Best AI tools for< Parallel Training Techniques >

Nooks is an AI-powered parallel dialer and virtual salesfloor platform designed to automate manual call tasks, boost volume, connect rates, and conversion rates. It offers features like call analytics, AI training, and Nooks Numbers to improve data coverage and quality. The platform enables users to coach and collaborate on live calls, transcribe and analyze calls, and work on talk tracks with tough personas using AI training. Nooks also provides resources like a blog, customer stories, and events to help users supercharge their sales pipeline.

Koncert is an AI-powered sales dialer and remote salesfloor platform that helps businesses accelerate sales success. With its AI-enhanced dialing, automated local presence, and caller ID health heat map, Koncert helps sales teams connect with more prospects, have more conversations, and close more deals. Koncert also offers a range of other features, including a multi-channel sales sequencer, remote coaching, and conversation intelligence. With Koncert, sales teams can improve their productivity, increase their connect rates, and close more deals.

BuildShip is a batch processing tool for ChatGPT that allows users to process ChatGPT tasks in parallel on a spreadsheet UI with CSV/JSON import and export. It supports various OpenAI models, including GPT4, Claude 3, and Gemini. Users can start with readymade templates and customize them with their own logic and models. The data generated is stored securely on the user's own Google Cloud project, and team collaboration is supported with granular access control.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

GPT Prompt Tuner is an AI tool designed to enhance ChatGPT prompts by generating variations and running conversations in parallel. It simplifies 'Prompt Engineering,' an emerging field that can lead to high earnings. Users can customize prompts, receive AI-generated variations, and engage in multiple ChatGPT conversations simultaneously. The tool offers flexible subscription plans and requires an OpenAI API Key for usage.

Zappx is a powerful power dialer application designed for sales professionals to enhance their cold calling outreach. With Zappx, users can double their daily connection rate by implementing parallel calling, dial up to 5 prospects simultaneously, filter out wrong numbers, automate voice mails, and connect calls to live prospects. The application also offers AI-enhanced features such as automated call transcription, sentiment analysis, and real-time analytics for performance evaluation. Zappx is built by sales people for sales people, aiming to transform outbound sales approaches with lightning-fast dialing capabilities.

Otto is an AI-powered tool designed to streamline work processes by bringing reasoning to data. It allows users to define tables once and automate numerous tasks in minutes. With features like research capabilities, outbound message creation, and customizable columns, Otto enables users to work 10x faster by leveraging AI agents for parallel processing. The tool unlocks insights from various data sources, including websites, documents, and images, and offers an AI Assistant for contextual assistance. Otto aims to enhance productivity and efficiency by providing advanced data analysis and processing functionalities.

FlashIntel is a revenue acceleration platform that offers a suite of tools and solutions to streamline sales and partnership processes. It provides features like real-time enrichment, personalized messaging, sequence and cadence, email deliverability, parallel dialing, account-based marketing, and more. The platform aims to help businesses uncover ideal prospects, target key insights, craft compelling outreach sequences, research companies and people's contacts in real-time, and execute omnichannel sequences with AI personalization.

Cykel AI is an AI co-pilot designed to assist users in automating various digital tasks. It interacts with any website to complete complex tasks based on user instructions, allowing users to offload 50% of their to-do list to AI. From sending emails to updating spreadsheets, Cykel offers a seamless way to streamline digital workflows and boost productivity. With features like autonomous learning, scalable parallel tasking, and the ability to create and share shortcuts, Cykel aims to revolutionize task automation for individuals and teams across different industries.

Automata is a content repurposing tool that uses AI to help you turn your videos, blogs, and other content into a variety of other formats, such as social media posts, email newsletters, and more. It offers a variety of features to make content repurposing easy and efficient, including platform-specific writing styles, 15+ content output types, content repurposing templates, and parallel content creation. Automata also has an AI Chrome extension for LinkedIn that can help you repurpose your content directly from the platform.

Beam AI is the #1 end-to-end automated takeoff software designed for General Contractors, Subcontractors, and Suppliers in the construction industry. It leverages cutting-edge Artificial Intelligence technology to provide accurate and fast quantity takeoffs for various trades, saving up to 90% of the time typically spent on manual takeoffs. With Beam AI, users can streamline their bidding process, send out more estimates, and focus on value engineering to build competitive estimates. The software offers features such as cloud-based collaboration, 100% done-for-you quantity takeoffs, auto-detection of spec details, and the ability to process multiple takeoffs in parallel.

