Best AI tools for< Test On Hopper >

Cirrascale Cloud Services is an AI tool that offers cloud solutions for Artificial Intelligence applications. The platform provides a range of cloud services and products tailored for AI innovation, including NVIDIA GPU Cloud, AMD Instinct Series Cloud, Qualcomm Cloud, Graphcore, Cerebras, and SambaNova. Cirrascale's AI Innovation Cloud enables users to test and deploy on leading AI accelerators in one cloud, democratizing AI by delivering high-performance AI compute and scalable deep learning solutions. The platform also offers professional and managed services, tailored multi-GPU server options, and high-throughput storage and networking solutions to accelerate development, training, and inference workloads.

SmartExam is an AI-powered platform designed to assist students in exam preparation by generating test exams based on uploaded lectures. The tool aims to help students succeed in their exams by providing tailored interactive exams and study materials. SmartExam is trusted by top students worldwide and offers a user-friendly experience. Users can upload lecture materials in PDF format, generate test exams in seconds, and download them for further training. The platform reduces exam preparation time by 50% and has received positive feedback for its efficiency and effectiveness.

Face Symmetry Test is an AI-powered tool that analyzes the symmetry of facial features by detecting key landmarks such as eyes, nose, mouth, and chin. Users can upload a photo to receive a personalized symmetry score, providing insights into the balance and proportion of their facial features. The tool uses advanced AI algorithms to ensure accurate results and offers guidelines for improving the accuracy of the analysis. Face Symmetry Test is free to use and prioritizes user privacy and security by securely processing uploaded photos without storing or sharing data with third parties.

Prompt Hippo is an AI tool designed as a side-by-side LLM prompt testing suite to ensure the robustness, reliability, and safety of prompts. It saves time by streamlining the process of testing LLM prompts and allows users to test custom agents and optimize them for production. With a focus on science and efficiency, Prompt Hippo helps users identify the best prompts for their needs.

ABtesting.ai is an AI-powered A/B testing software that helps businesses optimize their landing pages for conversions. It uses GPT-3 to generate automated text suggestions for headlines, copy, and call to actions, saving businesses time and effort. The software also automatically chooses the best combinations of elements to show to users, boosting conversion rates in the process. ABtesting.ai is easy to use and requires no manual work, making it a great option for businesses of all sizes.

U-xer is an innovative automation tool developed by Quality Museum Software Testing Services. It is designed to meet a broad range of needs, including Robotic Process Automation (RPA), test automation, and bot development. Crafted with user flexibility in mind, U-xer aims to be a user-friendly solution for your automation requirements! U-xer's unique screen recognition models interpret screens in the same way that humans do. This enables non-technical users to automate simple tasks, while allowing advanced users to tackle more complex tasks with ease. With U-xer, you can automate anything, anywhere, whether it's Web or Desktop. U-xer works seamlessly across all platforms with just a screenshot. Unlike other tools, U-xer interprets screens just like a human does, enabling more natural and accurate automation of a wide range of tasks.

BenchLLM is an AI tool designed for AI engineers to evaluate LLM-powered apps by running and evaluating models with a powerful CLI. It allows users to build test suites, choose evaluation strategies, and generate quality reports. The tool supports OpenAI, Langchain, and other APIs out of the box, offering automation, visualization of reports, and monitoring of model performance.

LLM Clash is a web-based application that allows users to compare the outputs of different large language models (LLMs) on a given task. Users can input a prompt and select which LLMs they want to compare. The application will then display the outputs of the LLMs side-by-side, allowing users to compare their strengths and weaknesses.

PaletteMaker is a unique tool for creative professionals and color lovers that allows you to create color palettes and test their behavior in pre-made design examples from the most common creative fields such as Logo design, UI/UX, Patterns, Posters and more. Check Color Behavior See how color works together in various of situations in graphic design. AI Color Palettes Filter palettes of different color tone and number of colors. Diverse Creative Fields Check your colors on logo, ui design, posters, illustrations and more. Create Palettes On-The-Go Instantly see the magic of creating color palettes. Totally Free PaletteMaker is created by professional designers, it’s completely free to use and forever will be. Powerful Export Export your palette in various formats, such as Procreate, Adobe ASE, Image, and even Code.

Sofy is a revolutionary no-code testing platform for mobile applications that integrates AI to streamline the testing process. It offers features such as manual and ad-hoc testing, no-code automation, AI-powered test case generation, and real device testing. Sofy helps app development teams achieve high-quality releases by simplifying test maintenance and ensuring continuous precision. With a focus on efficiency and user experience, Sofy is trusted by top industries for its all-in-one testing solution.

Functionize is an AI-powered test automation platform that helps enterprises improve their product quality and release faster. It uses machine learning to automate test creation, maintenance, and execution, and provides a range of features to help teams collaborate and manage their testing process. Functionize integrates with popular CI/CD tools and DevOps pipelines, and offers a range of pricing options to suit different needs.

