Best AI tools for< Run Classification Models >

PhotoPrism is an AI-Powered Photos App for the Decentralized Web that utilizes cutting-edge technologies to automatically tag and find pictures. It allows users to organize and access their photos effortlessly, without compromising privacy. The application offers features like browsing all photos and videos, powerful search filters, world maps for trip memories, live photo playback, facial recognition, and automatic picture classification based on content and location. PhotoPrism is self-funded and independent, ensuring data privacy and transparency. Users can run the app on a private server, in the cloud, or at home.

The Run Recommender is a web-based tool that helps runners find the perfect pair of running shoes. It uses a smart algorithm to suggest options based on your input, giving you a starting point in your search for the perfect pair. The Run Recommender is designed to be user-friendly and easy to use. Simply input your shoe width, age, weight, and other details, and the Run Recommender will generate a list of potential shoes that might suit your running style and body. You can also provide information about your running experience, distance, and frequency, and the Run Recommender will use this information to further refine its suggestions. Once you have a list of potential shoes, you can click on each shoe to learn more about it, including its features, benefits, and price. You can also search for the shoe on Amazon to find the best deals.

Dora is a no-code 3D animated website design platform that allows users to create stunning 3D and animated visuals without writing a single line of code. With Dora, designers, freelancers, and creative professionals can focus on what they do best: designing. The platform is tailored for professionals who prioritize design aesthetics without wanting to dive deep into the backend. Dora offers a variety of features, including a drag-and-connect constraint layout system, advanced animation capabilities, and pixel-perfect usability. With Dora, users can create responsive 3D and animated websites that translate seamlessly across devices.

Learn Playwright is a comprehensive platform offering resources for learning end-to-end testing using the Playwright automation framework. It provides a blog with in-depth subjects about end-to-end testing, an 'Ask AI' feature for querying ChatGPT about Playwright, and a Dev Tools section that serves as an all-in-one toolbox for QA engineers. Additionally, users can explore QA job opportunities, access answered questions about Playwright, browse a Discord forum archive, watch tutorials and conference talks, utilize a browser extension for generating Playwright locators, and refer to a QA Wiki for definitions of common end-to-end testing terms.

Symphony is an AI-powered programming tool that allows users to write programs using natural language. It simplifies the coding process by enabling users to interact with the tool through spoken language, making it easier for both beginners and experienced programmers to create code. Symphony leverages advanced natural language processing algorithms to understand and interpret user commands, translating them into executable code. With Symphony, users can seamlessly communicate their programming ideas without the need to write complex code syntax, enhancing productivity and efficiency in software development.

aify is an AI-native application framework and runtime that allows users to build AI-native applications quickly and easily. With aify, users can create applications by simply writing a YAML file. The platform also offers a ready-to-use AI chatbot UI for seamless integration. Additionally, aify provides features such as Emoji express for searching emojis by semantics. The framework is open source under the MIT license, making it accessible to developers of all levels.

Lumora is an AI tool designed to help users efficiently manage, optimize, and test prompts for various AI platforms. It offers features such as prompt organization, enhancement, testing, and development. Lumora aims to improve prompt outcomes and streamline prompt management for teams, providing a user-friendly interface and a playground for experimentation. The tool also integrates with various AI models for text, image, and video generation, allowing users to optimize prompts for better results.

Dora is an AI-powered platform that enables users to create 3D animated websites without the need for coding. It caters to designers, freelancers, and creative professionals who seek to design visually captivating websites effortlessly. With Dora, users can craft mesmerizing 3D and animated visuals that are responsive and seamlessly translate across devices. The platform is designed for professionals who prioritize design aesthetics and offers a no-code experience for those transitioning from other design tools. Dora leverages advanced AI algorithms to generate, customize, and deploy stunning landing pages, revolutionizing the web design process.

Magnet is an AI coding assistant that helps product teams fix issues, share AI threads, and organize projects. It integrates with Linear, GitHub, and Notion, and provides auto-suggested files and code files for personalized and accurate AI recommendations. Magnet also offers prompt templates to help users get started and suggests quick fixes for bugs or enhancements.

Devath is the world's first AI-powered SmartHome platform that revolutionizes the way users interact with their smart devices. It eliminates the need for writing extensive lines of code by allowing users to simply give instructions to the AI for seamless device control. With features like splash resistance and responsive design, Devath offers a user-friendly experience for managing smart home functionalities. The platform also enables developers to preview and test their apps before submission, providing a 99% faster publishing process. Devath is continuously evolving with user feedback and aims to enhance the SmartHome experience through AI copilots and customizable features. With Devath, users can control their devices from the web and enjoy free unlimited access to the AI era of SmartHome.

