Best AI tools for< Benchmark Kernels >

Junbi.ai is an AI-powered insights platform designed for YouTube advertisers. It offers AI-powered creative insights for YouTube ads, allowing users to benchmark their ads, predict performance, and test quickly and easily with fully AI-powered technology. The platform also includes expoze.io API for attention prediction on images or videos, with scientifically valid results and developer-friendly features for easy integration into software applications.

HelloData is an AI-powered platform designed for multifamily professionals in the real estate industry. It offers automated rent surveys, effective rent calculation, historical rent trends, expense benchmarks, and development feasibility analysis. The platform provides unlimited market surveys with competitor leasing trends, concessions, fees, and amenities, helping users optimize rents and grow net operating income. HelloData saves time by automating market surveys, reducing report times, and providing nationwide access to real-time data. It is a comprehensive toolbox that eliminates manual surveys and offers accurate data for real estate analysis.

ARC Prize is a platform hosting a $1,000,000+ public competition aimed at beating and open-sourcing a solution to the ARC-AGI benchmark. The platform is dedicated to advancing open artificial general intelligence (AGI) for the public benefit. It provides a formal benchmark, ARC-AGI, created by François Chollet, to measure progress towards AGI by testing the ability to efficiently acquire new skills and solve open-ended problems. ARC Prize encourages participants to try solving test puzzles to identify patterns and improve their AGI skills.

Report Card Comments Online is an AI Writing Assistant tool that helps teachers generate high-quality, unique, and personalized report card comments. The tool allows users to create a quality benchmark by writing their first draft of comments with the assistance of an AI assistant. It simplifies the report card writing process by providing features like rephrasing, maximum character count, and easy exporting of comments into a file. Designed by teachers for teachers, Report Card AI aims to streamline the comment writing process, ensuring error-free and eloquently written first drafts.

ASK BOSCO® is an AI reporting and forecasting tool designed for agencies and retailers. It connects and consolidates data for easy reporting, predicts media spend allocation, plans budgets, and forecasts future performance with 96% accuracy. The tool combines internal marketing data with algorithmic modeling to create personalized reporting dashboards, enabling data-driven marketing decisions and insights. ASK BOSCO® is trusted by leading brands and agencies, offering statistical modeling and machine learning for media budget planning and benchmarking against competitors.

Perspect is an AI-powered platform designed for high-performance software teams. It offers real-time insights into team contributions and impact, optimizing developer experience, and rewarding high-performers. With 50+ integrations, Perspect enables visualization of impact, benchmarking performance, and uses machine learning models to identify and eliminate blockers. The platform is deeply integrated with web3 wallets and offers built-in reward mechanisms. Managers can align resources around crucial KPIs, identify top talent, and prevent burnout. Perspect aims to enhance team productivity and employee retention through AI and ML technologies.

Trend Hunter is an AI-powered platform that offers a wide range of services to accelerate innovation and provide insights into trends and opportunities. With a vast database of ideas and innovations, Trend Hunter helps individuals and organizations stay ahead of the curve by offering trend reports, newsletters, training programs, and custom services. The platform also provides personalized assessments to enhance innovation potential and offers resources such as books, keynotes, and online courses to foster creativity and strategic thinking.

The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.

Clarity AI is an AI-powered technology platform that offers a Sustainability Tech Kit for sustainable investing, shopping, reporting, and benchmarking. The platform provides built-in sustainability technology with customizable solutions for various needs related to data, methodologies, and tools. It seamlessly integrates into workflows, offering scalable and flexible end-to-end SaaS tools to address sustainability use cases. Clarity AI leverages powerful AI and machine learning to analyze vast amounts of data points, ensuring reliable and transparent data coverage. The platform is designed to empower users to assess, analyze, and report on sustainability aspects efficiently and confidently.

Unify is an AI tool that offers a unified platform for accessing and comparing various Language Models (LLMs) from different providers. It allows users to combine models for faster, cheaper, and better responses, optimizing for quality, speed, and cost-efficiency. Unify simplifies the complex task of selecting the best LLM by providing transparent benchmarks, personalized routing, and performance optimization tools.

Groq is a fast AI inference tool that offers GroqCloud™ Platform and GroqRack™ Cluster for developers to build and deploy AI models with ultra-low-latency inference. It provides instant intelligence for openly-available models like Llama 3.1 and is known for its speed and compatibility with other AI providers. Groq powers leading openly-available AI models and has gained recognition in the AI chip industry. The tool has received significant funding and valuation, positioning itself as a strong challenger to established players like Nvidia.

Woven Insights is an AI-driven Fashion Retail Market & Consumer Insights solution that empowers fashion businesses with data-driven decision-making capabilities. It provides competitive intelligence, performance monitoring analytics, product assortment optimization, market insights, consumer insights, and pricing strategies to help businesses succeed in the retail market. With features like insights-driven competitive benchmarking, real-time market insights, product performance tracking, in-depth market analytics, and sentiment analysis, Woven Insights offers a comprehensive solution for businesses of all sizes. The application also offers bespoke data analysis, AI insights, natural language query, and easy collaboration tools to enhance decision-making processes. Woven Insights aims to democratize fashion intelligence by providing affordable pricing and accessible insights to help businesses stay ahead of the competition.