Virtuoso is an AI-powered, end-to-end functional testing tool for web applications. It uses Natural Language Programming, Machine Learning, and Robotic Process Automation to automate the testing process, making it faster and more efficient. Virtuoso can be used by QA managers, practitioners, and senior executives to improve the quality of their software applications.

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Trivai is an AI-powered trivia question generator that allows users to create trivia questions on any topic. With Trivai, you can generate random trivia questions or search for specific questions by category. Trivai is a great way to test your knowledge, learn new things, and have fun.

Magic Regex Generator is an AI-powered tool that simplifies the process of generating, testing, and editing Regular Expression patterns. Users can describe what they want to match in English, and the AI generates the corresponding regex in the editor for testing and refining. The tool is designed to make working with regex easier and more efficient, allowing users to focus on meaningful tasks without getting bogged down in complex pattern matching.

Rapid is a comprehensive API Hub that offers a seamless connected experience for developers to build, use, and share APIs. It features an Enterprise Marketplace, Public Marketplace, and security solutions. With over 40,000 APIs, 12,000 API publishers, and 200,000 monthly active subscribers, Rapid is a leading platform in the API ecosystem. The platform enables businesses, partners, and developers to create innovative products and drive new revenue streams through API management and monetization.

FaceSymAI is an online tool that utilizes advanced AI algorithms to analyze and determine the symmetry of your face. By uploading a photo, the AI examines your facial features, including the eyes, nose, mouth, and overall structure, to provide an accurate assessment of your facial symmetry. The analysis is based on mathematical and statistical methods, ensuring reliable and precise results. FaceSymAI is designed to be user-friendly and accessible, offering a free service to everyone. The uploaded photos are treated with utmost confidentiality and are not stored or used for any other purpose, ensuring your privacy is respected.

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The AI Toolbox for Innovators is a platform that offers a suite of free AI tools to help users test, pivot, and generate ideas quickly. The website is constantly updating with new tools and is currently undergoing a rebuild to incorporate the latest advancements in the AI field. Users can access tools like Brainstorm Buddy, Future Scenario Writer, Interview Script, Research Brief, and Opportunity Scores to enhance their innovation and problem-solving capabilities. The platform is brought to you by Board of Innovation, a global innovation firm focused on creating tomorrow's products, services, and businesses.

Pezzo is an open-source platform that enables developers to build, test, monitor, and ship AI features quickly and efficiently. It provides a range of powerful features to streamline the workflow, including prompt management, observability, troubleshooting, and collaboration tools. With Pezzo, teams can deliver impactful AI features in sync and optimize for cost and performance.

ppl.llm.kernel.cuda is a primitive cuda kernel library for ppl.nn.llm system, designed for Ampere and Hopper architectures. It requires Linux running on x86_64 or arm64 CPUs with specific versions of GCC, CMake, Git, and CUDA Toolkit. Users can follow the provided Quick Start guide to install prerequisites, clone the source code, and build from source. The project is distributed under the Apache License, Version 2.0.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

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.

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.

Marlin is a highly optimized FP16xINT4 matmul kernel designed for large language model (LLM) inference, offering close to ideal speedups up to batchsizes of 16-32 tokens. It is suitable for larger-scale serving, speculative decoding, and advanced multi-inference schemes like CoT-Majority. Marlin achieves optimal performance by utilizing various techniques and optimizations to fully leverage GPU resources, ensuring efficient computation and memory management.

LLM-Merging is a repository containing starter code for the LLM-Merging competition. It provides a platform for efficiently building LLMs through merging methods. Users can develop new merging methods by creating new files in the specified directory and extending existing classes. The repository includes instructions for setting up the environment, developing new merging methods, testing the methods on specific datasets, and submitting solutions for evaluation. It aims to facilitate the development and evaluation of merging methods for LLMs.

Q-Bench is a benchmark for general-purpose foundation models on low-level vision, focusing on multi-modality LLMs performance. It includes three realms for low-level vision: perception, description, and assessment. The benchmark datasets LLVisionQA and LLDescribe are collected for perception and description tasks, with open submission-based evaluation. An abstract evaluation code is provided for assessment using public datasets. The tool can be used with the datasets API for single images and image pairs, allowing for automatic download and usage. Various tasks and evaluations are available for testing MLLMs on low-level vision tasks.

K2 (GeoLLaMA) is a large language model for geoscience, trained on geoscience literature and fine-tuned with knowledge-intensive instruction data. It outperforms baseline models on objective and subjective tasks. The repository provides K2 weights, core data of GeoSignal, GeoBench benchmark, and code for further pretraining and instruction tuning. The model is available on Hugging Face for use. The project aims to create larger and more powerful geoscience language models in the future.

RTL-Coder is a tool designed to outperform GPT-3.5 in RTL code generation by providing a fully open-source dataset and a lightweight solution. It targets Verilog code generation and offers an automated flow to generate a large labeled dataset with over 27,000 diverse Verilog design problems and answers. The tool addresses the data availability challenge in IC design-related tasks and can be used for various applications beyond LLMs. The tool includes four RTL code generation models available on the HuggingFace platform, each with specific features and performance characteristics. Additionally, RTL-Coder introduces a new LLM training scheme based on code quality feedback to further enhance model performance and reduce GPU memory consumption.

