Search Results for "mac framework" - Page 23
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Showing 1279 open source projects for "mac framework"
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4M
4M: Massively Multimodal Masked Modeling
4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things... -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or... -
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Daft
Distributed DataFrame for Python designed for the cloud
Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python Dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run... -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote... -
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DeepLabCut
Implementation of DeepLabCut
DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates or for... -
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Qlib
Qlib is an AI-oriented quantitative investment platform
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. With Qlib, users can easily try their ideas to create better Quant investment strategies. At the module level, Qlib is a platform that consists of... -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
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Ollamac
Mac app for Ollama
Ollamac is an open-source native macOS application that provides a graphical interface for interacting with local large language models running through the Ollama inference framework. The project was created to simplify the process of using local AI models, which typically require command-line interaction, by offering a clean and intuitive desktop interface. Through this interface, users can run and chat with a variety of LLM models installed through Ollama directly on their own machines.... -
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Deep Agents
The batteries-included agent harness
Deep Agents is an open-source, batteries-included agent harness designed for long-running, multi-step AI work. It provides an opinionated agent setup while allowing developers to override or replace individual pieces without forking the project. The framework is model-agnostic and works with tool-calling models from hosted providers, open-weight deployments, or local runtimes. Built on LangGraph, it includes persistence, checkpointing, streaming, and production-oriented orchestration. Agents... -
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Skills for coding agents
Skills for coding agents
BuilderIO Skills is a collection of small, composable skills for coding agents. It is made for teams that want agents to perform better in planning, review, orchestration, validation, documentation discipline, and clear communication. Instead of acting like a heavy process framework, it lets teams install only the skills they need and adapt them to their project. The catalog includes tools for visual planning, visual PR recaps, agent audits, plan comparison, autonomous execution, model... -
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Train LLM From Scratch
A straightforward method for training your LLM
Train LLM From Scratch is an educational PyTorch project that shows how to build and train a transformer-based language model from the ground up. It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model. It supports training smaller or larger models, including million- and... -
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ZeroBot-Plugin
OneBot plugin based on ZeroBot
ZeroBot-Plugin is a Go-based plugin collection for the ZeroBot ecosystem and OneBot-compatible bot frameworks. It packages many bot capabilities into a ready-to-run project that can be used through release binaries, direct local execution, or custom compilation. The repository is aimed mainly at QQ and OneBot-style chatbot deployments, with plugins that can be enabled, modified, or extended by developers. It is designed for users who want a richer bot feature set without writing every plugin... -
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Agent Control
Centralized agent control plane for governing runtime agent behavior
Agent Control is a centralized control plane for governing AI agent behavior at runtime across different frameworks and deployment environments. It lets teams define controls once and apply them consistently to agents without rewriting the agent’s core code. The platform evaluates agent inputs and outputs against configurable policies to reduce risks such as prompt injection, unsafe responses, sensitive data exposure, and policy drift. It is designed for production environments where... -
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OpenSwarm
Claude code for everything except coding
OpenSwarm is an open-source multi-agent system that lets users create full deliverables from a single terminal prompt. Instead of relying on one general-purpose assistant, it coordinates a team of specialized agents through an orchestrator. The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch... -
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Mike
OSS AI Legal Platform
Mike is a software project that appears to focus on automation or tooling, likely designed to streamline workflows related to development, deployment, or data processing. It may function as a command-line utility or lightweight framework that integrates with existing systems to improve efficiency. The project emphasizes simplicity and clarity, providing focused functionality without unnecessary overhead. Its design likely supports extensibility, allowing users to adapt it to specific use... -
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Rewriting Project Claw Code
Ensure consistency and alignment between different codebases
Rewriting Project Claw Code is a development tool or framework designed to ensure consistency and alignment between different codebases, environments, or implementations. It focuses on maintaining parity across systems, which is particularly important in distributed architectures or multi-platform applications. The project provides mechanisms to compare, validate, and synchronize code or behavior, helping teams avoid discrepancies that can lead to bugs or inconsistencies. It may include... -
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Phantom
An AI co-worker with its own computer
Phantom is an experimental AI agent framework designed to simulate autonomous workflows with an emphasis on stealth, abstraction, and flexible execution across environments. The system likely focuses on orchestrating tasks in a way that minimizes friction between user intent and execution, allowing agents to operate with minimal direct supervision. Its architecture suggests modular components that handle planning, execution, and context management independently, enabling scalable and... -
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Claude Code Architecture Study
Research on Coding Agents
Claude Code Architecture Study is an educational and experimental repository designed to teach developers how to build, configure, and understand AI coding agents from first principles. The project focuses on breaking down the architecture of agentic systems, including how models perceive context, make decisions, and execute actions in a coding environment. It likely provides step-by-step examples, conceptual explanations, and practical implementations that guide users through creating their... -
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TurboQuant+
Implementation of TurboQuant (ICLR 2026)
TurboQuant Plus is an extended and enhanced version of quantization tooling aimed at improving neural network efficiency through advanced compression and optimization strategies. It builds upon the concept of reducing model precision to accelerate inference while attempting to maintain or recover accuracy through refined techniques. The project explores additional enhancements such as improved calibration, adaptive quantization, and potentially hybrid precision approaches that combine... -
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Ralph Orchestrator
An improved implementation of the Ralph Wiggum technique
Ralph Orchestrator is an AI workflow orchestration system designed to coordinate multiple agents, tools, and processes into structured pipelines that can execute complex tasks autonomously. It provides a framework for defining workflows where different components, such as LLMs, APIs, and custom functions, collaborate to achieve specific objectives. The system emphasizes modularity and composability, allowing developers to design workflows as reusable building blocks that can be combined or... -
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PromptBin
A free guide for learning to create ChatGPT3 Prompts
PromptBin is an open-source prompt engineering resource and lightweight web application designed to help users discover, organize, and reuse effective prompts for large language models like ChatGPT. At its core, the project acts as a curated and structured library of prompts across a wide variety of use cases, including writing, brainstorming, debugging, and coding, making it particularly useful for both beginners and advanced users. The repository is also intended as a foundation for... -
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NVIDIA Model Optimizer
A unified library of SOTA model optimization techniques
Model Optimizer is a unified library that provides state-of-the-art techniques for compressing and optimizing deep learning models to improve inference efficiency and deployment performance. It brings together multiple optimization strategies such as quantization, pruning, distillation, and speculative decoding into a single cohesive framework. The library is designed to reduce model size and computational requirements while maintaining accuracy, making it particularly valuable for deploying... -
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NeMo Retriever Library
Document content and metadata extraction microservice
NeMo Retriever Library is a scalable microservice framework designed for extracting, structuring, and enriching content from documents to support downstream generative AI applications. It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient... -
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VIPER
AI-powered red team platform for adversary simulation toolkit
Viper is a comprehensive red teaming and adversary simulation platform designed to support cybersecurity professionals in conducting advanced security assessments. It integrates a wide range of tools and capabilities required for penetration testing, post-exploitation, and attack simulation workflows into a unified environment. Viper emphasizes ease of use through a graphical interface, allowing users to manage complex operations without relying solely on command-line tools. It includes a...
