Showing 23 open source projects for "model-builder"

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  • 1
    Megatron-LM

    Megatron-LM

    Ongoing research training transformer models at scale

    ...Megatron-LM is widely used in research and industry for pretraining GPT-, BERT-, T5-, and multimodal-style models, with tooling for checkpoint conversion and interoperability with Hugging Face. Overall, it is a production-grade system for organizations pushing the limits of large-scale language model training.
    Downloads: 1 This Week
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  • 2
    PageLM

    PageLM

    PageLM is a community driven version of NotebookLM

    ...It supports uploaded documents including PDF, DOCX, Markdown, and TXT, allowing users to ground questions and generated materials in source content. On the technical side, it supports multiple model providers, multiple embedding back ends, WebSocket streaming for real-time generation, persistent content storage, and structured markdown outputs.
    Downloads: 3 This Week
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  • 3
    biblatex
    Biblatex is a LaTeX package which provides full-featured bibliographic facilities
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    Downloads: 9 This Week
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  • 4
    AllenNLP

    AllenNLP

    An open-source NLP research library, built on PyTorch

    AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional...
    Downloads: 0 This Week
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  • 5
    Brain Tokyo Workshop

    Brain Tokyo Workshop

    Experiments and code from Google Brain’s Tokyo research workshop

    The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. ...
    Downloads: 2 This Week
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  • 6
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    ...It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. PyTorch 1.1+, and has been tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10 and Windows Subsystem for Linux. ...
    Downloads: 0 This Week
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  • 7
    covid19model

    covid19model

    Code for modelling estimated deaths and cases for COVID19

    Code for modeling estimated deaths and infections for COVID-19 from "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe", Flaxman, Mishra, Gandy et al, Nature, 2020, the published version of our original Report 13. This is the release related to our Tiers paper, where we use the latent factor model to estimate the effectiveness of tiers systems in England. Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code should be run in full mode to obtain credible results. Not running a full run to estimate anything is not recommended and discouraged. Only a full run should be used to get results.
    Downloads: 2 This Week
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  • 8
    Lucid

    Lucid

    A collection of infrastructure and tools for research

    Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. 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...
    Downloads: 2 This Week
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  • 9
    Python/FEniCS Examples

    Python/FEniCS Examples

    phase-field simulation and other examples with Python/FEniCS

    The main goal of this project was developing phase-field simulations of lithium dendrite growth with FEniCS programmed in Python. The problem was based in the grand potential-based model of Zijian Hong and Venkatasubramanian Viswanathan (https://doi.org/10.1021/acsenergylett.8b01009) . Some simpler examples were developed before for a first approach with FEniCS: heat equation and combustion model.
    Downloads: 0 This Week
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  • 10
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run...
    Downloads: 0 This Week
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  • 11
    COVID-19 Scenarios

    COVID-19 Scenarios

    Models of COVID-19 outbreak trajectories and hospital demand

    Models of COVID-19 outbreak trajectories and hospital demand. This tool is based on the SIR model (see about page for details) that simulates a COVID19 outbreak. The population is initially mostly susceptible (other than for initial cases). Individuals that recover from COVID19 are subsequently immune. Currently, the parameters of the model are not fit data but are simply defaults. These might fit better for some localities than others.
    Downloads: 0 This Week
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  • 12
    Data Science at the Command Line

    Data Science at the Command Line

    Data science at the command line

    Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. ...
    Downloads: 0 This Week
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  • 13
    Deep Learning for Medical Applications

    Deep Learning for Medical Applications

    Deep Learning Papers on Medical Image Analysis

    ...MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter notebooks, model architectures, data preprocessing pipelines, and evaluation scripts specific to medical imaging tasks. The repository may also contain domain-specific modules: loss functions like Dice, focal loss, metrics such as sensitivity/recall/IoU, and visualization utilities for overlaying segmentation masks.
    Downloads: 0 This Week
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  • 14

    diauxic growth model ensemble

    An ensemble of models showing diauxic growth behavior

    An ensemble of mathematical model is presented that all show diauxic growth behaviour of a bacterial culture. Carbon catabolite repression (CCR) is the main mechanism controlling carbohydrate uptake in bacteria, and therefore also controlling whether or not different carbon sources are metabolized in parallel or sequentially. Although described as a paradigm of the regulation of bacterial metabolism, the underlying mechanisms remain controversial.
    Downloads: 0 This Week
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  • 15

    In silico fragmentation evaluation

    Comparative analysis of open source in silico fragmentation tools

    We compared the performance of four publicly available in silico fragmentation tools that help in structure elucidation of metabolites (MetFrag, CFM-ID, MAGMa+ and MS-FINDER). Using the output of these tools we developed a voting/consensus model which is combining, re-ordering and re-ranking the candidates file and increases the correct hit percentage. We used 520 compounds from the 2016 CASMI challenge with 312 compounds for training and 208 compounds for validation purposes.
    Downloads: 0 This Week
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  • 16
    Modular application for biomedical data processing.
    Downloads: 0 This Week
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  • 17
    C++ Travel Customer Choice Model Library
    That project aims at providing a clean API, and the corresponding C++ implementation, for choosing one item among a set of travel solutions, given demand-related characteristics (e.g., Willingness-To-Pay, preferred airline, preferred cabin, etc.).
    Downloads: 0 This Week
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  • 18

    ParMa

    Parameter Management for agent-based simulation models

    ParMa provides several ways to define and read parameter settings for ABM ant therefore facilitates the organisation of model parameter settings.
    Downloads: 0 This Week
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  • 19

    ReBAC Java Library

    ReBAC library for java development

    Java library for Relationship Based Access Control (ReBAC). Provides a general framework creating ReBAC policies and model checking. Also provides tools for testing. Obtain latest version as a Maven Dependency: <dependency> <groupId>ca.ucalgary.ispia</groupId> <artifactId>rebac</artifactId> <version>0.1.7</version> </dependency>
    Downloads: 0 This Week
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  • 20
    We are developing MIRACH, a Statistical Online Model Checker for Biological Pathway Models, based on the PLTLs formalism for expressing the rules/properties to be checked. MIRACH can currently check pathways models written either in CSML or SBML.
    Downloads: 0 This Week
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  • 21
    GRaPe - a platform-independent software tool for building integrative gene-reaction-protein (GRP) networks. It generates the kinetic equations for each reaction and outputs a SBML document. It also implements two methods for parameter estimation.
    Downloads: 0 This Week
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  • 22
    This research project seeks to use compiler techniques to perform an attribute-based data-flow analysis on (MOF/UML)models allowing for a syntax-driven validation of a model's static semantics as well as an abstract interpretation of i dynamic behavior.
    Downloads: 0 This Week
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  • 23
    Running Reality

    Running Reality

    World history plays out down to street level on a detailed map.

    ...We at Running Reality believe that we can use the power of today's computers and mobile devices to bring history to life in an accessible, immersive, and engaging way for K-12 students, history enthusiasts, and visitors to historical sites. Running Reality gives you a map that lets you go any place on any date from 3000BC to today and explore down to the street-level of history. This model has nations and cities but also ships, armies, buildings, and people. Towns grow, buildings are constructed, ships explore new seas, and armies battle. Harbors silt in, rivers change course, and cities are sacked and burned. When you are standing at a historical site and using your mobile phone, you can see all the events that happened around you at that exact spot then zoom out to see the context of what was happening more globally.
    Downloads: 0 This Week
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