Best AI tools for< Support Different Quantization Methods >

Aceify.ai is an AI tool designed to provide instant and accurate study help to students. It offers features such as a screenshot tool, a summarizer tool, and a variety of resources to assist users in finding solutions to academic problems. The tool aims to enhance productivity and learning efficiency by offering support across different types of questions and platforms. Aceify.ai is committed to high accuracy and continuous improvement to meet the needs of students and individuals seeking academic assistance.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Support AI is a custom AI chatbot application powered by ChatGPT that allows website owners to create personalized chatbots to provide instant answers to customers, capture leads, and enhance customer support. With Support AI, users can easily integrate AI chatbots on their websites, train them with specific content, and customize their behavior and responses. The application offers features such as capturing leads, providing accurate answers, handling bookings, collecting feedback, and offering product recommendations. Users can choose from different pricing plans based on their message volume and training content needs.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Context is an AI-powered chat tool designed to transform your product documentation into an automated 24/7 tech support bot. It allows you to import content from various sources, install bots on different platforms, and provide round-the-clock automated tech support. With features like GPT-4 enabled responses, multi-source data import, teammate collaboration, and response ranking, Context aims to streamline customer support processes and enhance user experience.

Converso is an AI-powered customer support platform that enables businesses to connect their own AI Assistant with a shared team inbox, thereby automating first-line customer support and reducing workload for front-line agents. AI Assistants can be connected to different channels, such as webchat, WhatsApp, SMS, and conversations can be transferred to a human agent in the event that the query is too complex for the AI Assistant to manage. Converso also enables outbound conversations via WhatsApp and SMS, managed via the same inbox, for proactive customer engagement.

AskMyDocs.ai is an AI tool designed to save time and money on customer and employee support by allowing users to ask questions and get precise, instant answers straight from their documentation sources. The tool offers various integrations with platforms like Zendesk, Gitbook, Sitemap, PDF, and Slack, enabling users to transform their knowledge base into an intelligent resource. AskMyDocs.ai provides features such as resource savings calculator, integrations with multiple platforms, and a chatbot for quick and precise responses. The tool offers different pricing plans catering to different business sizes and needs, with options for custom features and support SLAs.

DentroChat is an AI chat application that reimagines the way users interact with AI models. It allows users to select from various large language models (LLMs) in different modes, enabling them to choose the best AI for their specific tasks. With seamless mode switching and optimized performance, DentroChat offers flexibility and precision in AI interactions.

Atochat is an AI chatbot marketing tool that helps businesses level up their lead generation, sales, and customer support through automation. It offers a Visual Drag & Drop Flow Builder for creating dynamic chatbots without coding. With features like impactful broadcasting, real-time customer support, sequence messaging, user input flow, and webhook workflow, Atochat revolutionizes business workflows. It also provides an E-commerce platform, form builder for scheduling appointments, and WooCommerce automation. The tool enables efficient chat management with a shared team inbox and offers various pricing plans to cater to different business needs.

Woord is an online text-to-speech (TTS) tool that allows users to convert text into natural-sounding speech. It offers a wide range of voices in over 34 languages, including regional variations. Woord also provides advanced features such as SSML editing, OCR support, and API access. With its user-friendly interface and affordable pricing, Woord is a great choice for individuals and businesses looking to add speech capabilities to their applications.

DevRev is an AI-native modern support platform that offers a comprehensive solution for customer experience enhancement. It provides data engineering, knowledge graph, and customizable LLMs to streamline support, product management, and software development processes. With features like in-browser analytics, consumer-grade social collaboration, and global scale API calls, DevRev aims to bring together different silos within a company to drive efficiency and collaboration. The platform caters to support people, product managers, and developers, automating tasks, assisting in decision-making, and elevating collaboration levels. DevRev is designed to empower digital product teams to assimilate customer feedback in real-time, ultimately powering the next generation of technology companies.

Twig AI is an AI tool designed for Customer Experience, offering an AI assistant that resolves customer issues instantly, supporting both users and support agents 24/7. It provides features like converting user requests into API calls, instant responses for user questions, and factual answers cited with trustworthy sources. Twig simplifies data retrieval from external sources, offers personalization options, and includes a built-in knowledge base. The tool aims to drive agent productivity, provide insights to monitor customer experience, and offers various application interfaces for different user roles.

helpmee.ai is an AI-guided computer help platform designed to empower seniors and individuals with tech challenges through patient, voice-enabled conversations, screen sharing, and cutting-edge AI vision technology. The platform offers personalized assistance in 50+ languages, 24/7, using OpenAI's latest GPT-4o model to ensure users can navigate the digital world with confidence and independence. With subscription plans tailored to different needs, helpmee.ai aims to provide digital autonomy and minimize family tech support frustrations.

