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394 dépôts

Awesome GitHub RepositoriesDiffusion & Visual Synthesis Models

Explore 394 awesome GitHub repositories matching artificial intelligence & ml · Diffusion & Visual Synthesis Models. Refine with filters or upvote what's useful.

Awesome Diffusion & Visual Synthesis Models GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • trimstray/the-book-of-secret-knowledgeAvatar de trimstray

    trimstray/the-book-of-secret-knowledge

    228,641Voir sur GitHub↗

    Ce projet sert de dépôt centralisé de connaissances techniques et de ressources administratives piloté par la communauté. Il fournit une taxonomie structurée qui agrège des informations disparates dans un cadre consultable, soutenant l'apprentissage continu et la résolution rapide de problèmes pour les administrateurs système et les praticiens de la cybersécurité. En cartographiant les ressources à travers la sécurité offensive, la gestion de l'infrastructure et le développement logiciel, il offre un chemin unifié pour l'acquisition de compétences et la référence professionnelle. Le projet est défini par une philosophie de conception axée sur la ligne de commande, privilégiant les utilitaires basés sur le terminal et les interfaces scriptables pour faciliter une administration système efficace et des flux de travail de sécurité répétables. Il se distingue par une approche agnostique de la plateforme, maintenant une documentation et des guides opérationnels qui restent applicables à travers divers environnements de type Unix et basés sur le cloud. Cette intégration modulaire de la chaîne d'outils permet aux utilisateurs de composer des environnements personnalisés adaptés à des tâches administratives ou de sécurité spécifiques. Le dépôt couvre une large surface de capacités, notamment des boîtes à outils complètes pour l'audit système, la gestion réseau et le durcissement de l'infrastructure. Il fournit des parcours d'apprentissage structurés pour le développement des compétences en cybersécurité, allant des laboratoires de piratage éthique et des normes de test d'intrusion à l'évaluation des vulnérabilités et aux meilleures pratiques de configuration système. La collection englobe également un large éventail d'outils de productivité, d'utilitaires de diagnostic et de supports pédagogiques conçus pour rationaliser la maintenance de routine et améliorer la posture de sécurité globale.

    Generate realistic synthetic media, images, and text using advanced artificial intelligence tools.

    awesomeawesome-listbsd
    Voir sur GitHub↗228,641
  • automatic1111/stable-diffusion-webuiAvatar de AUTOMATIC1111

    AUTOMATIC1111/stable-diffusion-webui

    163,743Voir sur GitHub↗

    Stable Diffusion Web UI is a browser-based interface designed for managing text-to-image generation tasks. It provides a centralized dashboard for controlling generative processes, including native support for multi-stage model architectures to facilitate high-quality image refinement. The platform distinguishes itself through granular control over the generation process, offering tools for precise parameter management and advanced prompt engineering. Users can customize generation styles and capabilities by integrating external model-extension formats, such as textual inversions, low-rank ad

    Centralizes image generation, model management, and configuration tasks within a unified browser-based dashboard.

    Pythonaiai-artdeep-learning
    Voir sur GitHub↗163,743
  • huggingface/transformersAvatar de huggingface

    huggingface/transformers

    161,630Voir sur GitHub↗

    Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and

    Splits long prompt processing across multiple forward passes to prevent blocking other concurrent requests during generation.

    Pythonaudiodeep-learningdeepseek
    Voir sur GitHub↗161,630
  • 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
  • comfy-org/comfyuiAvatar de Comfy-Org

    Comfy-Org/ComfyUI

    117,227Voir sur GitHub↗

    ComfyUI is a node-based generative AI orchestration engine designed for constructing, testing, and executing complex image and video synthesis pipelines. By utilizing a directed acyclic graph execution model, the platform allows users to build reproducible workflows through modular, interconnected processing blocks without requiring manual code implementation. It serves as both a local environment for high-performance model inference and a production-ready server for deploying generative capabilities. The platform distinguishes itself through its focus on workflow portability and extensibilit

    Orchestrates multi-stage pipelines that synthesize dynamic video content from text prompts.

    Pythonaicomfycomfyui
    Voir sur GitHub↗117,227
  • 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

    Leverages denoising autoencoders within latent representations to synthesize detailed visual content efficiently.

    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
  • quantumnous/new-apiAvatar de QuantumNous

    QuantumNous/new-api

    39,722Voir sur GitHub↗

    This project is an AI model API gateway and proxy server designed to provide a unified interface for interacting with diverse artificial intelligence service providers. It functions as a centralized middleware platform that routes, load balances, and translates API requests across multiple models, enabling developers to access text, image, audio, and video generation capabilities through a single, standardized integration. The gateway distinguishes itself through comprehensive administrative and financial controls, including event-driven usage accounting, real-time token consumption tracking,

    Synthesizes dynamic video content from descriptive text prompts using generative models.

