Showing 11 open source projects for "training"

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  • 1
    rLLM

    rLLM

    Democratizing Reinforcement Learning for LLMs

    ...The project is designed to support large-scale language models (including support for big models via integrated training backends), making it relevant for state-of-the-art research and production use. The framework includes tools for defining workflows, specifying objectives or reward functions, and managing training/policy updates across possibly distributed settings.
    Downloads: 0 This Week
    Last Update:
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  • 2
    AWorld

    AWorld

    Build, evaluate and train General Multi-Agent Assistance with ease

    ...It provides features to help and coordinate across multiple agents. It can also scale their training across environments.
    Downloads: 0 This Week
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  • 3
    AppWorld

    AppWorld

    World of apps for benchmarking interactive coding agent

    AppWorld is a framework developed by Stony Brook University's NLP group to simulate environments for training and evaluating dialogue agents in task-oriented applications.
    Downloads: 1 This Week
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  • 4
    Habitat-Lab

    Habitat-Lab

    A modular high-level library to train embodied AI agents

    ...Configuring and instantiating a diverse set of embodied agents, including commercial robots and humanoids, specifying their sensors and capabilities. Providing algorithms for single and multi-agent training (via imitation or reinforcement learning, or no learning at all as in SensePlanAct pipelines), as well as tools to benchmark their performance on the defined tasks using standard metrics.
    Downloads: 0 This Week
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  • 5
    IntentKit

    IntentKit

    An open and fair framework for everyone to build AI agents

    IntentKit is a natural language understanding (NLU) library focused on intent recognition and entity extraction, enabling developers to build conversational AI applications.
    Downloads: 0 This Week
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  • 6
    Zeta

    Zeta

    Build high-performance AI models with modular building blocks

    zeta is a deep learning library focused on providing cutting-edge AI and neural network models with a strong emphasis on research-grade architectures. It includes state-of-the-art implementations for rapid experimentation and model building.
    Downloads: 0 This Week
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  • 7
    PilottAI

    PilottAI

    Python framework for building scalable multi-agent systems

    pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers.
    Downloads: 0 This Week
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  • 8
    smolagents

    smolagents

    Agents write python code to call tools and orchestrate other agents

    This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents.
    Downloads: 0 This Week
    Last Update:
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  • 9
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
    Downloads: 0 This Week
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  • 10
    ChatArena

    ChatArena

    ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments

    ChatArena is a library that provides multi-agent language game environments and facilitates research about autonomous LLM agents and their social interactions.
    Downloads: 0 This Week
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  • 11
    Adala

    Adala

    Adala: Autonomous DAta (Labeling) Agent framework

    Adala is a data-centric AI framework focused on dataset curation, annotation, and validation. It helps AI teams manage high-quality training datasets by providing tools for data auditing, error detection, and quality assessment.
    Downloads: 0 This Week
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