allowing developers to write MCP servers and clients with minimal code. It aims to simplify the development process by providing a straightforward API for integrating MCP functionalities into Go applications. Comprehensive documentation is available to assist developers in getting started. -
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LLM.swift
LLM.swift is a simple and readable library
LLM.swift is a Swift package that enables developers to run Large Language Models (LLMs) directly on Apple devices, including iOS, macOS, and watchOS. By leveraging Apple's hardware and software optimizations, LLM.swift facilitates on-device natural language processing tasks, ensuring user privacy and reducing latency associated with cloud-based solutions. -
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Medusa
Framework for Accelerating LLM Generation with Multiple Decoding Heads
Medusa is a framework aimed at accelerating the generation capabilities of Large Language Models (LLMs) by employing multiple decoding heads. This approach allows for parallel processing during text generation, significantly enhancing throughput and reducing response times. Medusa is designed to be simple to implement and integrates with existing LLM infrastructures, making it a practical solution for scaling LLM applications. -
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Arch Gateway
The AI-native (edge and LLM) proxy for agents
Arch is an AI-native proxy designed to facilitate the development of agentic applications by handling complex tasks such as input clarification, agent routing, and seamless integration of prompts with tools for common tasks. It provides unified access and observability of Large Language Models (LLMs), enabling developers to build applications more efficiently. Arch supports both edge and LLM deployments, offering flexibility in various environments. -
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Distributed Llama
Connect home devices into a powerful cluster to accelerate LLM
Distributed Llama is an open-source project that enables users to connect multiple home devices into a powerful cluster to accelerate Large Language Model (LLM) inference. By leveraging tensor parallelism and high-speed synchronization over Ethernet, it allows for faster performance as more devices are added to the cluster. The system supports various operating systems, including Linux, macOS, and Windows, and is optimized for both ARM and x86_64 AVX2 CPUs. -
MongoDB Atlas | Run databases anywhereMongoDB Atlas allows you to build and run modern applications across 125+ cloud regions, spanning AWS, Azure, and Google Cloud. Its multi-cloud clusters enable seamless data distribution and automated failover between cloud providers, ensuring high availability and flexibility without added complexity.
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LMDeploy
LMDeploy is a toolkit for compressing, deploying, and serving LLMs
LMDeploy is a toolkit designed for compressing, deploying, and serving large language models (LLMs). It offers tools and workflows to optimize LLMs for production environments, ensuring efficient performance and scalability. LMDeploy supports various model architectures and provides deployment solutions across different platforms. -
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deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for... -
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DevoxxGenie
DevoxxGenie is a plugin for IntelliJ IDEA that uses local LLM's
Devoxx Genie is a fully Java-based LLM Code Assistant plugin for IntelliJ IDEA, designed to integrate with local LLM providers such as Ollama, LMStudio, GPT4All, Llama.cpp, and Exo but also cloud-based LLMs such as OpenAI, Anthropic, Mistral, Groq, Gemini, DeepInfra, DeepSeek, OpenRouter and Azure OpenAI. -
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Model Context Protocol (MCP) Servers
Model Context Protocol Servers
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. -
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Maid
Maid is a cross-platform Flutter app for interfacing with GGUF
Maid is a cross-platform Flutter app for interfacing with GGUF / llama.cpp models locally, and with Ollama and OpenAI models remotely. Maid is a cross-platform free and open source application for interfacing with llama.cpp models locally, and remotely with Ollama, Mistral, Google Gemini and OpenAI models remotely. Maid supports Sillytavern character cards to allow you to interact with all your favorite characters. Maid supports downloading a curated list of Models in-app directly from... -
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PyKEEN
A Python library for learning and evaluating knowledge graph embedding
PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-modal information). PyKEEN is a Python package for reproducible, facile knowledge graph embeddings. PyKEEN has a function pykeen.env() that magically prints relevant version information about PyTorch, CUDA, and your operating system that can be used for debugging. If you’re in a Jupyter Notebook, it will be pretty-printed as an HTML table. -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
NMA Computational Neuroscience course. We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you... -
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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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SkyPilot
SkyPilot: Run AI and batch jobs on any infra
SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface. -
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promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API. -
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embedchain
Framework to easily create LLM powered bots over any dataset
Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds. -
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Vercel AI SDK
Build AI-powered applications with React, Svelte, Vue, and Solid
The Vercel AI SDK is a library for building AI-powered streaming text and chat UIs. -
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solo-learn
Library of self-supervised methods for visual representation
A library of self-supervised methods for visual representation learning powered by Pytorch Lightning. A library of self-supervised methods for unsupervised visual representation learning powered by PyTorch Lightning. We aim at providing SOTA self-supervised methods in a comparable environment while, at the same time, implementing training tricks. The library is self-contained, but it is possible to use the models outside of solo-learn. -
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Yandex Smart Home
Adds support for Yandex Smart Home (Alice voice assistant)
Adds support for Yandex Smart Home (Alice voice assistant) into Home Assistant. The component allows you to add devices from Home Assistant to the Yandex smart home platform and manage them from any device with Alice. The component runs on Home Assistant version 2023.2 or later. -
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LangChain.js
Building applications with LLMs through composability
Building applications with LLMs through composability. Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. This is built to... -
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OpenNMT-tf
Neural machine translation and sequence learning using TensorFlow
OpenNMT is an open-source ecosystem for neural machine translation and neural sequence learning. OpenNMT-tf is a general-purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support sequence-to-sequence mapping, sequence tagging, sequence classification, language modeling. Models are described with code to allow training custom architectures and overriding default behavior. For example, the...