The website offers a powerful AI tool for conducting social media opinion research on platforms like TikTok, Snapchat, LinkedIn, and more. It utilizes advanced algorithms to analyze and extract insights from user-generated content, helping businesses and individuals understand public sentiment and trends across various social media channels.

SaaSlidator is an AI-powered application designed to help users validate their project ideas efficiently and effectively. By providing a project name and description, SaaSlidator offers valuable insights to support decision-making on whether to proceed with building and launching a minimum viable product (MVP). The platform leverages AI algorithms to analyze data, offer market demand insights, competition analysis, and assess the feasibility of project ideas. With features like rapid validation, monetization suggestions, and benchmarking data, SaaSlidator aims to streamline the idea validation process and empower users to make informed decisions for successful project development.

Seek AI is a generative AI-powered database query tool that helps businesses break through information barriers. It is the #1 most accurate model on the Yale Spider benchmark and offers a variety of features to help businesses modernize their analytics, including auto-verification with confidence estimation, natural language summary, and embedded AI data analyst.

Studious Score AI is an AI-powered platform that offers knowledge and skill evaluation services supported by reputable individuals and organizations. The platform aims to revolutionize credentialing by providing a new approach. Studious Score AI is on a mission to establish itself as the global benchmark for assessing skills and knowledge in various aspects of life. Users can explore different categories and unlock their potential through the platform's innovative evaluation methods.

Weavel is an AI tool designed to revolutionize prompt engineering for large language models (LLMs). It offers features such as tracing, dataset curation, batch testing, and evaluations to enhance the performance of LLM applications. Weavel enables users to continuously optimize prompts using real-world data, prevent performance regression with CI/CD integration, and engage in human-in-the-loop interactions for scoring and feedback. Ape, the AI prompt engineer, outperforms competitors on benchmark tests and ensures seamless integration and continuous improvement specific to each user's use case. With Weavel, users can effortlessly evaluate LLM applications without the need for pre-existing datasets, streamlining the assessment process and enhancing overall performance.

Notle is an advanced AI-driven psychometric recording tool designed for mental health professionals. It revolutionizes how patient interactions in psychotherapy sessions are captured and analyzed. The platform provides cutting-edge analysis, effortless tracking, in-depth metrics, and empowers clinicians with intelligent analytics for personalized care. Notle sets a new benchmark for psychometric evaluation tools, ensuring unrivaled precision in psychometric assessment. It offers advanced behavioral insights, user-friendly interface, unmatched precision & reliability, and non-invasive integration into healthcare practices. The application is reliable, accurate, impactful, and validated through research methods.

Reflection 70B is a next-gen open-source LLM powered by Llama 70B, offering groundbreaking self-correction capabilities that outsmart GPT-4. It provides advanced AI-powered conversations, assists with various tasks, and excels in accuracy and reliability. Users can engage in human-like conversations, receive assistance in research, coding, creative writing, and problem-solving, all while benefiting from its innovative self-correction mechanism. Reflection 70B sets new standards in AI performance and is designed to enhance productivity and decision-making across multiple domains.

AskCory is an AI-powered marketing assistant designed to save time by generating strategic tactics, action plans, and content assets. It effortlessly integrates actionable insights and benchmarks, offering personalized marketing strategies for businesses in just minutes. The platform helps users craft and execute marketing plans 5x faster, saving up to 80% of their time. With AskCory, users can say goodbye to blank page syndrome and generic suggestions, and instead, receive proven tactics based on industry benchmarks. The tool streamlines the task of preparing action plans, allowing users to focus on decision-making and project leadership. AskCory also provides benefits such as improved ROI, streamlined workflows, and data-driven decision-making for busy professionals.

Atom is an accurate low-bit weight-activation quantization algorithm that combines mixed-precision, fine-grained group quantization, dynamic activation quantization, KV-cache quantization, and efficient CUDA kernels co-design. It introduces a low-bit quantization method, Atom, to maximize Large Language Models (LLMs) serving throughput with negligible accuracy loss. The codebase includes evaluation of perplexity and zero-shot accuracy, kernel benchmarking, and end-to-end evaluation. Atom significantly boosts serving throughput by using low-bit operators and reduces memory consumption via low-bit quantization.

ABQ-LLM is a novel arbitrary bit quantization scheme that achieves excellent performance under various quantization settings while enabling efficient arbitrary bit computation at the inference level. The algorithm supports precise weight-only quantization and weight-activation quantization. It provides pre-trained model weights and a set of out-of-the-box quantization operators for arbitrary bit model inference in modern architectures.