TarsyAI is an AI tool that allows users to build AI assistants without the need for coding. Users can create customized AI assistants to manage customer support, lead generation, sales, and more. The platform offers features such as training with own data, customizing chat widgets, deploying AI assistants, monitoring and improving performance. TarsyAI supports multiple languages, provides advanced AI instructions, lead generation capabilities, and detailed analytics to enhance user interactions. The tool offers various pricing options to cater to different user needs, with a free trial available for all plans.

Neural Canvas is an AI comic generator that allows users to create perfect comics using artificial intelligence. The platform offers over 100 different styles and characters to transform stories into visually appealing comics. Users can choose from various moods, styles, and characters to customize their comic creations. Neural Canvas has generated over 9,000 comics globally and provides a unique and creative way to bring stories to life through AI technology.

Superseek is a custom ChatGPT AI tool designed to help businesses enhance customer service by creating custom AI assistants that can resolve customer queries instantly. It offers multilingual answers in over 95 languages, powered by the user's content to ensure accuracy. Superseek allows users to customize their AI agents without any coding knowledge, capture leads with timely forms, and seamlessly handoff complex queries to human teams. It provides different pricing plans with varying features and advantages to suit different business needs.

Guidejar is an AI-powered tool that allows users to create interactive product demos and step-by-step guides effortlessly. It simplifies complex processes by providing easy-to-follow guides with AI superpowers. Trusted by teams worldwide, Guidejar helps transform any process into an interactive demo or guide. Users can customize their guides, share them easily, and enhance them with AI magic, voiceovers, and translations. With features like browser extension, branding, step management, guide views, and call-to-action, Guidejar boosts user activation and conversion rates. It offers different pricing plans to cater to various user needs, from free basic features to premium plans with extensive customization and analytics.

Nara is an AI-powered digital sales associate that helps online stores increase sales and provide 24/7 support across all chat channels. It automates customer engagement by answering support questions, providing tailored shopping advice, and simplifying customer checkout. Nara offers different pricing plans to suit varying needs and provides a human touch experience similar to interacting with a helpful sales associate in physical stores.

Rythmex Converter is an AI-powered audio-to-text converter tool that allows users to easily, quickly, and effectively transcribe audio files into text. With support for over 140 languages, Rythmex offers a seamless transcription experience for various industries such as business, education, journalism, law, and more. Users can upload their audio or video files, choose the language, and receive accurate transcriptions within minutes. The tool is designed to save time and effort by providing automated transcription services using machine learning technology.

Gan.AI is an AI-powered platform that revolutionizes video and audio communication by offering personalized video creation, avatar generation, dubbing, and conversational avatars. It provides APIs for video personalization, text-to-speech, voice cloning, and lip-sync technologies. The platform supports multiple languages, including 22 Indic languages, English, Spanish, and Portuguese. Gan.AI prioritizes privacy and data security, being SOC2 and ISO compliant, ensuring user data is safeguarded.

A web-based calculator to estimate hardware requirements for running Large Language Models (LLMs) in inference mode. This tool helps determine VRAM and system RAM needed for different LLM configurations. It calculates VRAM requirements based on model size, quantization method, context length, and KV cache settings. It provides estimates for required VRAM, minimum system RAM, on-disk model size, and number of GPUs needed. The project uses React, TypeScript, and Vite. Docker support is available with instructions provided. The tool provides approximations for calculations, includes overhead for KV cache, and assumes certain percentages for unified memory and discrete GPU calculations.

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.

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! 🚀

Qwen-TensorRT-LLM is a project developed for the NVIDIA TensorRT Hackathon 2023, focusing on accelerating inference for the Qwen-7B-Chat model using TRT-LLM. The project offers various functionalities such as FP16/BF16 support, INT8 and INT4 quantization options, Tensor Parallel for multi-GPU parallelism, web demo setup with gradio, Triton API deployment for maximum throughput/concurrency, fastapi integration for openai requests, CLI interaction, and langchain support. It supports models like qwen2, qwen, and qwen-vl for both base and chat models. The project also provides tutorials on Bilibili and blogs for adapting Qwen models in NVIDIA TensorRT-LLM, along with hardware requirements and quick start guides for different model types and quantization methods.

