Best AI tools for< Improve Inference Speed >

d-Matrix is an AI tool that offers ultra-low latency batched inference for generative AI technology. It introduces Corsair™, the world's most efficient AI inference platform for datacenters, providing high performance, efficiency, and scalability for large-scale inference tasks. The tool aims to transform the economics of AI inference by delivering fast, sustainable, and scalable AI solutions without compromising on speed or usability.

Lamini is an enterprise-level LLM platform that offers precise recall with Memory Tuning, enabling teams to achieve over 95% accuracy even with large amounts of specific data. It guarantees JSON output and delivers massive throughput for inference. Lamini is designed to be deployed anywhere, including air-gapped environments, and supports training and inference on Nvidia or AMD GPUs. The platform is known for its factual LLMs and reengineered decoder that ensures 100% schema accuracy in the JSON output.

Thirdai.com is an AI tool that offers a robot challenge screen for checking site connection security. The tool helps users assess the security of their website by requiring cookies to be enabled in the browser settings. It ensures that the connection is secure and provides recommendations for improving security measures.

Inworld is an AI framework designed for games and media, offering a production-ready framework for building AI agents with client-side logic and local model inference. It provides tools optimized for real-time data ingestion, low latency, and massive scale, enabling developers to create engaging and immersive experiences for users. Inworld allows for building custom AI agent pipelines, refining agent behavior and performance, and seamlessly transitioning from prototyping to production. With support for C++, Python, and game engines, Inworld aims to future-proof AI development by integrating 3rd-party components and foundational models to avoid vendor lock-in.

poolside is an advanced foundational AI model designed specifically for software engineering challenges. It allows users to fine-tune the model on their own code, enabling it to understand project uniqueness and complexities that generic models can't grasp. The platform aims to empower teams to build better, faster, and happier by providing a personalized AI model that continuously improves. In addition to the AI model for writing code, poolside offers an intuitive editor assistant and an API for developers to leverage.

The pplx-api is an AI tool designed to provide documentation and examples for blazingly fast LLM inference. It offers a reference for developers to integrate AI capabilities into their applications efficiently. The tool focuses on enhancing natural language processing tasks by leveraging advanced models and algorithms. Users can access detailed guides, API references, changelogs, and engage in discussions related to AI technologies.

Segwise is an AI tool designed to help game developers increase their game's Lifetime Value (LTV) by providing insights into player behavior and metrics. The tool uses AI agents to detect causal LTV drivers, root causes of LTV drops, and opportunities for growth. Segwise offers features such as running causal inference models on player data, hyper-segmenting player data, and providing instant answers to questions about LTV metrics. It also promises seamless integrations with gaming data sources and warehouses, ensuring data ownership and transparent pricing. The tool aims to simplify the process of improving LTV for game developers.

BuildAi is an AI tool designed to provide the lowest cost GPU cloud for AI training on the market. The platform is powered with renewable energy, enabling companies to train AI models at a significantly reduced cost. BuildAi offers interruptible pricing, short term reserved capacity, and high uptime pricing options. The application focuses on optimizing infrastructure for training and fine-tuning machine learning models, not inference, and aims to decrease the impact of computing on the planet. With features like data transfer support, SSH access, and monitoring tools, BuildAi offers a comprehensive solution for ML teams.

Anote is a human-centered AI company that provides a suite of products and services to help businesses improve their data quality and build better AI models. Anote's products include a data labeler, a private chatbot, a model inference API, and a lead generation tool. Anote's services include data annotation, model training, and consulting.

TechTarget is a leading provider of purchase intent data and marketing services for the technology industry. Our data-driven solutions enable technology companies to identify and engage with their target audiences, and to measure the impact of their marketing campaigns. We offer a range of products and services, including:

MakerJournal is a powerful AI tool designed to help users improve social engagement and increase audience by automatically generating summaries of log entries. It allows users to manage multiple projects, generate updates from GitHub commits, and post to social media accounts effortlessly. MakerJournal simplifies the process of deciding what to post, enabling users to focus on creating great products while enhancing their social rankings. With easy-to-use features and automatic summaries, MakerJournal streamlines the process of logging progress and increasing social influence.