Liger Kernel is a collection of Triton kernels designed for LLM training, increasing training throughput by 20% and reducing memory usage by 60%. It includes Hugging Face Compatible modules like RMSNorm, RoPE, SwiGLU, CrossEntropy, and FusedLinearCrossEntropy. The tool works with Flash Attention, PyTorch FSDP, and Microsoft DeepSpeed, aiming to enhance model efficiency and performance for researchers, ML practitioners, and curious novices.

FlashInfer is a library for Language Languages Models that provides high-performance implementation of LLM GPU kernels such as FlashAttention, PageAttention and LoRA. FlashInfer focus on LLM serving and inference, and delivers state-the-art performance across diverse scenarios.

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by the MMRazor and MMDeploy teams. It has the following core features: * **Efficient Inference** : LMDeploy delivers up to 1.8x higher request throughput than vLLM, by introducing key features like persistent batch(a.k.a. continuous batching), blocked KV cache, dynamic split&fuse, tensor parallelism, high-performance CUDA kernels and so on. * **Effective Quantization** : LMDeploy supports weight-only and k/v quantization, and the 4-bit inference performance is 2.4x higher than FP16. The quantization quality has been confirmed via OpenCompass evaluation. * **Effortless Distribution Server** : Leveraging the request distribution service, LMDeploy facilitates an easy and efficient deployment of multi-model services across multiple machines and cards. * **Interactive Inference Mode** : By caching the k/v of attention during multi-round dialogue processes, the engine remembers dialogue history, thus avoiding repetitive processing of historical sessions.

QServe is a serving system designed for efficient and accurate Large Language Models (LLM) on GPUs with W4A8KV4 quantization. It achieves higher throughput compared to leading industry solutions, allowing users to achieve A100-level throughput on cheaper L40S GPUs. The system introduces the QoQ quantization algorithm with 4-bit weight, 8-bit activation, and 4-bit KV cache, addressing runtime overhead challenges. QServe improves serving throughput for various LLM models by implementing compute-aware weight reordering, register-level parallelism, and fused attention memory-bound techniques.

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.

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This repository contains a collection of tools that can be used with vastai. The tools are free to use, modify and distribute. If you find this useful and wish to donate your welcome to send your donations to the following wallets. BTC 15qkQSYXP2BvpqJkbj2qsNFb6nd7FyVcou XMR 897VkA8sG6gh7yvrKrtvWningikPteojfSgGff3JAUs3cu7jxPDjhiAZRdcQSYPE2VGFVHAdirHqRZEpZsWyPiNK6XPQKAg RVN RSgWs9Co8nQeyPqQAAqHkHhc5ykXyoMDUp USDT(ETH ERC20) 0xa5955cf9fe7af53bcaa1d2404e2b17a1f28aac4f Paypal PayPal.Me/cryptolabsZA

vLLM is a fast and easy-to-use library for LLM inference and serving. It is designed to be efficient, flexible, and easy to use. vLLM can be used to serve a variety of LLM models, including Hugging Face models. It supports a variety of decoding algorithms, including parallel sampling, beam search, and more. vLLM also supports tensor parallelism for distributed inference and streaming outputs. It is open-source and available on GitHub.

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system. The core features of SGLang include: - **A Flexible Front-End Language**: This allows for easy programming of LLM applications with multiple chained generation calls, advanced prompting techniques, control flow, multiple modalities, parallelism, and external interaction. - **A High-Performance Runtime with RadixAttention**: This feature significantly accelerates the execution of complex LLM programs by automatic KV cache reuse across multiple calls. It also supports other common techniques like continuous batching and tensor parallelism.

HQQ is a fast and accurate model quantizer that skips the need for calibration data. It's super simple to implement (just a few lines of code for the optimizer). It can crunch through quantizing the Llama2-70B model in only 4 minutes! 🚀

This repository provides a comprehensive list of academic papers, articles, tutorials, slides, and projects related to Large Language Model (LLM) systems. It covers various aspects of LLM research, including pre-training, serving, system efficiency optimization, multi-model systems, image generation systems, LLM applications in systems, ML systems, survey papers, LLM benchmarks and leaderboards, and other relevant resources. The repository is regularly updated to include the latest developments in this rapidly evolving field, making it a valuable resource for researchers, practitioners, and anyone interested in staying abreast of the advancements in LLM technology.

Basalt is a lightweight and flexible CSS framework designed to help developers quickly build responsive and modern websites. It provides a set of pre-designed components and utilities that can be easily customized to create unique and visually appealing web interfaces. With Basalt, developers can save time and effort by leveraging its modular structure and responsive design principles to create professional-looking websites with ease.

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.

Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes.

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Benchmark HVAC GPT model with unmatched expertise and forward-thinking solutions, powered by OpenAI

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ESG performance assessment and reporting guide.

Compensation Advisor for HR and managers (v0.4)

Quizzes users on advanced machine learning concepts.

Guides businesses in managing global tax liabilities efficiently.

Free to use oracle for analyzing Net Promoter Score data.

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Ensures software performance meets organizational standards and expectations.