Best AI tools for< Test-preparer >

Quant Prep AI is an AI Chrome extension designed for GRE & GMAT quantitative preparation. It assists users in identifying and practicing strategies for solving quantitative questions. The extension provides tips and detailed solutions for quant problems, helping users enhance their quantitative skills efficiently.

APEUni is an AI-powered platform designed to help users practice for the Pearson Test of English (PTE) exam. It offers various AI scoring features for different sections of the PTE exam, such as Speaking, Writing, Reading, and Listening. Users can access practice materials, study guides, and receive detailed score reports to improve their performance. APEUni aims to provide a comprehensive and efficient way for PTE test takers to prepare for the exam.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

PrepGenius.ai is an AI-driven test preparation platform designed to revolutionize the way students prepare for AP courses, college admission tests, and more. The platform offers personalized study plans, real-time feedback, interactive learning tools, and comprehensive resources to help students understand their strengths and weaknesses. With PrepGenius.ai, students can study smarter, receive tailored feedback, and track their progress to improve their test scores effectively.

The AI-powered Cambridge English Test platform offers exercises for English levels B1, B2, C1, and C2. Users can select exercise types such as Reading and Use of English, including activities like Open Cloze, Multiple Choice, Word Formation, and more. The AI, developed by Shining Apps in partnership with Use of English PRO, provides a unique learning experience by generating exercises from a database of over 5000 official exams. It uses advanced Natural Language Processing (NLP) to understand context, tweak exercises, and offer detailed feedback for effective learning.

CasperPractice is an AI-powered toolkit designed to help individuals prepare for the Casper test, an open-response situational judgment test used for admissions to various professional schools. The platform offers personalized practice scenarios, instant quartile grading, detailed feedback, video answers, and a fully simulated test environment. With a large question bank and unlimited practice options, users can improve their test-taking skills and aim for a top quartile score. CasperPractice is known for its affordability, instant feedback, and realistic simulation, making it a valuable resource for anyone preparing for the Casper test.

The US Citizenship Practice Exam website is an AI-powered platform designed to help users study for the US naturalization test. The site offers a practice exam with 100 questions, all graded by an AI created by OpenAI. Users are required to answer 10 questions correctly out of the 100 to pass. The actual naturalization test is an oral exam graded by a USCIS officer. The website is created by Evan Conrad, who works on AI in San Francisco. It is open source on Github and aims to support civic work related to immigration processes.

PrepAI is an advanced test generator that uses AI to help educators create high-quality assessments quickly and easily. With PrepAI, teachers can save time, engage students with unique questions, and prepare them for success. PrepAI offers a variety of features to make test creation easy, including multiple content input options, various question formats, and an easy-to-use dashboard. PrepAI also offers a variety of advantages for educators, including the ability to analyze higher-order thinking skills, conduct tests effortlessly, and access unlimited question sets.

Testmint.ai is an online mock test platform designed to help users prepare for competitive exams. It offers a wide range of practice tests and study materials to enhance exam readiness. The platform is user-friendly and provides a simulated exam environment to improve test-taking skills. Testmint.ai aims to assist students and professionals in achieving their academic and career goals by offering a comprehensive and effective exam preparation solution.

SmallTalk2Me is an AI-powered simulator designed to help users improve their spoken English. It offers a range of features, including mock job interviews, IELTS speaking test simulations, and daily stories and courses. The platform uses AI to provide users with instant feedback on their performance, helping them to identify areas for improvement and track their progress over time.

The Princeton Review is an AI-based test preparation and tutoring platform offering personalized academic support, test prep courses, and college admissions counseling. With over 43 years of industry experience and a track record of helping millions of students, The Princeton Review uses sophisticated AI technology to provide students with tailored learning experiences, expert-led videos, interactive reports, and feedback tools for essays and homework. The platform covers a wide range of subjects and exams, from K-12 academics to graduate and professional tests like SAT, ACT, MCAT, LSAT, GRE, GMAT, and more. Additionally, it offers services for college admissions counseling, school partnerships, and international licensing.

Interview with AI is an online platform that helps users prepare for job interviews using artificial intelligence (AI). The platform offers a range of features, including personalized roadmaps, interactive quizzes, and mock interviews with AI companions. Interview with AI is designed to help users improve their interview skills, learn new concepts, and increase their chances of getting their dream job.

TutorOcean is an online tutoring platform that connects students with expert tutors from around the world. Students can search for tutors based on subject, language, price, and availability, and then book sessions directly with the tutor of their choice. TutorOcean offers a wide range of subjects, including math, science, languages, test prep, and more. Tutors on TutorOcean come from a variety of backgrounds and have different levels of experience and qualifications. Many tutors are certified teachers, while others have extensive experience in their subject area. Students can view vetted tutor profiles and ratings to help them choose the right tutor for their needs.

