Search Results for "model-builder"
Sort By:
Showing 32 open source projects for "model-builder"
View related business solutions-
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
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. -
2
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. -
3
nanoGPT
The simplest, fastest repository for training/finetuning models
...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 or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. While simple, it can still train non-trivial models on modern GPUs and generate coherent text. ... -
4
Biblatex is a LaTeX package which provides full-featured bibliographic facilities
-
Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
-
5
OpenSIMPLY
Discrete-event simulation modeling software for science and education
...Some application of this modeling software are: - traffic simulation - network simulation, - emergency and evacuation ways simulation and much more. This simulation tool runs in Windows and Linux, on 32-bit and 64-bit platforms, as a GUI or console (terminal) application. Write the model only once, simulate anywhere. Videos on installing OpenSIMPLY for different IDEs and operating systems : https://www.youtube.com/playlist?list=PLnyWoktGqA -
6
Artifact GeoMorph Toolbox 3D 3.1
A toolbox for 3DGM shape analysis of archaeological artifacts
The Artifact Geomorph Toolbox 3D software is designed to provide the archaeologist interested in artifact shape variability with a toolbox to allow the acquisition, analysis and results exploration of homologous 3D landmark-based geometric morphometric data. As such, the toolbox contains an automated item and semi-landmarks positioning procedure and the fundamental statistical analyses and procedures to allow the processing and analysis of the data. It is designed to be easy to use and... -
7
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... -
8
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. ... -
9
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. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
10
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. -
11
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... -
12
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. -
13
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... -
14
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. -
15
PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
...It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD, and CIFAR-10. In addition to core GAN training, the repository includes tools for model evaluation, such as Inception Score and SWD metrics, as well as advanced features like GDPP for diverse generation and AC-GAN conditioning for class-specific synthesis. The framework also supports “inspirational generation,” enabling style or content transfer from reference images through pre-trained models. -
16
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. ... -
17
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. -
18
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. -
19
Political economy library
Political economy simulation toolkit
Political economy library is a set of classes and accompanied tools for simulation of economy based on employment by companies, production of goods and consumption - EPC model. Actually it includes market-based model for research of the effects of Tobin tax. The library is based on Zarja library. -
20
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. -
21
-
22
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.).
-
23
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. -
24
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> -
25
Jointly optimized BF Assisted AEC
Jointly optimized BF Assisted AEC
...A stochastic model is derived for the transient and steady-state behaviors of the residual echo power. The convergence analysis provides a stability bound for the adaptation step-size. Monte Carlo simulations can be performed to illustrate the accuracy of the model, which can then used to provide design guidelines. Application of the new model confirms previous experimental findings that the same cancellation performance of a single-microphone AEC can be achieved with a shorter AEC when the possibility of spatial filtering is available.
