Best AI tools for< Catalog Models >

Phygital+ is an AI-powered platform that helps businesses bridge the gap between the physical and digital worlds. With Phygital+, businesses can create immersive and interactive experiences for their customers, using a variety of AI-powered tools. These tools include computer vision, natural language processing, and machine learning. Phygital+ is easy to use and can be integrated with a variety of existing systems. It is also scalable, so businesses of all sizes can use it to improve their customer experience.

Flux LoRA Model Library is an AI tool that provides a platform for finding and using Flux LoRA models suitable for various projects. Users can browse a catalog of popular Flux LoRA models and learn about FLUX models and LoRA (Low-Rank Adaptation) technology. The platform offers resources for fine-tuning models and ensuring responsible use of generated images.

HrFlow.ai is an API-first company and the leading AI-powered HR data automation platform. The company helps +1000 customers (HR software vendors, Staffing agencies, large employers, and headhunting firms) to thrive in a high-volume and high-frequency labor market. The platform provides a complete and fully integrated suite of HR data processing products based on the analysis of hundreds of millions of career paths worldwide -- such as Parsing API, Tagging API, Embedding API, Searching API, Scoring API, and Upskilling API. It also offers a catalog of +200 connectors to build custom scenarios that can automate any business logic.

Epidemic Sound is a platform that offers a vast catalog of music and sound effects for videos, allowing users to bring their stories to life with exclusive soundtracking tools and worry-free publishing worldwide. With over 2.5 billion daily views, the platform provides access to various genres, themes, moods, and sound effects, including music by global artists like K-Pop, Lo-Fi Beats, Classical, R&B, Electronic, and Hip Hop. Epidemic Sound stands out with its innovative royalty-free license model, offering users direct licenses with all rights included globally, ensuring content creators can use the music without paying royalties. The platform also provides tailored licensing options for different content needs, including major publishers requiring soundtracks for TV, cinema, streaming, and live events.

Zyng is a bulk image editing automation tool that uses AI to streamline complex image editing tasks. It allows users to edit thousands of images in minutes, freeing up their time to focus on more creative pursuits. Zyng's AI models can automatically crop images according to the subject or body landmarks, resize images for social media or e-commerce, remove backgrounds, and retouch portraits. Zyng is suitable for a variety of use cases, including e-commerce, marketing, photography, and graphic design.

Rightsify is a global music licensing agency that provides music for almost every use case imaginable, with a catalog of over 10 million songs that gets heard by over one billion people every year. Rightsify's music is available for businesses worldwide, and its Hydra AI Music Model enables high-quality music production for all with full commercial rights.

Tire Robot is an AI-powered deal finder application that helps users find the best deals on tires and wheels. Users can ask specific questions related to their car model, budget, season, or preferences, and the AI algorithm provides tailored product recommendations from a vast catalog. The application also features top deals on tire-related products and offers Buy Now, Pay Later financing options.

AI Music Catalog is an innovative application that utilizes artificial intelligence to curate and organize music based on user preferences. By leveraging advanced algorithms, the app recommends personalized playlists, suggests new tracks, and helps users discover music tailored to their tastes. With a user-friendly interface, AI Music Catalog simplifies the music discovery process, making it easier for users to explore and enjoy a wide range of genres and artists. Whether you're looking for new music or want to rediscover old favorites, this AI tool offers a seamless and personalized music experience.

Workshop Studio is an AI-powered tool that helps you create and manage your workshops. With Workshop Studio, you can easily create beautiful, engaging workshops that are sure to impress your audience. Our intuitive drag-and-drop interface makes it easy to add content, images, and videos to your workshops. You can also use our built-in templates to get started quickly.

DoMore.ai is a personalized AI tools catalog that offers a wide range of AI-powered tools to enhance productivity, creativity, and efficiency. With DoMore.ai, users can access a curated collection of AI tools tailored to their specific needs and preferences. The platform provides detailed descriptions, ratings, and reviews of each tool, making it easy for users to find the right tool for the job. DoMore.ai also offers a personalized recommendation engine that suggests tools based on user preferences and usage patterns. Whether you're a creative professional, a business owner, or a student, DoMore.ai has the tools you need to achieve your goals.

Almma.AI is the First A.I. Marketplace offering a variety of AI applications to enhance productivity and innovation. The platform features a range of AI tools for education, marketing, business, lifestyle, and more. Users can access personalized AI solutions for tasks like content generation, interview coaching, and data management. Almma.AI aims to revolutionize various industries by providing cutting-edge AI technologies to streamline workflows and boost efficiency.

