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217 dépôts

Awesome GitHub RepositoriesGenerative AI Models

Pre-trained models and scheduling algorithms specifically designed for generating synthetic data, images, or complex patterns.

Explore 217 awesome GitHub repositories matching artificial intelligence & ml · Generative AI Models. Refine with filters or upvote what's useful.

Awesome Generative AI Models GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • comfyanonymous/comfyuiAvatar de comfyanonymous

    comfyanonymous/ComfyUI

    117,322Voir sur GitHub↗

    ComfyUI is a modular generative AI workflow orchestrator and node-based GUI for designing and executing complex diffusion model pipelines. It functions as both a visual interface for building generative logic graphs and a programmable backend API that exposes diffusion model operations for external integration. The system distinguishes itself through a graph-based execution model that supports differential workflow execution, re-running only modified nodes to reduce computation. It features dynamic model offloading to manage memory between system RAM and GPU VRAM and utilizes metadata-embedde

    Designing complex generative pipelines for images, video, and audio using a modular node-based graph interface.

    Python
    Voir sur GitHub↗117,322
  • compvis/stable-diffusionAvatar de CompVis

    CompVis/stable-diffusion

    73,125Voir sur GitHub↗

    Stable Diffusion is a generative machine learning pipeline that synthesizes high-resolution visual content by performing iterative denoising within a compressed latent space. By mapping natural language embeddings into pixel outputs through conditioned probabilistic processes, the framework enables the generation of images from text prompts and the transformation of existing visual inputs based on semantic instructions. The architecture utilizes a modular execution environment that decouples model loading, scheduler logic, and inference components to support diverse hardware configurations. I

    Manipulates compressed latent representations to perform complex generative tasks on standard consumer hardware.

    Jupyter Notebook
    Voir sur GitHub↗73,125
  • labmlai/annotated_deep_learning_paper_implementationsAvatar de labmlai

    labmlai/annotated_deep_learning_paper_implementations

    66,981Voir sur GitHub↗

    This project is a collection of deep learning research papers translated into annotated code. It serves as a resource for reproducing academic research, providing implementations of transformers, diffusion models, and reinforcement learning architectures. The library distinguishes itself by using a side-by-side annotation format that combines executable Python code with descriptive markdown notes. This approach provides a structured way to explain the logic of neural network papers alongside their PyTorch-based implementations. The codebase covers several major capability areas, including ge

    Ships a library of generative AI models, including GANs and diffusion processes, for synthetic data and image creation.

    Pythonattentiondeep-learningdeep-learning-tutorial
    Voir sur GitHub↗66,981
  • nexu-io/open-designAvatar de nexu-io

    nexu-io/open-design

    65,830Voir sur GitHub↗

    Open Design is an AI design orchestration platform and LLM agent workspace designed for generating prototypes, presentations, and motion graphics. It functions as a local-first environment that integrates various command-line AI agents and coding tools into a unified design workflow, allowing users to migrate design specifications into brand-compliant source code. The project is distinguished by its ability to enforce visual consistency through a design system manager that defines brand contracts and tokens using Markdown. It features a specialized motion graphics generator that converts HTML

    Provides modular sequences of processing steps to orchestrate complex AI design workflows from discovery to critique.

    TypeScriptagent-skillsai-agentsai-design
    Voir sur GitHub↗65,830
  • keras-team/kerasAvatar de keras-team

    keras-team/keras

    64,094Voir sur GitHub↗

    Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a directed acyclic graph approach, the framework allows users to build intricate models with multiple inputs, outputs, and shared layers, ensuring consistent numerical execution through functional state management. The project distinguishes itself as a multi-backend machine learning

    Initializes image synthesis models using standardized presets to ensure efficient memory management and parameter configuration during diffusion tasks.

