Search Results for "generative" - Page 2
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Showing 481 open source projects for "generative"
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Text-to-image Playground
A playground to generate images from any text prompt using SD
dalle-playground is an open-source web application that allows users to generate images from natural language text prompts using modern text-to-image generative models. Originally built around DALL-E Mini, the project later transitioned to using Stable Diffusion, enabling more detailed and higher-quality image synthesis. The system combines a backend machine learning service with a browser-based frontend interface that lets users experiment interactively with prompt engineering and generative AI. ... -
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ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs
...Through these nodes, users can convert images into 3D models, manipulate geometry, and experiment with generative 3D workflows inside the visual pipeline editor. -
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AI Notes
Curated AI engineering notes on LLMs, generative models, and tools
ai-notes is a curated repository of notes focused on the evolving landscape of artificial intelligence, particularly generative models and large language models. It is designed to help software engineers quickly understand modern AI concepts, tools, and developments through structured documentation and research notes. It functions as a living knowledge base composed of numerous markdown files that organize topics such as text generation, image generation, AI infrastructure, and code generation models. ... -
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StabilityMatrix
Multi-Platform Package Manager for Stable Diffusion
...This approach is useful for model selection, prompt engineering, and benchmarking new checkpoints against baseline models under reproducible conditions. By turning ad-hoc tests into tracked experiments, StabilityMatrix reduces bias, surfaces subtle regressions, and accelerates iteration when tuning generative systems. -
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SD.Next
All-in-one WebUI for AI generative image and video creation
SD.Next is an all-in-one web user interface for generative image creation that expands beyond basic Stable Diffusion workflows to cover broader image and video generation, captioning, and processing tasks. It is designed as a power-user environment where model management, generation features, and workflow controls are centralized in a single UI rather than spread across separate scripts and utilities. -
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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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CTGAN
Conditional GAN for generating synthetic tabular data
CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may... -
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Clarity AI Upscaler
AI Image Upscaler & Enhancer
Clarity AI Upscaler is an open-source AI image enhancement tool designed to increase the resolution and visual quality of images using modern generative techniques. The system uses deep learning models based on diffusion and other image generation methods to reconstruct high-resolution versions of low-resolution images while preserving important visual details. Unlike traditional interpolation-based upscaling algorithms, the system generates additional visual information that improves perceived clarity and sharpness. ... -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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Envoy AI Gateway
Manages Unified Access to Generative AI Services
Envoy AI Gateway is an open-source gateway system designed to manage network traffic between applications and generative AI services using the Envoy proxy ecosystem. The project extends Envoy Gateway to support AI-specific workloads, enabling organizations to route, secure, and scale requests to large language models and other generative AI services. In a typical deployment, the architecture uses a two-tier gateway model where an outer gateway handles authentication, routing, and global rate limiting while a second gateway manages traffic to self-hosted model serving clusters. ... -
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USO
Open-sourced unified customization model
USO is ByteDance’s “Unified Style and Subject-Driven Generation” framework, open-sourced to allow customization in generative modeling by disentangling style and subject representation and using reward learning to guide generation. The system is designed such that users can control both “what” is generated (the subject: e.g. a person, object, scene) and “how” it is generated (the style: artistic style, color palette, aesthetic) separately, giving much more flexibility than conventional monolithic generative models. ... -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,... -
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Megatron
Ongoing research training transformer models at scale
Megatron is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and... -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the... -
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GPT AI Assistant
OpenAI + LINE + Vercel = GPT AI Assistant
GPT AI Assistant is an application that is implemented using the OpenAI API and LINE Messaging API. Through the installation process, you can start chatting with your own AI assistant using the LINE mobile app. -
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Flow Matching
A PyTorch library for implementing flow matching algorithms
flow_matching is a PyTorch library implementing flow matching algorithms in both continuous and discrete settings, enabling generative modeling via matching vector fields rather than diffusion. The underlying idea is to parameterize a flow (a time-dependent vector field) that transports samples from a simple base distribution to a target distribution, and train via matching of flows without requiring score estimation or noisy corruption—this can lead to more efficient or stable generative training. ... -
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FaceFusion
Industry leading face manipulation platform
...FaceFusion is built with a modular pipeline that allows users to customize processing steps and optimize performance for different hardware environments. The tool is often used in content creation, visual effects experimentation, and research into generative media. Overall, FaceFusion functions as a flexible and extensible platform for AI-driven face replacement and enhancement tasks. -
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Unredact
A simple tool for reading in poorly redacted documents
Unredact is a specialized tool that attempts to reconstruct redacted or obscured text in images, PDFs, or screenshots using a combination of image processing and generative AI inference to suggest plausible completions of blurred, black-boxed, or jumbled content. Unlike traditional optical character recognition (OCR), which only reads visible text, Unredact focuses on inferring missing content where redaction has been applied by analyzing surrounding context, font characteristics, and linguistic patterns to produce candidate reconstructions. ... -
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Wan2.1
Wan2.1: Open and Advanced Large-Scale Video Generative Model
Wan2.1 is a foundational open-source large-scale video generative model developed by the Wan team, providing high-quality video generation from text and images. It employs advanced diffusion-based architectures to produce coherent, temporally consistent videos with realistic motion and visual fidelity. Wan2.1 focuses on efficient video synthesis while maintaining rich semantic and aesthetic detail, enabling applications in content creation, entertainment, and research. -
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Moondream
Tiny vision language model
...It serves as both a playground for the author’s artistic curiosity and a resource for other creative coders interested in generative art techniques. The repository may include shaders, canvas/WebGL code, visual demos, and utilities that demonstrate how mathematical functions or noise patterns can be harnessed for compelling visuals. -
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Wan2.2
Wan2.2: Open and Advanced Large-Scale Video Generative Model
Wan2.2 is a major upgrade to the Wan series of open and advanced large-scale video generative models, incorporating cutting-edge innovations to boost video generation quality and efficiency. It introduces a Mixture-of-Experts (MoE) architecture that splits the denoising process across specialized expert models, increasing total model capacity without raising computational costs. Wan2.2 integrates meticulously curated cinematic aesthetic data, enabling precise control over lighting, composition, color tone, and more, for high-quality, customizable video styles. ... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
...The repo also bundles a full generative modeling pipeline (e.g. the framework “MaskGen” / “TA-TiTok”) that demonstrates how this 1D tokenizer can be used in text-to-image generation or image reconstruction tasks. -
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UNO
A Universal Customization Method for Single and Multi Conditioning
UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is new (see activity logs for 2025), it seems to aim at bridging between single-subject customization and multi-subject generation in generative modeling — potentially useful for personalized content creation, flexible composition, or controlled generation tasks. ... -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. -
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AudioLM - Pytorch
Implementation of AudioLM audio generation model in Pytorch
Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it...
