Showing 1874 open source projects for "python-4suite-xml"

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  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

    It's a modern take on desktop management that can be scaled as per organizational needs.

    Desktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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  • Binary Options and Forex Trading Software Icon
    Binary Options and Forex Trading Software

    For Forex traders (Crypto, Stocks, indices, metals), Binary Option traders

    CapitalCore is an online broker offering Forex (CFD) and binary options trading with the highest payouts in the industry. Our platform gives you access to global currency pairs for CFD trading and fast, straightforward binary options. Enjoy quick withdrawals, competitive spreads, and advanced trading tools, all designed to help you succeed. With flexible account options and dedicated support, we’re here to help traders of all levels reach their financial goals.
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  • 1
    Xiyan MCP Server

    Xiyan MCP Server

    A Model Context Protocol (MCP) server

    The XiYan MCP Server is a Model Context Protocol (MCP) server that enables natural language queries to databases, powered by XiYan-SQL, a state-of-the-art text-to-SQL model. It allows users to interact with databases using conversational language, simplifying data retrieval processes. ​
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  • 2
    MCP Server Qdrant

    MCP Server Qdrant

    An official Qdrant Model Context Protocol (MCP) server implementation

    The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. ​
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  • 3
    Browser Use MCP Server

    Browser Use MCP Server

    Browse the web, directly from Cursor etc.

    A browser automation server implementing the Model Context Protocol, designed to allow AI assistants to browse the web directly from applications like Cursor. It supports natural language commands for web navigation and interaction. ​
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  • 4
    MCP Shell Server

    MCP Shell Server

    Shell command execution server implementing the Model Context Protocol

    A secure shell command execution server implementing the Model Context Protocol (MCP), allowing remote execution of whitelisted shell commands with support for standard input. ​
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  • Admiral: The Visitor Relationship Management Company Icon
    Admiral: The Visitor Relationship Management Company

    A single platform helping Publishers grow Visitor Relationships and Revenue.

    Admiral created the first Visitor Relationship Management (VRM) platform for news and media publishers. The platform combines marketing automation, machine learning, personalization, and an engagement layer, to help digital publishers grow visitor relationships and revenue. They can deliver the right offer, at the right time, at every visitor touchpoint.
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  • 5
    RA.Aid

    RA.Aid

    Develop software autonomously

    RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality.​
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  • 6
    optillm

    optillm

    Optimizing inference proxy for LLMs

    OptiLLM is an optimizing inference proxy for Large Language Models (LLMs) that implements state-of-the-art techniques to enhance performance and efficiency. It serves as an OpenAI API-compatible proxy, allowing for seamless integration into existing workflows while optimizing inference processes. OptiLLM aims to reduce latency and resource consumption during LLM inference.
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  • 7
    LMDeploy

    LMDeploy

    LMDeploy is a toolkit for compressing, deploying, and serving LLMs

    LMDeploy is a toolkit designed for compressing, deploying, and serving large language models (LLMs). It offers tools and workflows to optimize LLMs for production environments, ensuring efficient performance and scalability. LMDeploy supports various model architectures and provides deployment solutions across different platforms.
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  • 8
    R1-V

    R1-V

    Witness the aha moment of VLM with less than $3

    R1-V is an initiative aimed at enhancing the generalization capabilities of Vision-Language Models (VLMs) through Reinforcement Learning in Visual Reasoning (RLVR). The project focuses on building a comprehensive framework that emphasizes algorithm enhancement, efficiency optimization, and task diversity to achieve general vision-language intelligence and visual/GUI agents. The team's long-term goal is to contribute impactful open-source research in this domain.
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  • 9
    Axolotl

    Axolotl

    Go ahead and axolotl questions

    Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training.
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  • Combine Jira and SCM data to improve team performance Icon
    Combine Jira and SCM data to improve team performance

    For engineering leaders who need to foster alignment with the business and streamline their operations for better efficiency and higher productivity

    Jellyfish is the leading Engineering Management Platform, providing complete visibility into engineering organizations, the work they do, and how they operate. By analyzing engineering signals from Git and Jira, qualitative team feedback, and contextual business data from roadmapping, incident response, HR, calendar, and collaboration tools, Jellyfish enables engineering leaders to align engineering decisions with business initiatives and deliver the right software, efficiently, on time. With Jellyfish, engineering leaders can focus their teams on what matters most to the business, driving strategic decisions and delivering results.
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  • 10
    Tianji

