Showing 5 open source projects for "support ibm"

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  • 1
    Agent Stack

    Agent Stack

    Deploy and share agents with open infrastructure

    ...The platform supports agents built in frameworks like LangChain, CrewAI, etc., enabling them to be hosted, managed and shared through a unified interface. It also offers multi-model, multi-provider support (OpenAI, Anthropic, Gemini, IBM WatsonX, Ollama etc.), letting users compare performance and cost across models. For developers and organizations building AI-agent products or automations, Agent Stack gives a scaffold that handles the “plumbing”, so they can focus on logic and domain.
    Downloads: 3 This Week
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  • 2
    SpeechRecognition

    SpeechRecognition

    Speech recognition module for Python

    Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using...
    Downloads: 7 This Week
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  • 3
    oneDNN

    oneDNN

    oneAPI Deep Neural Network Library (oneDNN)

    This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the...
    Downloads: 0 This Week
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  • 4
    PennyLane

    PennyLane

    A cross-platform Python library for differentiable programming

    ...Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. The same quantum circuit model can be run on different devices. Install plugins to run your computational circuits on more devices, including Strawberry Fields, Amazon Braket, Qiskit and IBM Q, Google Cirq, Rigetti Forest, and the Microsoft QDK.
    Downloads: 0 This Week
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    Atera all-in-one platform IT management software with AI agents

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  • 5

    Smart Grid Co-Simulator

    Windows code with Omnet++ and OpenDSS simulator

    ...We have tested our co-simulation framework with a renewable energy integration application. * This work was partly supported by an Open Collaborative Research (OCR) project from IBM. The authors are thankful to Deva Seetharam, Koushik Das and their team at IBM, for their valuable suggestions and comments.
    Downloads: 0 This Week
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