ExamSamur.ai is an AI-powered platform designed to help students prepare for exams efficiently. It offers a wide range of study materials, practice tests, and personalized study plans to enhance learning outcomes. The platform utilizes advanced algorithms to analyze students' performance and provide targeted feedback for improvement. With a user-friendly interface and interactive features, ExamSamur.ai aims to make exam preparation engaging and effective for students of all levels.

PrepSup is a powerful AI-powered learning platform that provides students with personalized study materials, an AI tutor, and a PDF analyzer to help them excel in their studies. With PrepSup, students can create and share flashcards, access a vast library of pre-made flashcards, and get instant feedback on their progress. The AI tutor provides personalized recommendations and guidance, helping students identify areas for improvement and develop effective study strategies. The PDF analyzer extracts key concepts and insights from PDFs, making it easier for students to understand and retain information. Whether you're preparing for a test, writing a paper, or simply trying to learn a new subject, PrepSup is the perfect tool to help you succeed.

Kippy is an AI language tutor application that allows users to practice speaking in various languages anytime, anywhere. It offers real-life conversations, pronunciation improvement, progress tracking, unlimited conversations powered by ChatGPT, natural human-like voices, instant 2-way translation, personal phrasebooks, and more. Users can engage in role-playing scenarios, test their pronunciation, track their vocabulary growth, and set daily speaking goals. The app supports English, Spanish, German, Italian, French, Korean, Japanese, Chinese, and Russian languages.

Speak is a language learning app that uses AI to help you improve your speaking skills. It offers a variety of features, including personalized lessons, instant feedback, and a virtual tutor. Speak is designed to be fun and engaging, and it can help you learn a new language quickly and easily.

Ripeti Con Me is an online Italian language learning platform that uses audio courses, bilingual readings, and an AI tutor to help learners master Italian like a pro. The platform is designed by a language expert and offers a variety of features to help learners succeed, including grammar lessons, vocabulary building exercises, and speaking practice. Ripeti Con Me is a great option for learners of all levels, from beginners to advanced speakers.

Learn Languages AI is a language learning tool that uses artificial intelligence to help users learn new languages. The tool is built on Telegram and allows users to speak, text, and play with an AI teacher. Learn Languages AI is designed to help users reach all of their language learning goals. The tool is free to use and does not require an account.

Hi Talk is a GPT-powered AI for language learning. Speak with AI and chat on various topics, either by writing or speaking, while receiving messages with a realistic voice. Available 24/7 — available in 30 languages

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

Ianvs is a distributed synergy AI benchmarking project incubated in KubeEdge SIG AI. It aims to test the performance of distributed synergy AI solutions following recognized standards, providing end-to-end benchmark toolkits, test environment management tools, test case control tools, and benchmark presentation tools. It also collaborates with other organizations to establish comprehensive benchmarks and related applications. The architecture includes critical components like Test Environment Manager, Test Case Controller, Generation Assistant, Simulation Controller, and Story Manager. Ianvs documentation covers quick start, guides, dataset descriptions, algorithms, user interfaces, stories, and roadmap.

LLM-FuzzX is an open-source user-friendly fuzz testing tool for large language models (e.g., GPT, Claude, LLaMA), equipped with advanced task-aware mutation strategies, fine-grained evaluation, and jailbreak detection capabilities. It helps researchers and developers quickly discover potential security vulnerabilities and enhance model robustness. The tool features a user-friendly web interface for visual configuration and real-time monitoring, supports various advanced mutation methods, integrates RoBERTa model for real-time jailbreak detection and evaluation, supports multiple language models like GPT, Claude, LLaMA, provides visualization analysis with seed flowcharts and experiment data statistics, and offers detailed logging support for main, mutation, and jailbreak logs.

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

SimpleAICV_pytorch_training_examples is a repository that provides simple training and testing examples for various computer vision tasks such as image classification, object detection, semantic segmentation, instance segmentation, knowledge distillation, contrastive learning, masked image modeling, OCR text detection, OCR text recognition, human matting, salient object detection, interactive segmentation, image inpainting, and diffusion model tasks. The repository includes support for multiple datasets and networks, along with instructions on how to prepare datasets, train and test models, and use gradio demos. It also offers pretrained models and experiment records for download from huggingface or Baidu-Netdisk. The repository requires specific environments and package installations to run effectively.

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

The Lakera PINT Benchmark provides a neutral evaluation method for prompt injection detection systems, offering a dataset of English inputs with prompt injections, jailbreaks, benign inputs, user-agent chats, and public document excerpts. The dataset is designed to be challenging and representative, with plans for future enhancements. The benchmark aims to be unbiased and accurate, welcoming contributions to improve prompt injection detection. Users can evaluate prompt injection detection systems using the provided Jupyter Notebook. The dataset structure is specified in YAML format, allowing users to prepare their datasets for benchmarking. Evaluation examples and resources are provided to assist users in evaluating prompt injection detection models and tools.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