Skillsoft is an online learning platform that provides a variety of courses and programs to help employees develop their skills and knowledge. The platform uses AI to personalize the learning experience for each user, and it offers a variety of features to help users track their progress and achieve their goals. Skillsoft is used by over 12,000 organizations worldwide, and it has been shown to improve employee engagement, productivity, and retention.

Columns is an AI tool designed to automate data storytelling. It helps users in creating compelling narratives and visualizations from their data without the need for manual intervention. With Columns, users can easily transform raw data into engaging stories, making data analysis more accessible and impactful. The tool offers a user-friendly interface and a range of customization options to tailor the storytelling process to individual needs.

MOTIV8 is an AI-powered self-growth planner application designed to help individuals explore ideas, organize life, and complete tasks. It offers a comprehensive platform for setting goals, managing tasks, and staying organized, while also providing personalized guidance and recommendations for personal growth and productivity. With the help of GPT-powered AI, users can break down goals into detailed task lists, discover new ideas, and seamlessly turn ideas into actionable tasks. MOTIV8 aims to enhance users' productivity, efficiency, and overall well-being by unlocking their true potential and empowering them to thrive in all areas of life.

SONOTELLER.AI is an AI song analyzer that analyzes song lyrics and music to provide a comprehensive summary about the song. It can identify musical attributes such as genres, subgenres, moods, instruments, BPM, and key. The tool is designed to simplify the way music lovers understand and organize their music collections, making it easier to discover and manage music across various platforms. SONOTELLER.AI is in beta phase, offering features like lyric analysis, music analysis, and automatic tagging to enhance music discovery and distribution.

Rubick AI is an advanced AI suite designed to revolutionize the eCommerce landscape for brands and sellers. It offers a comprehensive platform with solutions for cataloging, content generation, marketplace templates, and pricing intelligence. With features like data asset management, product attribute extraction, text analysis, and marketing insights, Rubick AI empowers eCommerce platforms at every stage of their growth. The application is known for its ability to streamline operations, enhance product visibility, and boost conversions through AI-enabled tools and services.

Claid.ai is an AI product photography suite designed to help eCommerce businesses enhance their product images quickly and efficiently. The tool offers guided background removal, color correction, and image upscaling features to transform ordinary product photos into high-quality marketing images. With Claid.ai, users can achieve consistency in their product catalog, improve conversions with enhanced images, and save time on editing tasks. The tool is trusted by over 10 million eCommerce images to elevate their visual content and boost online sales.

GPT Book Club is an AI-powered platform designed for book lovers who wish to stay updated on the latest literary trends without having to read every book. Users can interact with AI-generated guides and explore a wide range of book recommendations. The platform aims to provide a convenient and efficient way for users to discover new books and enhance their reading experience.

Cyanite.ai is an AI application designed for music tagging and similarity search. It offers a comprehensive set of features to analyze and categorize music, providing users with detailed tags, descriptions, and search capabilities. The platform leverages AI algorithms to enhance music discovery and catalog management, catering to musicians, music publishers, and other industry professionals. Cyanite.ai aims to revolutionize the way music is searched, discovered, and managed by combining cutting-edge technology with user-friendly interfaces.

Choco is an AI-powered platform designed for distributors and restaurants to streamline order processing and management. With Choco AI, orders from various sources like voicemails, SMS, emails, and third-party providers are automatically processed into the ERP system within seconds. The platform aims to enhance operational efficiency, reduce manual work and errors, improve customer satisfaction, and minimize waste in the food supply industry. Choco offers features such as digital order processing, AI-CRM solutions, marketing assistance, team management, and access to a comprehensive product catalog.

model-catalog is a repository containing standardized JSON descriptors for Large Language Model (LLM) model files. Each model is described in a JSON file with details about the model, authors, additional resources, available model files, and providers. The format captures factors like model size, architecture, file format, and quantization format. A Github action merges individual JSON files from the `models/` directory into a `catalog.json` file, which is validated using a JSON schema. Contributors can help by adding new model JSON files following the contribution process.

AI Toolkit for Visual Studio Code simplifies generative AI app development by bringing together cutting-edge AI development tools and models from Azure AI Studio Catalog and other catalogs like Hugging Face. Users can browse the AI models catalog, download them locally, fine-tune, test, and deploy them to the cloud. The toolkit offers actions such as finding supported models, testing model inference, fine-tuning models locally or remotely, and deploying fine-tuned models to the cloud. It also provides optimized AI models for Windows and a Q&A section for common issues and resolutions.

Visionatrix is a project aimed at providing easy use of ComfyUI workflows. It offers simplified setup and update processes, a minimalistic UI for daily workflow use, stable workflows with versioning and update support, scalability for multiple instances and task workers, multiple user support with integration of different user backends, LLM power for integration with Ollama/Gemini, and seamless integration as a service with backend endpoints and webhook support. The project is approaching version 1.0 release and welcomes new ideas for further implementation.