    Pythondata-sciencedeep-learningjax
    Voir sur GitHub↗64,094
  • microsoft/vibevoiceAvatar de microsoft

    microsoft/VibeVoice

    49,394Voir sur GitHub↗

    VibeVoice is a generative artificial intelligence platform designed for text-to-speech synthesis. It functions as a neural audio generation framework that converts written text into natural-sounding spoken audio, specifically engineered to maintain consistent vocal characteristics and narrative prosody across extended passages of content. The system distinguishes itself through its ability to generate long-form conversational speech while preserving speaker identity and linguistic content. By utilizing latent space disentanglement, the model separates speaker traits from the input text, allow

    Uses latent space disentanglement to separate speaker identity from linguistic content for consistent voice cloning.

    Python
    Voir sur GitHub↗49,394
  • exacity/deeplearningbook-chineseAvatar de exacity

    exacity/deeplearningbook-chinese

    37,285Voir sur GitHub↗

    This project is a comprehensive Chinese translation of a technical deep learning textbook, providing an educational resource on the theory and implementation of neural networks. It functions as a collaborative technical translation project designed to make complex academic AI literature accessible to non-English speakers. The project utilizes a community-driven translation model that integrates external suggestions and pull requests to refine linguistic accuracy and reduce bias. It employs standardized terminology mapping to ensure a uniform vocabulary throughout the translated content. To i

    Covers generating data samples by iteratively updating variables in blocks using bipartite graph structures.

    TeX
    Voir sur GitHub↗37,285
  • xingangpan/dragganAvatar de XingangPan

    XingangPan/DragGAN

    35,822Voir sur GitHub↗

    DragGAN is an interactive generative AI editor and GAN image editing tool designed for modifying the shape and structure of objects within images. It functions as a latent space manipulator that enables precise geometric and appearance editing by transforming images into editable latent codes. The system provides a web-based visual dashboard for real-time manipulation. Users can change the appearance of generated objects through an interactive point-based dragging interface, utilizing a process where source and target coordinates drive the optimization of the generative model. The project in

    Manipulates compressed latent representations via gradient descent to achieve specific geometric and appearance changes.

    Pythonartificial-intelligencegenerative-adversarial-networkgenerative-models
    Voir sur GitHub↗35,822
  • huggingface/diffusersAvatar de huggingface

    huggingface/diffusers

    33,872Voir sur GitHub↗

    Diffusers is a PyTorch-based library and generative AI framework used to build, train, and deploy diffusion pipelines for producing multi-modal media. It provides a suite of tools for generating images, video, and audio from natural language descriptions, as well as specialized systems for text-to-image generation. The project differentiates itself through a modular architecture that separates noise schedulers, pretrained model blocks, and pipeline compositions. This structure allows for the construction of custom generation workflows and the ability to swap individual components of the diffu

    Implements standardized interfaces for building and running generative diffusion models for multi-modal media.

    Pythondeep-learningdiffusionflux
    Voir sur GitHub↗33,872
  • openbmb/voxcpmAvatar de OpenBMB

    OpenBMB/VoxCPM

    29,985Voir sur GitHub↗

    VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice cloning tool and a synthetic voice designer, capable of generating natural speech across global languages and regional dialects using a GPU-accelerated audio generator. The project features a speech model fine-tuning framework that supports both full parameter updates and low-rank adaptation for customizing voice characteristics. It enables high-fidelity voice cloning from reference audio, including cross-lingual voice transfer and acoustic environment mimicry, as well as the crea

    Uses a hierarchical diffusion-based autoregressive architecture to generate high-fidelity continuous speech representations.

    Pythonaudiodeeplearningminicpm
    Voir sur GitHub↗29,985
  • hpcaitech/open-soraAvatar de hpcaitech

    hpcaitech/Open-Sora

    29,101Voir sur GitHub↗

    Open-Sora is a video generation framework designed to produce cinematic sequences from text prompts and images. It functions as a generative system that transforms written descriptions or reference images into video content featuring realistic textures and lighting. The project includes a dedicated prompt engineering tool that uses large language models to expand simple user inputs into detailed descriptions. It also features a motion controller for adjusting movement intensity in generated sequences and evaluating motion levels in existing video files. The framework incorporates text-to-vid

    Utilizes denoising schedulers to refine random noise into coherent video frames through iterative learned steps.