One-Commerce is an AI-powered application designed to streamline the e-commerce listing process. It utilizes gemini technology to automatically generate detailed product descriptions, specifications, and SEO keywords from a single image. With its innovative approach, One-Commerce aims to simplify and enhance the online selling experience for e-commerce businesses.

Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate various types of content such as images, text, music, and speech with just one line of code. It offers a platform where users can access a wide range of AI models contributed by the community, fine-tune models with their own data, and deploy custom models using Cog, an open-source tool for packaging machine learning models.

Sessions is a cloud-based video conferencing and webinar platform that offers a range of features to help businesses run successful online meetings and events. With Sessions, users can create interactive agendas, share screens, record meetings, and host webinars with up to 1000 participants. Sessions also integrates with a variety of third-party tools, including Google Drive, Dropbox, and Slack, making it easy to collaborate with colleagues and share files. Additionally, Sessions offers a number of AI-powered features, such as automatic transcription and translation, to help users get the most out of their meetings.

CALA is a leading fashion platform that unifies design, development, production, and logistics into a single, digital platform. It provides tools and support to automate and optimize the supply chain from start to finish. CALA also offers a network of designers and suppliers, as well as AI-powered design tools to help generate moodboards, fresh ideas, and more.

Effy AI is a free performance management software for teams. It is AI-powered and backed by Run your first 360 review in 60 sec. Fast, and stress-free 360 feedback and performance review software build for teams. With Effy AI, you can collect reviews from different sources such as self, peer, manager, and subordinate evaluations. The platform goes even further by allowing employees to suggest particular peers and seek approval from their manager, giving them a voice in their reviews. Effy AI uses cutting-edge artificial intelligence to carefully process reviewers' answers and generate comprehensive reports for each employee based on the review responses.

Tely is an autonomous AI agent that helps businesses run B2B content marketing. It uses machine learning to understand your product, build domain expertise, run SEO optimization, and create a content plan. Tely can also personalize your content with infographics, code snippets, experts' quotes, and call to actions. With Tely, you can drive sales with expert-level content on autopilot, reduce customer acquisition cost, increase conversion rate, and save money on marketing expenses.

GPUX is a cloud platform that provides access to GPUs for running AI workloads. It offers a variety of features to make it easy to deploy and run AI models, including a user-friendly interface, pre-built templates, and support for a variety of programming languages. GPUX is also committed to providing a sustainable and ethical platform, and it has partnered with organizations such as the Climate Leadership Council to reduce its carbon footprint.

Lemon Squeezy is an all-in-one platform designed for software companies to handle payments, subscriptions, global tax compliance, fraud prevention, and more. It offers features like global tax compliance, borderless SaaS payments, instant payment methods, local currency support, AI fraud prevention, and failed payment recovery. The platform also provides tools for ecommerce, marketing, reporting, and developer integration. Lemon Squeezy aims to simplify running a software business by offering a comprehensive solution for various business needs.

Stablematic is a web-based platform that allows users to run Stable Diffusion and other machine learning models without the need for local setup or hardware limitations. It provides a user-friendly interface, pre-installed plugins, and dedicated GPU resources for a seamless and efficient workflow. Users can generate images and videos from text prompts, merge multiple models, train custom models, and access a range of pre-trained models, including Dreambooth and CivitAi models. Stablematic also offers API access for developers and dedicated support for users to explore and utilize the capabilities of Stable Diffusion and other machine learning models.

Runday is a business-to-business software as a service (SaaS) company that provides artificial intelligence (AI)-powered agents to help businesses with sales, service, marketing, and recruiting. Runday's AI agents can be used to answer customer questions, book appointments, collect payments, and more. The company's software is used by over 30,000 businesses and has generated over $1 billion in sales for its customers.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

MediaPipe-rs is a Rust library designed for MediaPipe tasks on WasmEdge WASI-NN. It offers easy-to-use low-code APIs similar to mediapipe-python, with low overhead and flexibility for custom media input. The library supports various tasks like object detection, image classification, gesture recognition, and more, including TfLite models, TF Hub models, and custom models. Users can create task instances, run sessions for pre-processing, inference, and post-processing, and speed up processing by reusing sessions. The library also provides support for audio tasks using audio data from symphonia, ffmpeg, or raw audio. Users can choose between CPU, GPU, or TPU devices for processing.