This repository provides a demonstration of running a native Large Language Model (LLM) on Android devices. It supports various models such as Qwen2.5-Instruct, MiniCPM-DPO/SFT, Yuan2.0, Gemma2-it, StableLM2-Chat/Zephyr, and Phi3.5-mini-instruct. The demo models are optimized for extreme execution speed after being converted from HuggingFace or ModelScope. Users can download the demo models from the provided drive link, place them in the assets folder, and follow specific instructions for decompression and model export. The repository also includes information on quantization methods and performance benchmarks for different models on various devices.

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.

AQLM is the official PyTorch implementation for Extreme Compression of Large Language Models via Additive Quantization. It includes prequantized AQLM models without PV-Tuning and PV-Tuned models for LLaMA, Mistral, and Mixtral families. The repository provides inference examples, model details, and quantization setups. Users can run prequantized models using Google Colab examples, work with different model families, and install the necessary inference library. The repository also offers detailed instructions for quantization, fine-tuning, and model evaluation. AQLM quantization involves calibrating models for compression, and users can improve model accuracy through finetuning. Additionally, the repository includes information on preparing models for inference and contributing guidelines.

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.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

The stable-diffusion.cpp repository provides an implementation for inferring stable diffusion in pure C/C++. It offers features such as support for different versions of stable diffusion, lightweight and dependency-free implementation, various quantization support, memory-efficient CPU inference, GPU acceleration, and more. Users can download the built executable program or build it manually. The repository also includes instructions for downloading weights, building from scratch, using different acceleration methods, running the tool, converting weights, and utilizing various features like Flash Attention, ESRGAN upscaling, PhotoMaker support, and more. Additionally, it mentions future TODOs and provides information on memory requirements, bindings, UIs, contributors, and references.

This repository implements multiple key-value cache pruning methods and benchmarks using transformers, aiming to simplify the development of new methods for researchers and developers in the field of long-context language models. It provides a set of 'presses' that compress the cache during the pre-filling phase, with each press having a compression ratio attribute. The repository includes various training-free presses, special presses, and supports KV cache quantization. Users can contribute new presses and evaluate the performance of different presses on long-context datasets.

ms-swift is an official framework provided by the ModelScope community for fine-tuning and deploying large language models and multi-modal large models. It supports training, inference, evaluation, quantization, and deployment of over 400 large models and 100+ multi-modal large models. The framework includes various training technologies and accelerates inference, evaluation, and deployment modules. It offers a Gradio-based Web-UI interface and best practices for easy application of large models. ms-swift supports a wide range of model types, dataset types, hardware support, lightweight training methods, distributed training techniques, quantization training, RLHF training, multi-modal training, interface training, plugin and extension support, inference acceleration engines, model evaluation, and model quantization.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

AutoRound is an advanced weight-only quantization algorithm for low-bits LLM inference. It competes impressively against recent methods without introducing any additional inference overhead. The method adopts sign gradient descent to fine-tune rounding values and minmax values of weights in just 200 steps, often significantly outperforming SignRound with the cost of more tuning time for quantization. AutoRound is tailored for a wide range of models and consistently delivers noticeable improvements.

BitBLAS is a library for mixed-precision BLAS operations on GPUs, for example, the $W_{wdtype}A_{adtype}$ mixed-precision matrix multiplication where $C_{cdtype}[M, N] = A_{adtype}[M, K] \times W_{wdtype}[N, K]$. BitBLAS aims to support efficient mixed-precision DNN model deployment, especially the $W_{wdtype}A_{adtype}$ quantization in large language models (LLMs), for example, the $W_{UINT4}A_{FP16}$ in GPTQ, the $W_{INT2}A_{FP16}$ in BitDistiller, the $W_{INT2}A_{INT8}$ in BitNet-b1.58. BitBLAS is based on techniques from our accepted submission at OSDI'24.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

Mistral.rs is a fast LLM inference platform written in Rust. We support inference on a variety of devices, quantization, and easy-to-use application with an Open-AI API compatible HTTP server and Python bindings.

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