Showing 7 open source projects for "no code ai design"

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  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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  • All-in-one security tool helps you prevent ransomware and breaches. Icon
    All-in-one security tool helps you prevent ransomware and breaches.

    SIEM + Detection and Response for IT Teams

    Blumira’s detection and response platform enables faster resolution of threats to help you stop ransomware attacks and prevent data breaches. We surface real threats, providing meaningful findings so you know what to prioritize. With our 3-step rapid response, you can automatically block known threats, use our playbooks for easy remediation, or contact our security team for additional guidance. Our responsive security team helps with onboarding, triage and ongoing consultations to continuously help your organization improve your security coverage.
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  • 1
    Screenshot to Code

    Screenshot to Code

    A neural network that transforms a design mock-up into static websites

    Screenshot-to-code is a tool or prototype that attempts to convert UI screenshots (e.g., of mobile or web UIs) into code representations, likely generating layouts, HTML, CSS, or markup from image inputs. It is part of a research/proof-of-concept domain in UI automation and image-to-UI code generation. Mapping visual design to code constructs. Code/UI layout (HTML, CSS, or markup).
    Downloads: 3 This Week
    Last Update:
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  • 2
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation...
    Downloads: 0 This Week
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  • 3
    fastai

    fastai

    Deep learning library

    fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying...
    Downloads: 0 This Week
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  • 4
    ConvNeXt

    ConvNeXt

    Code release for ConvNeXt model

    ConvNeXt is a modernized convolutional neural network (CNN) architecture designed to rival Vision Transformers (ViTs) in accuracy and scalability while retaining the simplicity and efficiency of CNNs. It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure...
    Downloads: 0 This Week
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  • Automated RMM Tools | RMM Software Icon
    Automated RMM Tools | RMM Software

    Proactively monitor, manage, and support client networks with ConnectWise Automate

    Out-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
    Learn More
  • 5
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing...
    Downloads: 0 This Week
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  • 6
    GIMP ML

    GIMP ML

    AI for GNU Image Manipulation Program

    This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on...
    Downloads: 19 This Week
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  • 7
    MMF

    MMF

    A modular framework for vision & language multimodal research

    MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box.
    Downloads: 3 This Week
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