Hercules is the world’s first open-source testing agent designed to handle the toughest testing tasks for modern web applications. It turns simple Gherkin steps into fully automated end-to-end tests, making testing simple, reliable, and efficient. Hercules adapts to various platforms like Salesforce and is suitable for CI/CD pipelines. It aims to democratize and disrupt test automation, making top-tier testing accessible to everyone. The tool is transparent, reliable, and community-driven, empowering teams to deliver better software. Hercules offers multiple ways to get started, including using PyPI package, Docker, or building and running from source code. It supports various AI models, provides detailed installation and usage instructions, and integrates with Nuclei for security testing and WCAG for accessibility testing. The tool is production-ready, open core, and open source, with plans for enhanced LLM support, advanced tooling, improved DOM distillation, community contributions, extensive documentation, and a bounty program.

xFasterTransformer is an optimized solution for Large Language Models (LLMs) on the X86 platform, providing high performance and scalability for inference on mainstream LLM models. It offers C++ and Python APIs for easy integration, along with example codes and benchmark scripts. Users can prepare models in a different format, convert them, and use the APIs for tasks like encoding input prompts, generating token ids, and serving inference requests. The tool supports various data types and models, and can run in single or multi-rank modes using MPI. A web demo based on Gradio is available for popular LLM models like ChatGLM and Llama2. Benchmark scripts help evaluate model inference performance quickly, and MLServer enables serving with REST and gRPC interfaces.

ML-Bench is a tool designed to evaluate large language models and agents for machine learning tasks on repository-level code. It provides functionalities for data preparation, environment setup, usage, API calling, open source model fine-tuning, and inference. Users can clone the repository, load datasets, run ML-LLM-Bench, prepare data, fine-tune models, and perform inference tasks. The tool aims to facilitate the evaluation of language models and agents in the context of machine learning tasks on code repositories.

MultiPL-E is a system for translating unit test-driven neural code generation benchmarks to new languages. It is part of the BigCode Code Generation LM Harness and allows for evaluating Code LLMs using various benchmarks. The tool supports multiple versions with improvements and new language additions, providing a scalable and polyglot approach to benchmarking neural code generation. Users can access a tutorial for direct usage and explore the dataset of translated prompts on the Hugging Face Hub.

Bench is a tool for evaluating LLMs for production use cases. It provides a standardized workflow for LLM evaluation with a common interface across tasks and use cases. Bench can be used to test whether open source LLMs can do as well as the top closed-source LLM API providers on specific data, and to translate the rankings on LLM leaderboards and benchmarks into scores that are relevant for actual use cases.

Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.

Eval-Scope is a framework for evaluating and improving large language models (LLMs). It provides a set of commonly used test datasets, metrics, and a unified model interface for generating and evaluating LLM responses. Eval-Scope also includes an automatic evaluator that can score objective questions and use expert models to evaluate complex tasks. Additionally, it offers a visual report generator, an arena mode for comparing multiple models, and a variety of other features to support LLM evaluation and development.

CodeGPT is a CLI tool written in Go that helps you write git commit messages or do a code review brief using ChatGPT AI (gpt-3.5-turbo, gpt-4 model) and automatically installs a git prepare-commit-msg hook. It supports Azure OpenAI Service or OpenAI API, conventional commits specification, Git prepare-commit-msg Hook, customizing the number of lines of context in diffs, excluding files from the git diff command, translating commit messages into different languages, using socks or custom network HTTP proxies, specifying model lists, and doing brief code reviews.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

AiOS is a tool for human pose and shape estimation, performing human localization and SMPL-X estimation in a progressive manner. It consists of body localization, body refinement, and whole-body refinement stages. Users can download datasets for evaluation, SMPL-X body models, and AiOS checkpoint. Installation involves creating a conda virtual environment, installing PyTorch, torchvision, Pytorch3D, MMCV, and other dependencies. Inference requires placing the video for inference and pretrained models in specific directories. Test results are provided for NMVE, NMJE, MVE, and MPJPE on datasets like BEDLAM and AGORA. Users can run scripts for AGORA validation, AGORA test leaderboard, and BEDLAM leaderboard. The tool acknowledges codes from MMHuman3D, ED-Pose, and SMPLer-X.

ZipNN is a lossless and near-lossless compression library optimized for numbers/tensors in the Foundation Models environment. It automatically prepares data for compression based on its type, allowing users to focus on core tasks without worrying about compression complexities. The library delivers effective compression techniques for different data types and structures, achieving high compression ratios and rates. ZipNN supports various compression methods like ZSTD, lz4, and snappy, and provides ready-made scripts for file compression/decompression. Users can also manually import the package to compress and decompress data. The library offers advanced configuration options for customization and validation tests for different input and compression types.

Sports-betting is a Python library for implementing betting strategies and analyzing sports data. It provides tools for collecting, processing, and visualizing sports data to make informed betting decisions. The library includes modules for scraping data from sports websites, calculating odds, simulating betting strategies, and evaluating performance. With sports-betting, users can automate betting processes, test different strategies, and improve their betting outcomes.

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