Directory
Models and machine learning covers model hubs, research papers, training guides and evaluation tools. The topic mixes practical resources with reference material, so you will find repositories that host downloadable models next to sites that explain how a technique works. Some entries are collections of papers or benchmarks, and others are tutorials that walk through fine-tuning or deployment. It pays to compare the model licence, the training data, the hardware needed and the date of the last update. The field moves quickly, so verify version notes on the source before you build on anything listed here.
Flux is a machine learning library built as a pure-Julia stack, offering lightweight abstractions over Julia's native GPU and automatic differentiation support. It is compiled and eager, and existing Julia libraries can be incorporated into Flux models. Its ecosystem includes probabilistic programming, graph neural networks, computer vision and natural language processing packages, and it is maintained by a community team.
Flyflow is a GitHub organization with public repositories including an OpenAPI specification for the Flyflow API, a service framework, a Python library, and demo applications and notebooks. The organization page lists no public members.
FoLiA is an XML-based format for linguistic annotation intended for representing and exchanging written language resources such as corpora. It aims to accommodate many annotation types through a generalized paradigm without committing to a particular label set, language or linguistic theory. The project includes documentation, a RelaxNG schema and software libraries.
FontVibe is a free AI-powered font generator that creates custom text artwork. Users can either describe their desired style or select from over 120 available text effect styles, including neon, glitch, fire, and 3D options. Finished artwork can be downloaded instantly as PNG or JPG files.
Forefront is described as a platform to fine-tune and inference open-source language models. The site mentions building with open-source AI, fine-tuning models on data, and running inference through serverless API endpoints. It also describes storing training, validation and evaluation data in ready-to-fine-tune datasets. Pricing lists a free tier and a team plan at $99 per month, each including $20 in free credits.
Library for high performance deep learning inference on NVIDIA GPUs.
This is the public GitHub profile of Devin Stein, which hosts 57 public code repositories for community access. Visitors can follow the profile to view and use Stein's shared code on the GitHub platform.
Friday is a developer agent that helps create applications with AI assistance. It provides a core prompt for the application foundation and allows adding unlimited sections, each a prompt representing a specific part of the app.
Frog integrates memory-based natural language processing modules developed for Dutch, all based on the Timbl learning software package. Modules originated in the 1990s, and a dependency parser, base phrase chunker and named-entity recognizer were added more recently. It offers a command-line interface that can run as a daemon, plus a C++ library.
An open source Python library for drift detection in machine learning systems.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Fuzzy Wuzzy is a Python library for fuzzy string matching. The repository was archived by its owner on Aug 26, 2024, and is now read-only. The project has been renamed and moved to TheFuzz, and pull requests and issues must be resubmitted there.
Gaussian Mixture Model is an unsupervised machine learning implementation using a multivariate Gaussian mixture model. It supports both offline data and real-time data streams. The repository provides installation instructions, a simple example, and a license. It is hosted on GitHub at https://github.com/lukapopijac/gaussian-mixture-model.
GaussianProcesses.jl is a Julia package for Gaussian Processes that allows fitting exact Gaussian process models when observations are Gaussian distributed about the latent function. The main GP function fits Gaussian and non-Gaussian data, and parameters can be estimated by maximizing the log-likelihood or sampled with Hamiltonian Monte Carlo.
Creates, rewrites or summarizes written content with language models.
Creates, rewrites or summarizes written content with language models.
A curated UC Berkeley Law Library guide collecting resources on generative AI applications in law school, higher education, and legal practice. It links news, studies, ethics materials and access-to-justice research, and notes that the resources will be regularly updated.
Generative AI Takes Stereotypes and Bias From Bad to Worse provides machine-learning models, research, training resources, or evaluation tools.
The article 'Generative AI: A Creative New World' by Sequoia Capital discusses the emergence of a powerful new class of large language models that enable machines to write, code, draw, and create with credible or superhuman results. It contrasts analytical AI with creative AI.
A curated list of generative deep learning tools, works, models, etc. for artistic uses, by @filipecalegario.
GeneticSharp is a C# genetic algorithm library described as fast, extensible, multi-platform and multithreading, intended to simplify development of applications using genetic algorithms. The source states it can be used in .NET 6, .NET Standard and .NET Framework apps, including ASP.NET MVC, ASP.NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A Chinese segment based on Conditional Random Field.
Host inference APIs, bulk inference and fine tune text, vision, audio and multi-modal models.
