Search Results for "hash-linux" - Page 65
Sort By:
Showing 16311 open source projects for "hash-linux"
View related business solutions-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
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.
-
1
ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence.... -
2
clip-retrieval
Easily compute clip embeddings and build a clip retrieval system
clip-retrieval is an open-source toolkit designed to build large-scale semantic search systems for images and text by leveraging CLIP embeddings to enable multimodal retrieval. It allows developers to compute embeddings for both images and text efficiently and then index them for fast similarity search across massive datasets. The system is optimized for performance and scalability, capable of processing tens or even hundreds of millions of embeddings using GPU acceleration. It includes... -
3
Swarms
Enterprise multi-agent orchestration framework for scalable AI apps
Swarms is an enterprise-grade multi-agent orchestration framework designed to help developers build, manage, and scale collaborative AI systems composed of multiple agents. It provides a structured infrastructure for coordinating agents in hierarchical, parallel, or sequential workflows, enabling complex task execution across distributed components. It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale... -
4
PySINDy
A package for the sparse identification of nonlinear dynamical systems
PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a... -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
5
Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph... -
6
NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference... -
7
Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
Search with Lepton is an open source demonstration project that shows how to build a conversational search engine using the Lepton AI framework. It combines traditional web search with large language models to provide natural language answers to user queries. It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. The implementation is intentionally minimal, containing fewer than 500 lines of code... -
8
RecAI
Bridging LLM and Recommender System
RecAI is an open-source research platform developed by Microsoft to explore how large language models can be integrated into modern recommender systems. Traditional recommender systems rely on structured behavioral data such as user interactions and item embeddings, while large language models excel at understanding language and reasoning about user preferences. RecAI aims to bridge these two domains by creating architectures and training methods that allow LLMs to function as intelligent... -
9
Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
10
R-KV
Redundancy-aware KV Cache Compression for Reasoning Models
R-KV is an open-source research project that focuses on improving the efficiency of large language model inference through key-value cache compression techniques. Modern transformer models rely heavily on KV caches during autoregressive decoding, which store intermediate attention states to accelerate generation. However, these caches can consume large amounts of memory, especially in reasoning-oriented models with long context windows. R-KV introduces a method for compressing the KV cache... -
11
SwanLab
An open-source, modern-design AI training tracking and visualization
SwanLab is an open-source experiment tracking and visualization platform designed to help machine learning engineers monitor, compare, and analyze the training of artificial intelligence models. The tool records training metrics, hyperparameters, model outputs, and experiment configurations so that developers can easily understand how different experiments perform over time. It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance... -
12
Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer... -
13
Cube Studio
Cube Studio open source cloud native one-stop machine learning
Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data... -
14
MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching.... -
15
Agentic Data Scientist
An end-to-end Data Scientist
Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. Each agent is designed to independently call functions, interact with data... -
16
Context Engineering
A frontier, first-principles handbook
Context Engineering is a comprehensive, open-source project serving as a first-principles handbook for the emerging discipline of context design and optimization in AI. Moving beyond traditional prompt engineering, this repository defines and explores how to craft and provide complete context payloads — not just single prompts — to large language models so they can perform tasks more reliably and intelligently. It takes inspiration from thought leaders like Andrej Karpathy and bridges theory... -
17
Open Wearables
Self-hosted platform to unify wearable health data
Open Wearables is an open-source initiative that aims to provide a community-driven ecosystem for wearable device software and interoperability by connecting sensor data, activity tracking, and health insights across multiple platforms and devices. Instead of relying on closed vendor ecosystems, the project provides standardized data models and APIs that let developers and hobbyists collect, sync, and analyze biometric and environmental data from wearables, DIY sensors, and open hardware... -
18
AnyTool
AnyTool: Universal Tool-Use Layer for AI Agents
AnyTool is an open-source universal tool-use layer for AI agents that addresses the critical problem of how autonomous agents reliably interact with external tools and environments. Rather than having each agent handle tool invocation logic on its own, AnyTool provides a standardized interface and orchestrator that intelligently selects and manages tools, reduces context overhead, and improves execution reliability across diverse capabilities like web APIs, local commands, and GUI... -
19
MiniRAG
Making RAG Simpler with Small and Open-Sourced Language Models
MiniRAG is a lightweight retrieval-augmented generation tool designed to bring the benefits of RAG workflows to smaller datasets, edge environments, and constrained compute settings by simplifying embedding, indexing, and retrieval. It extracts text from documents, codes, or other structured inputs and converts them into embeddings using efficient models, then stores these vectors for fast nearest-neighbor search without requiring huge databases or separate vector servers. When a query is... -
20
NovaSR
A lightning fast audio upsampler
NovaSR is an extremely lightweight and high-performance audio upsampling model that transforms low-quality 16 kHz audio into clearer, high-fidelity 48 kHz audio with remarkable speed and efficiency. At only about 50 KB in size, the model is orders of magnitude smaller than typical audio super-resolution networks, yet it achieves high quality and realtime performance thanks to its compact architecture and efficient convolutional design. NovaSR is especially valuable for post-processing tasks... -
21
Z80-μLM
Z80-μLM is a 2-bit quantized language model
Z80-μLM is a retro-computing AI project that demonstrates a tiny language model (Z80-μLM) engineered to run on an 8-bit Z80 CPU by aggressively quantizing weights down to 2-bit precision. The repository provides a complete workflow where you train or fine-tune conversational models in Python, then export them into a format that can be executed on classic Z80 systems. A key deliverable is producing CP/M-compatible .COM binaries, enabling a genuinely vintage “chat with your computer”... -
22
Flan Scan
A pretty sweet vulnerability scanner
Flan Scan is a lightweight open-source network vulnerability scanner designed to make it easy to detect exposed services, open ports, and associated vulnerabilities across IP ranges or network segments as part of security audit and compliance workflows. It is essentially a thin wrapper around the widely-used Nmap scanner, augmenting it with scripts and tooling that transform raw Nmap output into vulnerability-focused reports that map detected services to known CVEs, making results more... -
23
Sapiens
High-resolution models for human tasks
Sapiens is a research framework from Meta AI focused on embodied intelligence and human-like multimodal learning, aiming to train agents that can perceive, reason, and act in complex environments. It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and... -
24
Oh My Zsh (ohmyzsh)
A framework for managing your zsh configuration
Oh My Zsh is a widely used, open-source, community-driven framework for managing Zsh shell configurations, providing hundreds of plugins, themes, and an auto-update system—designed to enhance developer productivity and shell aesthetics. Once installed, your terminal shell will become the talk of the town or your money back! With each keystroke in your command prompt, you'll take advantage of the hundreds of powerful plugins and beautiful themes. It's a good idea to inspect the install script... -
25
Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This...