FastFit is a Python package designed for fast and accurate few-shot classification, especially for scenarios with many semantically similar classes. It utilizes a novel approach integrating batch contrastive learning and token-level similarity score, significantly improving multi-class classification performance in speed and accuracy across various datasets. FastFit provides a convenient command-line tool for training text classification models with customizable parameters. It offers a 3-20x improvement in training speed, completing training in just a few seconds. Users can also train models with Python scripts and perform inference using pretrained models for text classification tasks.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates tasks such as data cleaning, preprocessing, and complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. It aims to expedite the data analysis process, making it accessible to all, regardless of their expertise in data analysis. The tool is built to empower users to process data and achieve high-quality visualizations with unparalleled efficiency, and to execute high-performance modeling with the best strategies. Future enhancements include Natural Language Processing (NLP), neural networks, and object detection utilizing YOLO, broadening its capabilities to meet diverse data analysis needs.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

This repository provides advanced AI explainability for PyTorch, offering state-of-the-art methods for Explainable AI in computer vision. It includes a comprehensive collection of Pixel Attribution methods for various tasks like Classification, Object Detection, Semantic Segmentation, and more. The package supports high performance with full batch image support and includes metrics for evaluating and tuning explanations. Users can visualize and interpret model predictions, making it suitable for both production and model development scenarios.

ztachip is a RISCV accelerator designed for vision and AI edge applications, offering up to 20-50x acceleration compared to non-accelerated RISCV implementations. It features an innovative tensor processor hardware to accelerate various vision tasks and TensorFlow AI models. ztachip introduces a new tensor programming paradigm for massive processing/data parallelism. The repository includes technical documentation, code structure, build procedures, and reference design examples for running vision/AI applications on FPGA devices. Users can build ztachip as a standalone executable or a micropython port, and run various AI/vision applications like image classification, object detection, edge detection, motion detection, and multi-tasking on supported hardware.

The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.

DeepPavlov is an open-source conversational AI library built on PyTorch. It is designed for the development of production-ready chatbots and complex conversational systems, as well as for research in the area of NLP and dialog systems. The library offers a wide range of models for tasks such as Named Entity Recognition, Intent/Sentence Classification, Question Answering, Sentence Similarity/Ranking, Syntactic Parsing, and more. DeepPavlov also provides embeddings like BERT, ELMo, and FastText for various languages, along with AutoML capabilities and integrations with REST API, Socket API, and Amazon AWS.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

Hands-On Large Language Models is a repository containing code examples from the book 'The Illustrated LLM Book' by Jay Alammar and Maarten Grootendorst. The repository provides practical tools and concepts for using Large Language Models with over 250 custom-made figures. It covers topics such as language model introduction, tokens and embeddings, transformer LLMs, text classification, text clustering, prompt engineering, text generation techniques, semantic search, multimodal LLMs, text embedding models, fine-tuning representation models, and fine-tuning generation models. The examples are designed to be run on Google Colab with T4 GPU support, but can be adapted to other cloud platforms as well.

This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for **fast prototyping** and **prompting** , and turning unstructured responses into **robust outputs** for various NLP tasks, **no training data** required. It supports open-source LLMs hosted on Hugging Face 🤗: Falcon, Dolly, Llama 2, OpenLLaMA, StableLM, Mistral. Integration with LangChain 🦜️🔗 - all `langchain` models and features can be used in `spacy-llm`. Tasks available out of the box: Named Entity Recognition, Text classification, Lemmatization, Relationship extraction, Sentiment analysis, Span categorization, Summarization, Entity linking, Translation, Raw prompt execution for maximum flexibility. Soon: Semantic role labeling. Easy implementation of **your own functions** via spaCy's registry for custom prompting, parsing and model integrations. For an example, see here. Map-reduce approach for splitting prompts too long for LLM's context window and fusing the results back together

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

The Intel® AI Reference Models repository contains links to pre-trained models, sample scripts, best practices, and tutorials for popular open-source machine learning models optimized by Intel to run on Intel® Xeon® Scalable processors and Intel® Data Center GPUs. It aims to replicate the best-known performance of target model/dataset combinations in optimally-configured hardware environments. The repository will be deprecated upon the publication of v3.2.0 and will no longer be maintained or published.

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