Showing 6 open source projects for "ptclab-setup"

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  • 1
    Open Source Vizier

    Open Source Vizier

    Python-based research interface for blackbox

    ...Define a problem statement and study configuration. Setup a local server, setup a client to connect to the server, perform a typical tuning loop, and use other client APIs.
    Downloads: 1 This Week
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  • 2
    nanoGPT

    nanoGPT

    The simplest, fastest repository for training/finetuning models

    NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare...
    Downloads: 6 This Week
    Last Update:
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  • 3

    BEDS - Bed Evaluation & Design System

    A system for designing and evaluating patient flow in hospitals.

    ...Several scientific studies have shown that this simple setup is an adequate approximation for describing the occupancy in inpatient wards.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Lucid

    Lucid

    A collection of infrastructure and tools for research

    ...We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. You can run the notebooks on your local machine, too. Clone the repository and find them in the notebooks subfolder. You will need to run a local instance of the Jupyter notebook environment to execute them. ...
    Downloads: 3 This Week
    Last Update:
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  • 5
    Dopamine

    Dopamine

    Framework for prototyping of reinforcement learning algorithms

    Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important...
    Downloads: 0 This Week
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  • 6
    Yans is a extensible, mixed-level, Monte-Carlo Method based, discrete event network simulator. Yans is divided into interacting layers, namely: core, topology, nodes, monitors; and is driven by a config-file that describes the setup of the network.
    Downloads: 0 This Week
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