Search Results for "ai models"
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Showing 1783 open source projects for "ai models"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Core AI Models
Model export recipes, Python primitives, and Swift runtime utilities
Core AI Models is Apple’s repository for building and running on-device AI models with Core AI. It provides export recipes that convert supported open-source models into Core AI model files. It also includes Python primitives for authoring custom PyTorch models that are better suited for Apple platform deployment. The Swift package adds runtime utilities that help developers integrate exported models into macOS and iOS apps. ... -
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any... -
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AI as Workspace
An elegant AI chat client. Full-featured, lightweight
AI as Workspace, short for AI as Workspace, is an open-source AI client application that provides a unified interface for interacting with multiple large language models and AI tools within a single workspace environment. The platform is designed as a lightweight yet powerful desktop or web application that organizes AI interactions through structured workspaces. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external cloud models. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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AI-Flow
UI application to connect multiple AI models together
Open-source tool to seamlessly connect multiple AI models in repeatable flow. While a live demo is available for convenience, for the best experience we recommend running the application directly on your local machine. AI Flow is an open source, user-friendly UI application that empowers you to seamlessly connect multiple AI models together, specifically leveraging the capabilities of ChatGPT. -
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Operit AI
Powerful Android AI agent with tools, automation, and Linux shell
...Operit supports both local and remote AI models, including offline execution through frameworks like llama.cpp and MNN, helping preserve user privacy while maintaining flexibility. Operit also includes an intelligent memory system that stores, organizes, and retrieves user interactions to provide more personalized and context-aware responses. In addition, it offers workflow automation, plugin extensibility, & a rich tool ecosystem, making it suitable for advanced productivity. -
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Perception Models
State-of-the-art Image & Video CLIP, Multimodal Large Language Models
Perception Models is a state-of-the-art framework developed by Facebook Research for advanced image and video perception tasks. It introduces two primary components: the Perception Encoder (PE) for visual feature extraction and the Perception Language Model (PLM) for multimodal decoding and reasoning. The PE module is a family of vision encoders designed to excel in image and video understanding, surpassing models like SigLIP2, InternVideo2, and DINOv2 across multiple benchmarks. Meanwhile,... -
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AI Notes
Curated AI engineering notes on LLMs, generative models, and tools
ai-notes is a curated repository of notes focused on the evolving landscape of artificial intelligence, particularly generative models and large language models. It is designed to help software engineers quickly understand modern AI concepts, tools, and developments through structured documentation and research notes. It functions as a living knowledge base composed of numerous markdown files that organize topics such as text generation, image generation, AI infrastructure, and code generation models. ... -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. -
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Cybersecurity AI
Cybersecurity AI (CAI), the framework for AI Security
...Rather than being a single-purpose tool, CAI is positioned as a framework that supports building multiple security automations and integrating them into existing processes. It is designed for real-world usability, aiming to reduce friction for teams experimenting with AI agents in security operations, assessment, and response contexts. The framework emphasizes extensibility so users can connect models, tools, and supporting components depending on their environment and constraints. -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. -
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kubectl-ai
AI assistant for managing Kubernetes clusters from the terminal
...It can help perform tasks such as inspecting resources, retrieving logs, troubleshooting issues, and modifying cluster configurations. kubectl-ai supports both cloud-based and locally hosted language models, allowing it to adapt to different infrastructure and privacy requirements. -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
...There is an urgent demand to train models in a distributed environment. However, distributed training, especially model parallelism, often requires domain expertise in computer systems and architecture. It remains a challenge for AI researchers to implement complex distributed training solutions for their models. Colossal-AI provides a collection of parallel components for you. -
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OpenHiggsfield AI
A studio for image and video generation
OpenHiggsfield is an open-source browser studio for generating images and videos through multiple AI models from one interface. A single prompt composer handles both media types, while the selected model determines which generation workflow is used. Its catalog includes dozens of image and video models from several providers. Each model exposes only the settings it supports, such as aspect ratio, resolution, duration, audio, batch size, and prompt enhancement. ... -
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Shell-AI
LangChain powered shell command generator and runner CLI
Shell-AI is an open-source command-line interface utility that allows users to generate and execute shell commands using natural language prompts. Instead of requiring users to remember complex command syntax, the tool lets them describe their intent in plain English and automatically suggests commands that accomplish the task. The system is powered by large language models and integrates with frameworks such as LangChain to interpret user requests and translate them into executable shell instructions. ... -
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ai-cookbook
Examples and tutorials to help developers build AI systems
...The repository contains examples that demonstrate how to build AI workflows using modern tools such as large language models, autonomous agents, and external APIs. Developers can learn how to construct applications like intelligent assistants, automation pipelines, and AI-powered data analysis tools through step-by-step tutorials and ready-to-run scripts. The code examples are designed to emphasize practical architecture patterns that are commonly used in production environments, helping developers understand how to integrate AI services into software products. -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. ... -
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Stripe AI
One-stop shop for building AI-powered products and businesses
...It enables developers to connect large language models and AI agents with Stripe APIs so that automated systems can perform actions such as handling transactions, managing subscriptions, or processing financial events. The platform is particularly relevant for companies building AI-driven products that require monetization, usage-based billing, or programmable financial interactions. -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous... -
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JADX-AI-MCP
Plugin for JADX to integrate MCP server
JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. ... -
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XiaoZhi AI Chatbot
Build your own AI friend
xiaozhi-esp32 is an open-source project that guides users in building their own AI-powered conversational companion using the ESP32 microcontroller. The project provides detailed instructions on assembling the hardware, setting up the software, and integrating AI models to enable natural language interactions. This DIY approach offers an accessible entry point into AI and hardware development. -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. -
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AI App Lab
Implementing large models into scenario-based applications
AI App Lab is an open-source platform developed by Volcengine that provides tools, SDKs, and example applications for building real-world AI applications powered by large language models. The project focuses on helping developers bridge the gap between AI models and practical business use cases by offering a structured environment for creating production-ready AI systems. -
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AI-Trader
100% Fully-Automated Agent-Native Trading
AI-Trader is an open-source AI-powered quantitative trading framework designed to combine financial analysis, machine learning, and autonomous trading workflows into a unified research platform. The project integrates large language models, financial indicators, market analysis pipelines, and automated decision-making systems to support strategy generation and market prediction tasks. -
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
...By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal music libraries and generate curated playlists for different moods or listening contexts. AudioMuse-AI integrates with several popular self-hosted music servers including Jellyfin, Navidrome, and Emby, allowing users to extend existing media servers with advanced AI-powered recommendation capabilities. The system uses machine learning and audio analysis tools such as Librosa and ONNX models to extract features directly from audio tracks.