    Goai-gatewayclaudedeepseek
    Voir sur GitHub↗39,722
  • chatchat-space/langchain-chatchatAvatar de chatchat-space

    chatchat-space/Langchain-Chatchat

    38,211Voir sur GitHub↗

    Langchain-Chatchat is a system for building retrieval-augmented generation applications and autonomous AI agents. It integrates a knowledge base management system and an agent framework to enable language models to interact with private documents and execute multi-step tasks through external tools. The platform supports local deployment of language models on private infrastructure to operate without an internet connection. It includes a multimodal AI platform that combines vision models for image analysis with text-to-image generation capabilities. The system provides a web-based conversatio

    Generates images from natural language text prompts using integrated generative models.

    Pythonchatbotchatchatchatglm
    Voir sur GitHub↗38,211
  • 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

    Explains how to map simple latent distributions to complex data using neural generators.

    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
  • microsoft/taskmatrixAvatar de microsoft

    microsoft/TaskMatrix

    34,079Voir sur GitHub↗

    TaskMatrix is a visual language model orchestration framework and modular visual pipeline designed to coordinate disparate foundation models. It functions as a multi-model workflow coordinator that sequences visual and textual models through logic paths to handle image processing tasks without requiring additional training. The system integrates large language models with visual foundation models to enable the exchange of image data during interactive chat sessions. It utilizes template-based orchestration to chain specialized models together for complex visual tasks. The framework supports

    Provides text-guided image editing using bounding boxes and segmentation masks to perform targeted generative inpainting.

    Python
    Voir sur GitHub↗34,079
  • chenfei-wu/taskmatrixAvatar de chenfei-wu

    chenfei-wu/TaskMatrix

    34,082Voir sur GitHub↗

    TaskMatrix is a multimodal AI chat interface and visual task orchestrator. It combines language models with visual recognition to enable the exchange, analysis, and modification of images within a conversational environment. The system coordinates multiple foundation models through orchestration pipelines that chain language, detection, and segmentation models. This allows for complex visual operations, such as using text instructions to guide image masking and executing modular inpainting workflows to edit specific image regions. The project includes a computer vision toolset for object det

    Provides a modular workflow for modifying image regions using segmentation masks and diffusion models.

    Python
    Voir sur GitHub↗34,082
  • 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

    Provides high-resolution image generation from natural language text prompts using diffusion pipelines.

    Pythondeep-learningdiffusionflux
    Voir sur GitHub↗33,872
  • linshenkx/prompt-optimizerAvatar de linshenkx

    linshenkx/prompt-optimizer

    30,927Voir sur GitHub↗

    Prompt Optimizer is a framework designed for the iterative refinement and testing of text-based instructions for large language models. It functions as an automated evaluation pipeline that systematically adjusts prompt structure, constraints, and clarity to improve the accuracy and consistency of model outputs. The system distinguishes itself through a model-agnostic interface that standardizes communication across different artificial intelligence providers. It incorporates a versioned asset management system to track prompt history, enabling developers to maintain consistency and perform r

    Creates visual content from text descriptions by applying specific style parameters and model configurations.

    TypeScriptllmpromptprompt-engineering
    Voir sur GitHub↗30,927
  • 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
  • sillytavern/sillytavernAvatar de SillyTavern

    SillyTavern/SillyTavern

    29,463Voir sur GitHub↗

    SillyTavern is a comprehensive interface and orchestration platform designed for immersive AI roleplay and interactive chat experiences. It functions as a unified gateway that connects users to a wide array of local and cloud-based large language models, providing a centralized environment to manage complex character personas, narrative context, and model-driven interactions. The platform distinguishes itself through its advanced prompt engineering and automation capabilities. It utilizes a sophisticated macro-based templating engine and vector-database retrieval to dynamically inject lore, c

    Produces images and spoken audio responses from AI models to enhance interactive experiences.

    JavaScriptaichatllm
    Voir sur GitHub↗29,463
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  3. Generative AI Resources
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Explorer les sous-tags

  • Generation Utilities4 sous-tagsAuxiliary tools and modules that enhance generative AI workflows through visualization, prefilling, and model extension capabilities.
  • Generative AI Architectures1 sous-tagStructural components and mechanisms, such as attention layers, that enable models to generate new content.
  • Generative AI Capabilities2 sous-tagsFunctional capabilities that allow artificial intelligence systems to synthesize new media, such as images or audio.
  • Generative AI Models7 sous-tagsPre-trained models and scheduling algorithms specifically designed for generating synthetic data, images, or complex patterns.
  • Generative AI Pipelines4 sous-tagsEnd-to-end sequences of operations that transform input data into generated media like images or video.
  • Generative AI Tasks4 sous-tagsSpecific high-level tasks that involve the synthesis of new content from existing media inputs.
  • Generative AI Workflows5 sous-tagsDefined sequences of automated steps for creating and refining generative content through iterative processing.
  • Generative Models1 sous-tagStatistical models capable of learning data distributions to produce new, original samples from latent spaces.
  • Synthetic Content Generators2 sous-tagsSystems that automatically generate new media, such as images, audio, or text, from existing data.