KubeAI is a highly scalable AI platform that runs on Kubernetes, serving as a drop-in replacement for OpenAI with API compatibility. It can operate OSS model servers like vLLM and Ollama, with zero dependencies and additional OSS addons included. Users can configure models via Kubernetes Custom Resources and interact with models through a chat UI. KubeAI supports serving various models like Llama v3.1, Gemma2, and Qwen2, and has plans for model caching, LoRA finetuning, and image generation.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

AI-Catalog is a curated list of AI tools, platforms, and resources across various domains. It serves as a comprehensive repository for users to discover and explore a wide range of AI applications. The catalog includes tools for tasks such as text-to-image generation, summarization, prompt generation, writing assistance, code assistance, developer tools, low code/no code tools, audio editing, video generation, 3D modeling, search engines, chatbots, email assistants, fun tools, gaming, music generation, presentation tools, website builders, education assistants, autonomous AI agents, photo editing, AI extensions, deep face/deep fake detection, text-to-speech, startup tools, SQL-related AI tools, education tools, and text-to-video conversion.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

Unitxt is a customizable library for textual data preparation and evaluation tailored to generative language models. It natively integrates with common libraries like HuggingFace and LM-eval-harness and deconstructs processing flows into modular components, enabling easy customization and sharing between practitioners. These components encompass model-specific formats, task prompts, and many other comprehensive dataset processing definitions. The Unitxt-Catalog centralizes these components, fostering collaboration and exploration in modern textual data workflows. Beyond being a tool, Unitxt is a community-driven platform, empowering users to build, share, and advance their pipelines collaboratively.

Podman AI Lab is an open source extension for Podman Desktop designed to work with Large Language Models (LLMs) on a local environment. It features a recipe catalog with common AI use cases, a curated set of open source models, and a playground for learning, prototyping, and experimentation. Users can quickly and easily get started bringing AI into their applications without depending on external infrastructure, ensuring data privacy and security.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

Contoso Chat is a Python sample demonstrating how to build, evaluate, and deploy a retail copilot application with Azure AI Studio using Promptflow with Prompty assets. The sample implements a Retrieval Augmented Generation approach to answer customer queries based on the company's product catalog and customer purchase history. It utilizes Azure AI Search, Azure Cosmos DB, Azure OpenAI, text-embeddings-ada-002, and GPT models for vectorizing user queries, AI-assisted evaluation, and generating chat responses. By exploring this sample, users can learn to build a retail copilot application, define prompts using Prompty, design, run & evaluate a copilot using Promptflow, provision and deploy the solution to Azure using the Azure Developer CLI, and understand Responsible AI practices for evaluation and content safety.

The Google Cloud Applied AI Engineering repository provides reference guides, blueprints, code samples, and hands-on labs developed by the Google Cloud Applied AI Engineering team. It contains resources for Generative AI on Vertex AI, including code samples and hands-on labs demonstrating the use of Generative AI models and tools in Vertex AI. Additionally, it offers reference guides and blueprints that compile best practices and prescriptive guidance for running large-scale AI/ML workloads on Google Cloud AI/ML infrastructure.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

This repository contains reference architectures and test cases for distributed model training with Amazon SageMaker Hyperpod, AWS ParallelCluster, AWS Batch, and Amazon EKS. The test cases cover different types and sizes of models as well as different frameworks and parallel optimizations (Pytorch DDP/FSDP, MegatronLM, NemoMegatron...).

OpenVINO™ Model Server (OVMS) is a high-performance system for serving models. Implemented in C++ for scalability and optimized for deployment on Intel architectures, the model server uses the same architecture and API as TensorFlow Serving and KServe while applying OpenVINO for inference execution. Inference service is provided via gRPC or REST API, making deploying new algorithms and AI experiments easy.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

Unity Catalog is an open and interoperable catalog for data and AI, supporting multi-format tables, unstructured data, and AI assets. It offers plugin support for extensibility and interoperates with Delta Sharing protocol. The catalog is fully open with OpenAPI spec and OSS implementation, providing unified governance for data and AI with asset-level access control enforced through REST APIs.

Provides comprehensive guidance on educational standards and assessments.

A tool for historians to analyze and catalog historical images and documents.

GPT expert on CISA's KEV Catalog and CVE existence check

Pokémon card cataloging assistant with Zapier integration.

Expert in esoteric knowledge such as Neoplatonism, Gnosticsim, Hermeticism, Mythology, and more!