Bodify is a predictive analytics platform that helps online retailers improve the shopping experience for their customers. By using AI to analyze customer data, Bodify can provide retailers with insights into what products customers are most likely to purchase, what sizes and styles they prefer, and what factors influence their decisions. This information can then be used to create more personalized and relevant shopping experiences, which can lead to higher conversion rates, increased customer loyalty, and improved bottom-line results.

BladeRunner is a browser plug-in that highlights AI-generated text directly on web pages. It helps users detect AI-generated content in various contexts such as social media, news, education, e-commerce, and government communications. The tool aims to assist individuals in distinguishing between human-generated and AI-generated text, especially in the age of advanced language models and increasing AI influence on digital content.

Cast.app is an AI-driven platform that automates customer success management, enabling businesses to grow and preserve revenue by leveraging AI agents. The application offers a range of features such as automating customer onboarding, driving usage and adoption, minimizing revenue churn, influencing renewals and revenue expansion, and scaling without increasing team size. Cast.app provides personalized recommendations, insights, and customer communications, enhancing customer engagement and satisfaction. The platform is designed to streamline customer interactions, improve retention rates, and drive revenue growth through AI-powered automation and personalized customer experiences.

QOVES is a website that provides tools and advice to help people improve their looks. The website offers a variety of services, including facial analysis, hairline design, style advice, and Photoshop retouching. QOVES also has a blog with articles on a variety of topics related to beauty and aesthetics.

FCK.School is an online platform that provides AI-powered writing tools to help students with various aspects of their academic work, including creating outlines, generating essay conclusions, crafting thesis statements, and much more. It offers a range of tools such as paraphrasing, text generation, summarizing, grammar and punctuation correction, title generation, thesis statement generation, outline generation, intro generation, paragraph generation, and conclusion generation. FCK.School aims to improve writing skills, save time and effort, and enhance the quality of written content.

Cyberday.ai is an AI-powered platform designed to help organizations improve and certify their cybersecurity. The platform offers a comprehensive set of tools and resources to guide users in implementing security tasks, creating policies, and generating compliance reports. With a focus on automation and efficiency, Cyberday.ai streamlines the process of managing information security, from risk assessment to employee training. By leveraging AI technology, Cyberday.ai aims to simplify the complex task of cybersecurity management for organizations of all sizes.

Neurala is a company that provides visual quality inspection software powered by AI. Their software is designed to help manufacturers improve their inspection process by reducing product defects, increasing inspection rates, and preventing production downtime. Neurala's software is flexible and can be easily retrofitted into existing production line infrastructure, without the need for AI experts or expensive capital expenditures. The company's software is used by a variety of manufacturers, including Sony, AITRIOS, and CB Insights.

Zevi is an AI-powered site search and discovery platform that helps businesses improve their website search and chat experience. It offers a range of features including neural search, chat assistant, merchandising, and analytics. Zevi's AI-driven technology helps businesses understand their customers' queries and provide them with the most relevant results. It also helps businesses create a more personalized and conversational shopping experience for their customers.

Helper Systems has developed technology that restores the trust between students who want to use AI tools for research and faculty who need to ensure academic integrity. With kOS (pronounced chaos), students can easily provide proof of work using a platform that significantly simplifies and enhances the research process in ways never before possible. Add PDF files from your desktop, shared drives or the web. Annotate them if you desire. Use AI responsibly, knowing when information is generated from your research vs. the web. Instantly create a presentation of all your resources. Share and prove your work. Try other cool features that offer a unique way to find, organize, discover, archive, and present information.

AWQ (Activation-aware Weight Quantization) is a tool designed for efficient and accurate low-bit weight quantization (INT3/4) for Large Language Models (LLMs). It supports instruction-tuned models and multi-modal LMs, providing features such as AWQ search for accurate quantization, pre-computed AWQ model zoo for various LLMs, memory-efficient 4-bit linear in PyTorch, and efficient CUDA kernel implementation for fast inference. The tool enables users to run large models on resource-constrained edge platforms, delivering more efficient responses with LLM/VLM chatbots through 4-bit inference.

CogVideo is an open-source repository that provides pretrained text-to-video models for generating videos based on input text. It includes models like CogVideoX-2B and CogVideo, offering powerful video generation capabilities. The repository offers tools for inference, fine-tuning, and model conversion, along with demos showcasing the model's capabilities through CLI, web UI, and online experiences. CogVideo aims to facilitate the creation of high-quality videos from textual descriptions, catering to a wide range of applications.

