Search Results for "generative"
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Showing 20 open source projects for "generative"
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Generative AI Examples
Generative AI Examples is a collection of GenAI examples
Efficiently integrate secure, performant, and cost-effective Generative AI workflows into business value. Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines. Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows. A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness. -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
...Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. Albumentations works well with data from different domains: photos, medical images, satellite imagery, manufacturing and industrial applications, Generative Adversarial Networks. Albumentations can work with various deep learning frameworks such as PyTorch and Keras. -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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LLPhant
A comprehensive PHP Generative AI Framework
LLPhant is a PHP-based generative AI framework designed to bring large language model capabilities into modern PHP applications with a structure inspired by frameworks like LangChain. It provides developers with a set of abstractions for building AI-powered features such as chat systems, retrieval pipelines, and automated workflows while remaining simple enough to integrate into existing Symfony or Laravel projects. -
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Gen.jl
A general-purpose probabilistic programming system
...Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. Users can also hand-code parts of their models that demand better performance. -
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RuVector
Self-Learning, Vector Graph Neural Network, and Database built in Rust
...The project fits into a larger vision of modular, composable AI infrastructure designed to support autonomous agents, data retrieval, and intelligent automation workflows. It emphasizes extensibility and interoperability with modern AI stacks, allowing developers to integrate vector operations into search, reasoning, or generative systems. The repository reflects a research-forward approach that blends practical utilities with experimental agentic concepts, encouraging exploration of emerging AI design patterns. It is intended for developers building sophisticated AI-powered applications who need flexible vector handling and integration capabilities. -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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ComfyUI Workflows ZHO
My ComfyUI workflows collection
ComfyUI Workflows ZHO is a collection of reusable ComfyUI workflow files for generative image, video, 3D, and multimodal experiments. It brings together ready-made graphs for systems such as Stable Cascade, SD3, FLUX.1, Hunyuan Video, InstantID, PhotoMaker, and LivePortrait Animals. The repository also includes workflows that combine large language models with diffusion systems. Other examples cover ControlNet, image-to-image generation, inpainting, prompt visualization, upscaling, and 3D-oriented tasks. ... -
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Deep Learning Essay Reading
Read classic and new deep learning papers paragraph by paragraph
...Instead of reading entire dense academic papers, contributors provide structured breakdowns and insights into the most influential research from the past decade, often including explanation highlights and key takeaways. The content spans foundational models, architectures, and training methodologies across computer vision, natural language processing, generative models, and other machine learning domains. These summaries help students, researchers, and engineers stay up to date with breakthroughs in the field without needing to sift through full academic documents. With thousands of stars and forks, this repository has become a widely referenced learning resource for anyone interested in understanding the technical ideas behind major advancements. -
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iJEPA
Official codebase for I-JEPA
...A context encoder sees visible regions of an image and predicts target embeddings for masked regions produced by a slowly updated target encoder, focusing learning on semantics instead of texture. This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer strongly with linear probes and minimal fine-tuning. The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. ... -
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DeepMind Research
Implementations and code to accompany DeepMind publications
This repository collects reference implementations and illustrative code accompanying a wide range of DeepMind publications, making it easier for the research community to reproduce results, inspect algorithms, and build on prior work. The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. ... -
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glfx.js
An image effects library for JavaScript using WebGL
...A demo page showcases a variety of filters, from basic brightness/contrast adjustments to more advanced distortions and color manipulations. glfx.js remains a handy reference and solution for anyone needing client-side photo editing, visual effects, or generative graphics powered by WebGL. -
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vae
Simple vae and cvae from keras
...The code is organized as standalone experiments rather than a unified library API. It is best suited for studying older Keras implementations of latent-variable generative modeling techniques. -
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pytorch-examples
Simple examples to introduce PyTorch
...It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners and experienced practitioners. By emphasizing readable code, the repository helps users understand how PyTorch’s imperative programming style enables flexible model development. It also serves as a quick reference for common patterns and techniques used in deep learning workflows. ... -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. ... -
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Keras resources
Directory of tutorials and open-source code repositories
...It aggregates a wide range of resources, including beginner guides, advanced tutorials, code examples, and third-party tools, all organized into a single reference hub. The repository covers diverse topics such as image classification, natural language processing, reinforcement learning, and generative models, providing both theoretical and practical insights. It also includes links to external projects built with Keras, demonstrating real-world applications of deep learning techniques. The structure is designed for easy navigation, allowing users to quickly find relevant materials based on their skill level or area of interest. ... -
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EaselJS
Work with the HTML5 Canvas element easily
The Easel Javascript library provides a full, hierarchical display list, a core interaction model, and helper classes to make working with the HTML5 Canvas element much easier. A JavaScript library that makes working with the HTML5 Canvas element easy. Useful for creating games, generative art, and other highly graphical experiences. EaselJS provides straight forward solutions for working with rich graphics and interactivity with HTML5 Canvas. It provides an API that is familiar to Adobe Animate developers, but embraces JavaScript sensibilities. It consists of a full, hierarchical display list, a core interaction model, and helper classes to make working with Canvas much easier. ... -
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Grenade
Deep Learning in Haskell
Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only... -
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Pt
An experimental library on point, form, and space
Pt.js is an experimental JavaScript/TypeScript toolkit for generative visuals and interactive graphics. Built around the ideas of Point, Form, and Space, it provides entities for vectors, shapes, animations, and event handling. Suitable for visualizations, D3-like interactions, and creative coding experiments in browser or desktop. -
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graphics-resources
A list of graphic programming resources
graphics-resources is a curated collection of resources, tools, and references for creative coding and real-time graphics development, aimed at developers working with visual systems, generative art, and interactive media. Rather than being a traditional codebase, it functions as a knowledge hub that aggregates tutorials, libraries, research papers, and inspirational materials across multiple domains such as WebGL, shaders, animation, and design systems. The repository is structured to help developers discover high-quality tools and deepen their understanding of graphics programming ecosystems. ...
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