Search Results for "apache" - Page 4
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Showing 1747 open source projects for "apache"
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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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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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TensorFlow Datasets
TFDS is a collection of datasets ready to use with TensorFlow,
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets. -
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Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
...They support context lengths up to 128,000 tokens and offer multilingual capabilities in over 29 languages, including Chinese, English, French, Spanish, and more. The models are open-source under the Apache 2.0 license, with resources and documentation available on platforms like Hugging Face and ModelScope. -
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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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SageMaker Python SDK
Training and deploying machine learning models on Amazon SageMaker
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker-compatible Docker containers, you can train and host models using these as well. -
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owllook
Vertical novel search engine with unified reading and tracking tools
Owllook is an open source vertical search engine designed for discovering and reading online novels from multiple sources. Instead of redirecting users to different sites, the system parses content from many novel platforms and presents it in a unified reading interface. It focuses on providing a simple and comfortable reading experience with features such as searching for books, following updates, bookmarking chapters, and maintaining a personal bookshelf. It aggregates results from... -
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tika-python
Python binding to the Apache Tika™ REST services
...This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache. -
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Agently 4
Build GenAI application quick and easy
...The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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CogVideo
Text and image to video generation: CogVideoX and CogVideo
CogVideo is an open-source family of advanced video generation models that can create videos from text, images, or existing video inputs. Built on large-scale Transformer and diffusion architectures, it enables multimodal generation across text-to-video, image-to-video, and video continuation tasks. The latest CogVideoX models offer higher resolution outputs, longer video durations, and improved controllability through prompt engineering. The project includes tools for inference,... -
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Qwen3-TTS
Qwen3-TTS is an open-source series of TTS models
Qwen3-TTS is an open-source text-to-speech (TTS) project built around the Qwen3 large language model family, focused on generating high-quality, natural-sounding speech from plain text input. It provides researchers and developers with tools to transform text into expressive, intelligible audio, supporting multiple languages and voice characteristics tuned for clarity and fluidity. The project includes pre-trained models and inference scripts that let users synthesize speech locally or... -
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alphageometry
AI-driven neuro-symbolic solver for high-school geometry problems
AlphaGeometry, developed by Google DeepMind, is a theorem-proving system that combines symbolic reasoning with deep learning to solve challenging geometry problems, such as those found in mathematical Olympiads. The repository provides the full implementation of DDAR (Deductive Difference and Abductive Reasoning) and AlphaGeometry, two automated geometry solvers described in the 2024 Nature paper “Solving Olympiad Geometry without Human Demonstrations.” AlphaGeometry integrates a symbolic... -
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Python Web
Course to learn frontend web development
This repository is a beginner-friendly template for creating Python web applications using Flask. Designed by @mouredev for learning and practice, it provides a simple, minimalistic structure for serving HTML pages and static content. Ideal for educational purposes and small-scale web projects, it also includes preconfigured files to simplify deployment and local development. -
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PaaSTA
An open, distributed platform as a service
PaaSTA is a highly-available, distributed system for building, deploying, and running services using containers and Kubernetes. PaaSTA has been running production services at Yelp since 2016. It was originally designed to run on top of Apache Mesos but has subsequently been updated to use Kubernetes. Over time the features and functionality that PaaSTA provides have increased but the principal design remains the same. PaaSTA aims to take a declarative description of the services that teams need to run and then ensures that those services are deployed safely, efficiently, and in a manner that is easy for the teams to maintain. ... -
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Anthropic Cybersecurity Skills
754 structured cybersecurity skills for AI agents
Anthropic Cybersecurity Skills is a collection of structured prompts, tools, and workflows designed to enhance the cybersecurity capabilities of AI systems. It focuses on defining reusable “skills” that guide AI models in performing tasks such as vulnerability analysis, threat detection, and security auditing. The project is intended for experimentation and development of AI-assisted cybersecurity workflows, providing templates that can be adapted to different environments. It emphasizes... -
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Open AEA Framework
A framework for open autonomous economic agent (AEA) development
open-aea is an open-source framework for building autonomous software agents that can operate and interact independently on decentralized networks. Developed by Valory, it facilitates creating agents capable of economic transactions, communication, and smart contract interactions in Web3 ecosystems. -
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uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
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Wanwu AI Agent Platform
Enterprise AI agent platform for workflows, models, and RAG apps
Wanwu is an enterprise-grade AI agent development platform designed to help organizations build and deploy intelligent applications at scale. It provides a multi-tenant environment that enables teams to create AI agents, orchestrate workflows, and implement retrieval-augmented generation systems within a unified framework. Wanwu integrates large language models with business process automation, allowing developers to design complex, production-ready AI solutions tailored to enterprise needs.... -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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Docker Compose
Define and run multi-container applications with Docker
Docker Compose is an open source tool for defining and running multi-container applications with Docker. Compose lets you use a YAML file to configure your application’s services, and then create and start all the services from your configuration with just a single command. Compose works great in all environments: production, staging, testing, development, and on CI workflows. Compose has commands for every stage of your application lifecycle, from starting, stopping and rebuilding services,... -
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ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model
ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference... -
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Handcalcs
Python library for converting Python calculations into rendered latex
Handcalcs is a Python library that auto-renders calculation code in Jupyter notebooks or LaTeX documents with step-by-step symbolic substitution, giving output a “handwritten” feel. It supports cell magics and auto-LaTeX generation via configurable output options. -
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NGBoost
Natural Gradient Boosting for Probabilistic Prediction
ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck. -
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Dataproc Templates
Dataproc templates and pipelines for solving simple in-cloud data task
Dataproc templates are designed to address various in-cloud data tasks, including data import/export/backup/restore and bulk API operations. These templates leverage the power of Google Cloud's Dataproc, supporting both Dataproc Serverless and Dataproc clusters. Google provides this collection of pre-implemented Dataproc templates as a reference and for easy customization. -
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MLflow
Open source platform for the machine learning lifecycle
MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). -
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MCP Teams Server
An MCP (Model Context Protocol) server implementation
An MCP server implementation for Microsoft Teams integration, providing capabilities to read messages, create messages, reply to messages, and mention members, facilitating AI-driven interactions within Teams. -
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RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