InfLLM is a training-free memory-based method that unveils the intrinsic ability of LLMs to process streaming long sequences. It stores distant contexts into additional memory units and employs an efficient mechanism to lookup token-relevant units for attention computation. Thereby, InfLLM allows LLMs to efficiently process long sequences while maintaining the ability to capture long-distance dependencies. Without any training, InfLLM enables LLMs pre-trained on sequences of a few thousand tokens to achieve superior performance than competitive baselines continually training these LLMs on long sequences. Even when the sequence length is scaled to 1, 024K, InfLLM still effectively captures long-distance dependencies.

Cerebrium's official examples repository provides practical, ready-to-use examples for building Machine Learning / AI applications on the platform. The repository contains self-contained projects demonstrating specific use cases with detailed instructions on deployment. Examples cover a wide range of categories such as getting started, advanced concepts, endpoints, integrations, large language models, voice, image & video, migrations, application demos, batching, and Python apps.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

A curated list of high-quality papers on resource-efficient Large Language Models (LLMs) with a focus on various aspects such as architecture design, pre-training, fine-tuning, inference, system design, and evaluation metrics. The repository covers topics like efficient transformer architectures, non-transformer architectures, memory efficiency, data efficiency, model compression, dynamic acceleration, deployment optimization, support infrastructure, and other related systems. It also provides detailed information on computation metrics, memory metrics, energy metrics, financial cost metrics, network communication metrics, and other metrics relevant to resource-efficient LLMs. The repository includes benchmarks for evaluating the efficiency of NLP models and references for further reading.

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.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

llama-zip is a command-line utility for lossless text compression and decompression. It leverages a user-provided large language model (LLM) as the probabilistic model for an arithmetic coder, achieving high compression ratios for structured or natural language text. The tool is not limited by the LLM's maximum context length and can handle arbitrarily long input text. However, the speed of compression and decompression is limited by the LLM's inference speed.

TPI-LLM (Tensor Parallelism Inference for Large Language Models) is a system designed to bring LLM functions to low-resource edge devices, addressing privacy concerns by enabling LLM inference on edge devices with limited resources. It leverages multiple edge devices for inference through tensor parallelism and a sliding window memory scheduler to minimize memory usage. TPI-LLM demonstrates significant improvements in TTFT and token latency compared to other models, and plans to support infinitely large models with low token latency in the future.

GPTQModel is an easy-to-use LLM quantization and inference toolkit based on the GPTQ algorithm. It provides support for weight-only quantization and offers features such as dynamic per layer/module flexible quantization, sharding support, and auto-heal quantization errors. The toolkit aims to ensure inference compatibility with HF Transformers, vLLM, and SGLang. It offers various model supports, faster quant inference, better quality quants, and security features like hash check of model weights. GPTQModel also focuses on faster quantization, improved quant quality as measured by PPL, and backports bug fixes from AutoGPTQ.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

Demystifying Experimentation and Causal Inference with 1-Sided Tests Focus

CUDA and Triton expert with concise, accurate answers.

コードを分析し、言語ではなくスタイルに焦点を当て、プログラムを書いた人の性格を推察するツールです。( It is a tool that analyzes code, focuses on style rather than language, and infers the personality of the person who wrote the program. )

Expert in NLP, persuasion, and body language, teaching through lessons and practical tests.

Explaining behavioral economics in ways that help you!

Strategic advisor on power dynamics, inspired by 'The 48 Laws of Power'

Gives you tips and suggestions on how you can improve your application for your users.

Upload a screenshot of your Tinder profile to improve it and get feedback

Improve your Ideas with First Principles Thinking

Offers exercises and techniques to improve memory retention and cognitive functions.

Generates conversation examples and chunks for specified situations. Improve your instantaneous conversational skills through repetitive practice!

Improve your physical & mental health

Analyzes customer churn and provides strategies to improve loyalty and retention.

Improve your curriculum telling chatgpt your cv and the desired job

Agile expert providing practical, step-by-step advice with the agile way of working of your team and organisation. Whether you're looking to improve your Agile skills or find solutions to specific problems. Including Scrum, Kanban and SAFe knowledge.

I improve objects with animals.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Helps improve language skills through interactive scenarios and feedback.

I improve Dutch sentences, explain errors, and give tips.

Bypass Internet censorship & improve your security online