TriForce is a training-free tool designed to accelerate long sequence generation. It supports long-context Llama models and offers both on-chip and offloading capabilities. Users can achieve a 2.2x speedup on a single A100 GPU. TriForce also provides options for offloading with tensor parallelism or without it, catering to different hardware configurations. The tool includes a baseline for comparison and is optimized for performance on RTX 4090 GPUs. Users can cite the associated paper if they find TriForce useful for their projects.

Groma is a grounded multimodal assistant that excels in region understanding and visual grounding. It can process user-defined region inputs and generate contextually grounded long-form responses. The tool presents a unique paradigm for multimodal large language models, focusing on visual tokenization for localization. Groma achieves state-of-the-art performance in referring expression comprehension benchmarks. The tool provides pretrained model weights and instructions for data preparation, training, inference, and evaluation. Users can customize training by starting from intermediate checkpoints. Groma is designed to handle tasks related to detection pretraining, alignment pretraining, instruction finetuning, instruction following, and more.

aiosmtpd is an asyncio-based SMTP server implementation that provides a modern and efficient way to handle SMTP and LMTP protocols in Python 3. It replaces the outdated asyncore and asynchat modules with asyncio for improved asynchronous I/O operations. The project aims to offer a more user-friendly, extendable, and maintainable solution for handling email protocols in Python applications. It is actively maintained by experienced Python developers and offers full documentation for easy integration and usage.

The Synthetic-Voice-Detection-Vocoder-Artifacts repository provides the LibriSeVoc dataset containing self-vocoding samples created with six state-of-the-art vocoders to expose and exploit vocoder artifacts. It also introduces a new approach for detecting synthetic human voices by identifying signal artifacts left by neural vocoders and enhancing the RawNet2 baseline. The repository includes a paper and dataset for further reference and offers instructions for training the model and testing it in the wild.

cl-waffe2 is an experimental deep learning framework in Common Lisp, providing fast, systematic, and customizable matrix operations, reverse mode tape-based Automatic Differentiation, and neural network model building and training features accelerated by a JIT Compiler. It offers abstraction layers, extensibility, inlining, graph-level optimization, visualization, debugging, systematic nodes, and symbolic differentiation. Users can easily write extensions and optimize their networks without overheads. The framework is designed to eliminate barriers between users and developers, allowing for easy customization and extension.

IKBT is a Python-based system for generating closed-form solutions to the manipulator inverse kinematics problem using behavior trees for action selection. Solutions are fully symbolic and are output as LaTex, Python, and C++. The tool automates closed-form kinematics solving by organizing solution algorithms in a behavior tree, incorporating frequently used knowledge, generating a dependency graph of joint variables, and providing features for automatic documentation and code generation. It is implemented in Python with minimal dependencies outside of the standard Python distribution.

AirLine is a learnable edge-based line detection algorithm designed for various robotic tasks such as scene recognition, 3D reconstruction, and SLAM. It offers a novel approach to extracting line segments directly from edges, enhancing generalization ability for unseen environments. The algorithm balances efficiency and accuracy through a region-grow algorithm and local edge voting scheme for line parameterization. AirLine demonstrates state-of-the-art precision with significant runtime acceleration compared to other learning-based methods, making it ideal for low-power robots.

Torch-Pruning (TP) is a library for structural pruning that enables pruning for a wide range of deep neural networks. It uses an algorithm called DepGraph to physically remove parameters. The library supports pruning off-the-shelf models from various frameworks and provides benchmarks for reproducing results. It offers high-level pruners, dependency graph for automatic pruning, low-level pruning functions, and supports various importance criteria and modules. Torch-Pruning is compatible with both PyTorch 1.x and 2.x versions.

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Ensures software quality through automated testing strategies.

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児童、生徒、学生のテストの自己採点物を分析し、文化や私生活を考慮した学習のアドバイスを行います。(This program analyzes the self-graded test items of children, students, and students, and advises them on their studies, taking into account their cultural and personal lives.)

Put your prompt engineering skills to the ultimate test! Embark on a journey to outwit a mythical guardian of ancient secrets. Try to extract the secret passphrase hidden in the system prompt and enter it in chat when you think you have it and claim your glory. Good luck!

Quizzes users on advanced machine learning concepts.

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Hint-giving, single-question quiz master on Twain

AI trivia expert, engaging and concise, focusing on AI history since the 1950s.

Get 1-on-1 tutoring. Trained from official questions only (verbal, quant, data insights). Score in the 90th percentile! 🚀

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Ce GPT a pour objectif de me préparer aux partiels de mastère professionnel "Manager du développement commercial". Il me permettra notamment de réviser l'ensemble des cours reçus lors de cette année.

Java testing consultant specializing in Mockito, based on the book Mockito Made Clear and related blog posts by Ken Kousen.