    Python
    Voir sur GitHub↗29,101
  • sgl-project/sglangAvatar de sgl-project

    sgl-project/sglang

    29,079Voir sur GitHub↗

    Sglang is a high-performance inference engine and serving system designed for large language and multimodal models. It provides a programmable interface for orchestrating complex generation workflows, enabling developers to coordinate multi-turn dialogues, tool invocations, and reasoning chains through a domain-specific language. The platform is built to support production-scale deployments, offering an OpenAI-compatible API that allows for integration with existing application ecosystems. The system distinguishes itself through a disaggregated architecture that separates compute-intensive pr

    Provides capabilities for executing inference and serving tasks for diffusion-based generative models.

    Pythonattentionblackwellcuda
    Voir sur GitHub↗29,079
  • svc-develop-team/so-vits-svcAvatar de svc-develop-team

    svc-develop-team/so-vits-svc

    28,097Voir sur GitHub↗

    This project is a singing voice conversion tool based on VITS generative modeling. It transforms the identity of a singing voice to a target speaker while preserving the original melody, lyrics, and intonation. The system distinguishes itself through hybrid voice synthesis, allowing for the blending of multiple speaker identities via linear model interpolation. It utilizes cluster-based feature retrieval to increase target voice similarity and employs a diffusion probabilistic model as a post-processor to remove electronic artifacts and improve vocal clarity. The software covers a broad rang

    Applies a diffusion probabilistic model as a post-processor to remove electronic artifacts and improve vocal clarity.

    Python
    Voir sur GitHub↗28,097
  • invoke-ai/invokeaiAvatar de invoke-ai

    invoke-ai/InvokeAI

    27,500Voir sur GitHub↗

    InvokeAI is a self-hosted, professional-grade platform designed for managing generative models and performing complex image synthesis. It provides a local application environment that allows users to execute diffusion models directly on their own hardware, ensuring data privacy and complete ownership of all generated assets. The platform distinguishes itself through a node-based workflow system that enables the construction of reproducible and automated image generation pipelines. By chaining modular functional units into directed acyclic graphs, users can automate intricate production tasks

    Provides a professional-grade web interface for generating and editing images using local diffusion models.

    TypeScriptai-artartificial-intelligencegenerative-art
    Voir sur GitHub↗27,500
  • stability-ai/generative-modelsAvatar de Stability-AI

    Stability-AI/generative-models

    27,189Voir sur GitHub↗

    This is a framework for training and sampling diffusion models to generate high-fidelity images, video, and 4D assets. It provides a modular environment for managing generative AI training pipelines, including the handling of datasets, noise sampling, and loss weighting to stabilize the creation of synthetic content. The project features a modular model configuration system that uses YAML-based assembly to define network submodules and conditioners. It also includes a dedicated toolset for AI image watermarking, allowing for the embedding and detection of invisible markers to verify the origi

    Provides a comprehensive framework for training and sampling diffusion models to generate high-fidelity images, video, and 4D assets.

    Python
    Voir sur GitHub↗27,189
  • black-forest-labs/fluxAvatar de black-forest-labs

    black-forest-labs/flux

    25,637Voir sur GitHub↗

    Flux is a diffusion model inference engine designed for text-to-image generation and image-to-image manipulation. It provides a system for executing open-weight models to transform natural language descriptions into visual imagery or to modify existing images. The project distinguishes itself through a flow-matching framework for image generation and a structural image controller. This controller allows for guided synthesis by using depth maps and Canny edge detection to constrain the geometry and composition of the output. The toolkit covers a broad range of image editing capabilities, incl

    Provides a high-performance inference engine for executing open-weight diffusion models to generate images.

