Stable Diffusion

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Stable Diffusion

Latent diffusion models (LDMs) are a type of image generation technique that work by iteratively "de-noising" data in a latent representation space, and then decoding the representation into a full image. This is in contrast to other popular image synthesis methods such as generative adversarial networks (GANs) and the auto-regressive technique used by DALL-E. The Stable Diffusion model is created by a collaboration between engineers and researchers from CompVis, Stability AI, and LAION and released under a Creative ML OpenRAIL-M license, wich means that it can be used for commercial and non-commercial purposes.

The release of this file is the culmination of many hours of collective effort to compress the visual information of humanity into a few gigabytes. Furthermore, the model also supports image-to-image style transfer, as well as upscaling and generating an images from a simple sketch. Included is also an AI-based Safty Classifier, which understands concepts and other factors in generations to remove outputs that may not be desired by the model user.

General
Relese date	August 22, 2022
Research Paper	https://ommer-lab.com/research/latent-diffusion-models/
Type	Deep learning text to image model

Stable diffusion Tutorials

👉 Discover more Stable Diffusion Tutorials on lablab.ai

Knowledge Base

Find out how it is working!

Research Paper The Stable Diffusion paper describes the model and its training process in detail.
Stable Diffusion Demo You can play around with Stable Diffusion on Hugging Face
GitHub Repository Visit the Stable Diffusion v2 repository on GitHub
dreamstudio Online stable diffusion interface with a lot of optional configurations

Models

There are plenty of Stable Diffusion models, which are taiolred to deliver various art styles, animation styles and more. We encourage you to experiment with many of them and choose the one which you like the most. Here are some of the finest ones:

Boilerplates

Get started with technology!

Stable Diffusion Colab A Colab notebook that shows how to use Stable Diffusion with GPU!
Stable Diffusion & Whisper Colab A Colab notebook that shows how to use Stable Diffusion with Whisper!
Stable Diffusion Interpolation V2.2 A Colab notebook about Stable Diffusion Interpolation!

Edit on GitHub

Stability AI Stable Diffusion AI technology Hackathon projects

Discover innovative solutions crafted with Stability AI Stable Diffusion AI technology, developed by our community members during our engaging hackathons.

Qubic Liquidation Guardian

Qubic Liquidation Guardian is a hybrid Track 1 + Track 2 project built by CrewX that brings real-time liquidation protection, institutional-grade risk analysis, and automated alerting to the Qubic Network. The problem is simple: DeFi liquidations happen instantly, but users do not get instant signals. As a result, borrowers lose capital, protocols lose liquidity, and investors hesitate to adopt new systems without safety infrastructure. Inspired by this gap, Qubic Liquidation Guardian provides a complete safety layer over lending protocols deployed on the Nostromo Launchpad. At its core, the system includes an on-chain event listener and a real-time risk scoring engine, which analyzes: • Health Factor • Liquidation Proximity • Total Debt Exposure • Active Positions These metrics are combined into a 0–100 Risk Score, dynamically updated for each borrower. Based on the score, users are automatically classified into Low, Medium, High, and Critical risk tiers, enabling rapid decision-making. The platform also includes advanced features such as: • Whale Watch: Detect large-value transactions to anticipate market shifts • Smart Alerts: Severity-based notifications connected to any tool • Auto-Airdrop: Rewards for users who resolve high-risk positions • Crash Simulator: A built-in testing environment to simulate -70% market dumps, rebounds, and full resets to verify protocol safety Qubic Liquidation Guardian is designed to strengthen the Nostromo ecosystem by improving investor confidence, increasing protocol safety, and enabling risk-aware liquidity management. With over 35 production-ready API endpoints, an edge-distributed database, and a Next.js 15 architecture, the application is fully deployable and already live for testing. Ultimately, this project delivers exactly what new chains and protocols need: speed, stability, transparency, and automation—making Qubic safer for everyone.

DreamWeaver

DreamWeaver is an AI-powered storytelling platform designed to visually bring dreams to life. Built with a React frontend and a Python FastAPI backend, the app allows users to input or speak their dreams. These dreams are enhanced using the Groq API with the LLaMA model to generate creative, refined prompts. The enhanced prompts are then sent to Hugging Face’s free Stable Diffusion model to generate vivid dream images. Users can view and revisit their dreams in a personalized journal, stored using localStorage. DreamWeaver promotes creativity, emotional expression, and self-reflection by blending generative AI with an immersive user experience.

