Search Results for "linux deploy" - Page 5
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Showing 244 open source projects for "linux deploy"
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LLM-Pruner
On the Structural Pruning of Large Language Models
LLM-Pruner is an open-source framework designed to compress large language models through structured pruning techniques while maintaining their general capabilities. Large language models often require enormous computational resources, making them expensive to deploy and inefficient for many practical applications. LLM-Pruner addresses this issue by identifying and removing non-essential components within transformer architectures, such as redundant attention heads or feed-forward... -
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MaxText
A simple, performant and scalable Jax LLM
MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small... -
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Lagent
A lightweight framework for building LLM-based agents
Lagent is a lightweight open-source framework designed to help developers build autonomous agents powered by large language models. The framework provides tools and abstractions that allow language models to interact with external tools, execute tasks, and perform multi-step reasoning processes. Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with... -
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II Agent
A new open-source framework to build and deploy intelligent agents
II-Agent is an open-source intelligent assistant framework designed to automate complex workflows across multiple domains using large language models and external tools. The platform allows users to interact with multiple AI models within a single environment while connecting those models to external services and knowledge sources. Through a unified interface, users can switch between models, access specialized tools, and execute tasks that require information retrieval, code execution, or... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Chitu
High-performance inference framework for large language models
Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations.... -
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FastDeploy
High-performance Inference and Deployment Toolkit for LLMs and VLMs
FastDeploy is an open-source inference and deployment toolkit designed to simplify the process of running and serving deep learning models across a wide range of hardware platforms. Developed within the PaddlePaddle ecosystem, the toolkit focuses on providing high-performance deployment capabilities for modern AI models including large language models and vision-language systems. The platform enables developers to deploy trained models quickly using optimized inference pipelines that support... -
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Sandstorm
One API call, pull Claude agent, completely sandboxed
Sandstorm is an open-source project that wraps a powerful Claude-based AI agent within a completely sandboxed, ephemeral API service designed to make agentic AI workflows easy to deploy and scale without infrastructure complexity. The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is... -
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TrendRadar
AI-driven public opinion trend monitor with multi-platform aggregation
TrendRadar is an AI-powered trend and hotspot tracking system that aggregates information from dozens of news, social, and content platforms to help users cut through information overload and focus on what matters. It automatically crawls and monitors trends across 30+ sources with smart filtering, keyword triggers, sentiment analysis, and natural language summarization to give actionable insights. The tool supports multiple alert modes—such as daily summaries, incremental change monitoring,... -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models,... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Argilla
The open-source data curation platform for LLMs
Argilla is a production-ready framework for building and improving datasets for NLP projects. Deploy your own Argilla Server on Spaces with a few clicks. Use embeddings to find the most similar records with the UI. This feature uses vector search combined with traditional search (keyword and filter based). Argilla is free, open-source, and 100% compatible with major NLP libraries (Hugging Face transformers, spaCy, Stanford Stanza, Flair, etc.). In fact, you can use and combine your preferred... -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources... -
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NVIDIA Merlin
Library providing end-to-end GPU-accelerated recommender systems
NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. For more information, see NVIDIA... -
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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
Magic is an open source all-in-one AI productivity platform designed to help organizations build, deploy, and scale AI-driven applications efficiently. It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error... -
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handy-ollama
Implement CPU from scratch and play with large model deployments
handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based... -
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NVIDIA Generative AI Examples
Generative AI reference workflows
NVIDIA GenerativeAIExamples is an open-source repository that provides practical reference implementations and example workflows for building generative AI applications using NVIDIA’s software ecosystem. The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. The repository includes examples covering topics such as... -
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AgentScope
Build and run agents you can see, understand and trust
AgentScope is a production-ready agent framework designed to help developers build, deploy, and scale intelligent agentic applications. It provides essential abstractions that evolve with advancing LLM capabilities, emphasizing reasoning, tool use, and flexible orchestration rather than rigid prompt constraints. With built-in support for ReAct agents, memory, planning, human-in-the-loop control, and real-time voice interaction, developers can create powerful agents in minutes. AgentScope... -
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Jenkins-Zero-To-Hero
Install Jenkins and configure Docker
Jenkins-Zero-To-Hero is a hands-on learning repository that teaches Jenkins from scratch, starting with installation and moving all the way to building end-to-end CI/CD pipelines. The course is designed around running Jenkins on an AWS EC2 instance, guiding you through installing Java, configuring Jenkins, and exposing it safely via security group rules. From there, it covers installing plugins like Docker Pipeline, configuring Docker as an agent, and wiring up multi-stage and multi-agent... -
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AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local... -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on... -
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Webifier
A GitHub Action to deploy Notebooks, Markdowns
Webifier is a stand-alone build tool for converting any repository into a deployable jekyll website. You can define your pages via yaml files and provide notebooks, markdown and pdf and other files for Webifier to render. It uses python markdown providing additional control over attributes and other extensive functionalities. It lets you define and direct how your web pages feel and automatically manages your assets, making it a perfect solution for fast static website development and a... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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PySyft
Data science on data without acquiring a copy
Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data... -
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REST APIs with Flask and Python
Projects and e-book for our course, REST APIs with Flask and Python
A full course to teach you how to use Flask and Python to make REST APIs using multiple Flask extensions and PostgreSQL. Learn Flask, Docker, PostgreSQL, and more. Build professional-grade REST APIs with Python. No more outdated tutorials. Use Python 3.10+ and the latest versions of every Flask extension and library. Run your apps in Docker, host your code with Git, write documentation with Swagger, and test your APIs while developing. Learn how to perform user authentication using JWTs and... -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
NVIDIA NeMo is a scalable, cloud-native generative AI framework aimed at researchers and PyTorch developers working on large language models, multimodal models, and speech AI (ASR and TTS), with growing support for computer vision. It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. NeMo 2.0 introduces a Python-based configuration system,... -
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OuteTTS
Interface for OuteTTS models
OuteTTS is an interface library for running OuteTTS text-to-speech models across a range of backends, making it easier to deploy the same model on different hardware and runtimes. It provides a high-level Interface API that wraps model configuration, speaker handling, and audio generation so you can focus on integrating speech into your application rather than wiring up low-level engines. The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face...