    Python
    Voir sur GitHub↗25,637
  • facebookresearch/audiocraftAvatar de facebookresearch

    facebookresearch/audiocraft

    23,379Voir sur GitHub↗

    Audiocraft is a deep learning audio library and machine learning framework designed for training, fine-tuning, and evaluating generative models for music and sound effects. It functions as a text-to-music generative model and a neural audio codec, providing the tools necessary to compress audio signals into discrete representations and synthesize high-fidelity waveforms from textual descriptions. The framework is distinguished by its ability to combine multiple conditioning signals, allowing for the generation of audio based on text prompts, melodic excerpts, or style-based audio clips. It al

    Reconstructs audio waveforms from discrete tokens by predicting multiple frequency bands simultaneously for higher fidelity.

    Jupyter Notebook
    Voir sur GitHub↗23,379
  • sanster/iopaintAvatar de Sanster

    Sanster/IOPaint

    23,244Voir sur GitHub↗

    IOPaint is an AI image editor and Stable Diffusion inpainting tool providing a web interface for removing objects and replacing image content. It utilizes latent diffusion image processing to synthesize high-resolution replacements for erased sections of an image. The project features a specialized AI background remover for isolating subjects and an AI image upscaler that employs super-resolution models for general photos and anime artwork. The software covers a broad range of capabilities including image segmentation for object isolation, face restoration for improving facial details, and t

    Ships a web interface for removing objects and replacing image content using Stable Diffusion.

    Pythoninpaintinglamalatent-diffusion
    Voir sur GitHub↗23,244
  • sanster/lama-cleanerAvatar de Sanster

    Sanster/lama-cleaner

    23,235Voir sur GitHub↗

    Lama Cleaner is an AI-powered image editing application focused on inpainting, object removal, and generative filling. It provides a suite of tools for erasing unwanted elements from photos and filling the resulting gaps using generative artificial intelligence. The project includes specialized capabilities for image outpainting to extend borders, background removal through object segmentation, and face restoration to fix visual defects. It also features an image upscaler to increase resolution and clarity via super-resolution AI, as well as a Stable Diffusion-based editor for replacing speci

    Offers a web interface for performing generative filling and border extension via Stable Diffusion.

    Python
    Voir sur GitHub↗23,235
  • magenta/magentaAvatar de magenta

    magenta/magenta

    19,778Voir sur GitHub↗

    Magenta is a comprehensive toolkit for training, synthesizing, and performing music through neural models and hardware-integrated engines. It functions as a machine learning framework that enables the generation, manipulation, and real-time performance of audio, providing the structural foundations for musical intelligence through hierarchical sequence modeling and symbolic processing. The project distinguishes itself by enabling real-time, low-latency neural audio synthesis that can be integrated directly into professional digital audio workstations. It supports interactive musical jamming a

    Enables smooth transitions between musical styles by interpolating within latent spaces.

    Python
    Voir sur GitHub↗19,778
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Explorer les sous-tags

  • Denoising SchedulersMathematical solvers that manage the iterative refinement process in diffusion-based generative models.
  • Diffusion Model ManagersTools for importing, organizing, and switching between different pre-trained diffusion model weights. **Distinct from Diffusion Models:** Focuses on the management and switching of model files rather than the execution interface or training.
  • Diffusion Model Memory OptimizersFrameworks that reduce the memory footprint of diffusion models for inference on consumer hardware. **Distinct from Diffusion Weight Optimizers:** Focuses on inference memory optimization and precision recovery rather than training weight optimization.
  • Diffusion Models20 sous-tagsStandardized interfaces for initializing and running image synthesis models based on diffusion architectures.
  • Diffusion Weight OptimizersTools for optimizing weights of diffusion models to enable training on consumer-grade hardware. **Distinct from Diffusion Model Managers:** Focuses on the mathematical optimization of weights for training efficiency rather than the organizational management of model files.
  • Generation Task ManagersSystems for scheduling prompts, managing parameters, and recovering interrupted generation sessions. **Distinct from Diffusion Model Managers:** Focuses on the execution and recovery of tasks rather than just managing model weight files.
  • Latent Space Generative Models13 sous-tagsModels that perform generative tasks by manipulating compressed latent representations.