AfriLearn AI Tutoring Platform

Schools in Africa have several needs. We want to focus on the lack of adequate infrastructure and the limited access to modern technologies, which restricts students' ability to participate in online learning programs or access digital educational resources. AI-powered platform. Initially developed on Streamlit for rapid prototyping, this platform integrates multiple technologies to deliver an educational experience rooted in African culture. It leverages OpenAI’s GPT-3.5 for a multilingual chatbot that answers questions using culturally relevant African examples. Stability AI generates localized visual lessons, such as science diagrams featuring native plants, while ElevenLabs provides text-to-speech functionality for audio responses. Additionally, the mentorship system organizes requests in a CSV database and includes an admin dashboard for managing student needs.

NetConnect

Public Sector Network Connectivity Analyzer The Public Sector Network Connectivity Analyzer is a comprehensive solution designed to address the critical need for reliable network monitoring across public institutions. Our application serves as an essential tool for IT administrators managing connectivity infrastructure for schools, healthcare facilities, government offices, libraries, and other public service organizations. Core Capabilities Real-Time Network Visualization Interactive diagrams and topology maps provide clear visibility into how public institutions are connected, displaying network elements, connection points, and infrastructure components with intuitive visualization tools. Performance Monitoring System Our platform continuously tracks vital network metrics including uptime percentages, latency measurements, bandwidth utilization, and connection status across the entire public sector network, enabling proactive management. Advanced Simulation Engine IT professionals can run comprehensive simulations to test network resilience under various scenarios such as increased user loads, infrastructure failures, or cyber incidents, helping identify vulnerabilities before they impact critical services. Institution Management Portal Administrators can efficiently manage information about connected institutions, monitor their connection status in real-time, and access detailed performance metrics through a unified dashboard interface. Geographic Mapping Integration Our system incorporates geographic visualization capabilities to display the physical distribution of institutions and network infrastructure across regions, facilitating better resource allocation and planning. Technical Implementation This solution addresses the unique challenges faced by public sector organizations that require reliable connectivity for delivering essential services to communities, while providing the tools needed to ensure network resilience, performance, and security.

SupplyGenius Pro

Core Features 1. Document Processing & Analysis - Automated analysis of supply chain documents - Extraction of key information (parties, dates, terms) - Compliance status verification - Confidence scoring for extracted data 2. Demand Forecasting & Planning - AI-powered demand prediction - Time series analysis with confidence intervals - Seasonal pattern recognition - Multi-model ensemble forecasting (LSTM, Random Forest) 3.Inventory Optimization - Real-time inventory level monitoring - Dynamic reorder point calculation - Holding cost optimization - Stockout risk prevention 4. Risk Management - Supply chain disruption simulation - Real-time risk monitoring - Automated mitigation strategy generation - Risk score calculation 5. Supplier Management - Supplier performance tracking - Lead time optimization - Pricing analysis - Automated purchase order generation 6. Financial Analytics - ROI calculation - Cost optimization analysis - Financial impact assessment - Budget forecasting 7. Real-time Monitoring - Live metrics dashboard - WebSocket-based alerts - Performance monitoring - System health tracking 8. Security Features - JWT-based authentication - Role-based access control - Rate limiting - Secure API endpoints -- Technical Capabilities 1. AI Integration - IBM Granite 13B model integration - RAG (Retrieval Augmented Generation) - Custom AI toolchains - Machine learning pipelines 2. Data Processing - Real-time data processing - Time series analysis - Statistical modeling - Data visualization 3. Performance Optimization - Redis caching - Async operations - Rate limiting - Load balancing 4. Monitoring & Logging - Prometheus metrics - Detailed logging - Performance tracking - Error handling

Social Media Content Generator

The Social Media Content Generator is a comprehensive solution designed to streamline and enhance the process of creating and managing social media content. This tool leverages advanced AI technology, specifically Falcon's LLMs, to automate the generation of engaging posts for LinkedIn and Twitter. Users start by inputting a topic, mood, and optionally a website URL for context. The tool then crafts tailored content and can generate AI-based images for LinkedIn posts, making them more visually appealing. The generator offers direct posting capabilities, allowing users to share content effortlessly across their social media accounts. The project addresses a significant pain point in social media management, where creating high-quality, consistent posts can be time-consuming and complex. The market for social media management tools is experiencing rapid growth, projected to expand from $15 billion in 2023 to $40 billion by 2028. This growth is fueled by increased social media usage and a rising demand for automation solutions. Our tool is strategically positioned to capture a share of this market by offering both efficiency and effectiveness in content creation. Future enhancements will focus on expanding platform support, improving AI capabilities, and incorporating user feedback to continually enhance the tool's functionality. In summary, the Social Media Content Generator provides a powerful and user-friendly solution for managing social media content, helping users save time, engage their audience, and maintain a consistent online presence while tapping into a lucrative and expanding market.