    Tianji

    Evaluation suite designed to assess the performance of LLMs

    Tianji is a comprehensive evaluation suite designed to assess the performance of large language models (LLMs) across multiple dimensions. It focuses on measuring general capabilities such as reasoning, knowledge, commonsense, and language understanding. Tianji provides a curated set of benchmarks and a unified framework for systematically comparing LLMs, making it useful for research and model selection.
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  • 11
    robosuite

    robosuite

    A Modular Simulation Framework and Benchmark for Robot Learning

    Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning.
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  • 12
    TextWorld

    TextWorld

    ​TextWorld is a sandbox learning environment for the training

    TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities.
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  • 13
    PettingZoo

    PettingZoo

    An API standard for multi-agent reinforcement learning environments

    PettingZoo is a standardized API and library for multi-agent reinforcement learning (MARL) environments. It provides a broad set of environments and tools to facilitate the development and evaluation of multi-agent algorithms.
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  • 14
    Potpie

    Potpie

    Create custom engineering agents for your codebase

    Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding.
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  • 15
    NNCF

    NNCF

    Neural Network Compression Framework for enhanced OpenVINO

    NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency.
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  • 16
    DeepSparse

    DeepSparse

    Sparsity-aware deep learning inference runtime for CPUs

    A sparsity-aware enterprise inferencing system for AI models on CPUs. Maximize your CPU infrastructure with DeepSparse to run performant computer vision (CV), natural language processing (NLP), and large language models (LLMs).
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  • 17
    Text Generation Inference

    Text Generation Inference

    Large Language Model Text Generation Inference

    Text Generation Inference is a high-performance inference server for text generation models, optimized for Hugging Face's Transformers. It is designed to serve large language models efficiently with optimizations for performance and scalability.
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  • 18
    Advanced Solutions Lab

    Advanced Solutions Lab

    This repos contains notebooks for the Advanced Solutions Lab

    This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level.
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  • 19
    Autodistill

    Autodistill

    Images to inference with no labeling

    Autodistill uses big, slower foundation models to train small, faster supervised models. Using autodistill, you can go from unlabeled images to inference on a custom model running at the edge with no human intervention in between. You can use Autodistill on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud.
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  • 20
    Nerve

    Nerve

    The Simple Agent Development Kit

    Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. It’s designed for technical users who want programmable, auditable, and reproducible automation...
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  • 21
    Instructor

    Instructor

    Structured outputs for llms

    Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of...
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  • 22
    YData Synthetic

    YData Synthetic

    Synthetic data generators for tabular and time-series data

    ...This repository contains material related to Generative Adversarial Networks for synthetic data generation, in particular regular tabular data and time-series. It consists a set of different GANs architectures developed using Tensorflow 2.0. Several example Jupyter Notebooks and Python scripts are included, to show how to use the different architectures. YData synthetic has now a UI interface to guide you through the steps and inputs to generate structure tabular data. The streamlit app is available form v1.0.0 onwards.
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  • 23
    OpenVINO Training Extensions

    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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  • 24
    Hivemind

    Hivemind

    Decentralized deep learning in PyTorch. Built to train models

    Hivemind is a PyTorch library for decentralized deep learning across the Internet. Its intended usage is training one large model on hundreds of computers from different universities, companies, and volunteers. Distributed training without a master node: Distributed Hash Table allows connecting computers in a decentralized network. Fault-tolerant backpropagation: forward and backward passes succeed even if some nodes are unresponsive or take too long to respond. Decentralized parameter...
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  • 25
    AIF360

    AIF360

    A comprehensive set of fairness metrics for datasets

    ...The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifecycle. AI Fairness 360 package is available in both Python and R. The AI Fairness 360 interactive experience provides a gentle introduction to the concepts and capabilities. The tutorials and other notebooks offer a deeper, data scientist-oriented introduction. The complete API is also available. Being a comprehensive set of capabilities, it may be confusing to figure out which metrics and algorithms are most appropriate for a given use case. ...
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