Search Results for "ai framework" - Page 5
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Showing 146 open source projects for "ai framework"
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Cyclone
Powerful workflow engine and end-to-end pipeline solutions
...Cyclone is architectured with a low-level workflow engine that is application agnostic, offering capabilities like workflow DAG scheduling, resource lifecycle management and most importantly, a pluggable and extensible framework for extending the core APIs. Above which, Cyclone provides built-in support for high-level functionalities, with CI/CD pipelines and AI DevOps being two notable examples, and it is possible to expand to more use cases as well. With Cyclone, users end up with the flexibility of workflow orchestration and the usability of complete CI/CD and AI DevOps solutions. ... -
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Godot Steering AI Framework
A complete framework for Godot to create beautiful and complex AI
This project is a framework for the Godot game engine. It takes inspiration from the excellent GDX-AI framework for the LibGDX java-based framework. -
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Agentopia
Java5 mobile agents in peer2peer containers without stubs/skeletons.
Agentopia is a programming framework (API) for Java 5 mobile agents in peer-to-peer networks. Main features: Routing around firewalls, anonymity, and it is extremely easy to write new agents. No RMI, no CORBA, just plain Java bytecode loading. -
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HyperGAN
Composable GAN framework with api and user interface
A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. -
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Replica Dataset
High-fidelity indoor 3D dataset for AI simulation and robotics
...Replica integrates seamlessly with AI Habitat, Meta’s framework for embodied AI training, enabling large-scale agent simulation and photorealistic rendering for reinforcement learning and robotics. Researchers can use Replica’s ReplicaViewer to interactively explore the 3D scenes. -
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BWAPI
An API for interacting with Starcraft: Brood War (1.16.1)
Brood War Application Programming Interface or BWAPI is a free and open source C++ framework that is used to create Artificial Intelligence (AI) agents that play the popular Real Time Strategy (RTS) game Starcraft: Brood War. With BWAPI, players of varying levels can create AI agents to play Brood War, but with certain limits. BWAPI will only reveal visible parts of the game state to AI modules to enable programmers to write competitive non-cheating AIs. ... -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. -
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.
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Swift AI
The Swift machine learning library
Swift AI currently depends on Apple's Accelerate framework for vector/matrix calculations and digital signal processing. -
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buddidictionary
An English to Sinhala Dictionary with Morphological Processing
Buddidictionary is an English to Sinhala bilingual dictionary embed with English and Sinhala Morphological analysis. the system has been developed as a part of the EnSiMaS Project which is capable to translate English sentence into Sinhala. System has been developed through the MaSMT MUlti agent system development framework -
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Caffe
A fast open framework for deep learning
...Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
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Agent Factory is an open and extensible framework for developing and deploying agent systems that provides a FIPA-based distributed Run-Time Environment that supports the deployment of diverse agent types, ranging from bespoke, reactive to deliberative.
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AI Search Agent Framework
Java Framework for Artificial Intelligence Search Agents algorithms
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serein
A Framework to Model Metaheuristics
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JCLALtext
Text processing module for JCLAL
JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project. -
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The ERDialog project offers a simple browser framework for small projects written in Erlang. Written applets include a bittorrent client, address book, text editor, AI experiments and graphics and music applications.
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Architecture for Virtual Agents with Dynamic Embodiment - A framework for developing virtual environments equipped with virtual agents. Virtual agents are dynamically embodied; they have the ability to deliberatively change the form of their avatar.
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Framework for creation of board games. Chess is built-in, Monopoly comes next. It addresses: 1) Players 2) Game authors 3) AI developers 4) Model-based developers. Developed by software professionals using EMF. New games are configured in few hours.
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INGENIAS Development Kit (IDK) is a framework for analysis, design and implementation of multi-agent systems (MAS). It is based on the specification of MAS meta-models, from which tools such as the model editor and code generation are generated.
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Java framework for agent based application development
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easy fusion is a java-based framework that intends to automatically deploy and control information fusion systems (IFS) on distributed and dynamic resources.
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Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
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Security is a subject of major concern in mobile agents. This project provides a security framework that allows the protection of mobile agents from third parties. A self-protected approach, where the agents themselves manage the process, is used.