Wannafake is a user-friendly online platform that allows users to swap faces in videos using just one photo. The application enables users to easily create fun and original videos by uploading photos and videos for free, combining them to create new videos. Wannafake offers a simple face swap tool with no subscriptions, allowing users to pay as they go. Users can buy seconds and spend them whenever they want, with built-in video clipping feature to easily trim videos and pay only for the clipped part. The platform allows users to create multiple videos simultaneously, ensuring videos are created fast and in parallel. Wannafake also offers a 15-second free trial upon creating a free account. Terms of use, privacy policy, and contact information are provided for user convenience.

Iambic Therapeutics is a cutting-edge AI-driven drug discovery platform that tackles the most challenging design problems in drug discovery, addressing unmet patient need. Its physics-based AI algorithms drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week. Iambic's platform optimizes target product profiles, exploring multiple profiles in parallel to ensure that molecules are designed to solve the right problems in disease biology. It also optimizes drug candidates, deeply exploring chemical space to reveal novel mechanisms of action and deliver diverse high-quality leads.

Imperative Execution is the parent company of IntelligentCross, a platform that uses artificial intelligence (AI) to optimize trading performance in the US equities market. The platform's matching logic enhances market efficiency by optimizing price discovery and minimizing market impact. IntelligentCross is built with high-performance, massively parallel transaction processing that fully utilizes modern multi-core servers.

Pentest Copilot by BugBase is an ultimate ethical hacking assistant that guides users through each step of the hacking journey, from analyzing web apps to root shells. It eliminates redundant research, automates payload and command generation, and provides intelligent contextual analysis to save time. The application excels at data extraction, privilege escalation, lateral movement, and leaving no trace behind. With features like secure VPN integration, total control over sessions, parallel command processing, and flexibility to choose between local or cloud execution, Pentest Copilot offers a seamless and efficient hacking experience without the need for Kali Linux installation.

SquadGPT is an AI-powered platform designed to help startups streamline their hiring process by creating accurate job descriptions and screening candidates efficiently. The tool allows users to generate job descriptions with AI assistance, share them on various platforms, and then sit back while the AI screens candidates in parallel. SquadGPT aims to revolutionize the recruitment process by providing personalized and conversational screening experiences, ultimately accelerating the hiring process for startups.

This repository contains a student training series focusing on AI-driven science on supercomputers. It covers topics such as ALCF systems overview, AI on supercomputers, neural networks, LLMs, and parallel training techniques. The content is organized into subdirectories with prefixed indexes for easy navigation. The series aims to provide hands-on experience and knowledge in utilizing AI on supercomputers for scientific research.

SWIFT (Scalable lightWeight Infrastructure for Fine-Tuning) supports training, inference, evaluation and deployment of nearly **200 LLMs and MLLMs** (multimodal large models). Developers can directly apply our framework to their own research and production environments to realize the complete workflow from model training and evaluation to application. In addition to supporting the lightweight training solutions provided by [PEFT](https://github.com/huggingface/peft), we also provide a complete **Adapters library** to support the latest training techniques such as NEFTune, LoRA+, LLaMA-PRO, etc. This adapter library can be used directly in your own custom workflow without our training scripts. To facilitate use by users unfamiliar with deep learning, we provide a Gradio web-ui for controlling training and inference, as well as accompanying deep learning courses and best practices for beginners. Additionally, we are expanding capabilities for other modalities. Currently, we support full-parameter training and LoRA training for AnimateDiff.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

The NeMo Framework Launcher is a cloud-native tool designed for launching end-to-end NeMo Framework training jobs. It focuses on foundation model training for generative AI models, supporting large language model pretraining with techniques like model parallelism, tensor, pipeline, sequence, distributed optimizer, mixed precision training, and more. The tool scales to thousands of GPUs and can be used for training LLMs on trillions of tokens. It simplifies launching training jobs on cloud service providers or on-prem clusters, generating submission scripts, organizing job results, and supporting various model operations like fine-tuning, evaluation, export, and deployment.

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.

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

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

Long-Context-Attention (YunChang) is a unified sequence parallel approach that combines the strengths of DeepSpeed-Ulysses-Attention and Ring-Attention to provide a versatile and high-performance solution for long context LLM model training and inference. It addresses the limitations of both methods by offering no limitation on the number of heads, compatibility with advanced parallel strategies, and enhanced performance benchmarks. The tool is verified in Megatron-LM and offers best practices for 4D parallelism, making it suitable for various attention mechanisms and parallel computing advancements.

Consistency Large Language Models (CLLMs) is a family of efficient parallel decoders that reduce inference latency by efficiently decoding multiple tokens in parallel. The models are trained to perform efficient Jacobi decoding, mapping any randomly initialized token sequence to the same result as auto-regressive decoding in as few steps as possible. CLLMs have shown significant improvements in generation speed on various tasks, achieving up to 3.4 times faster generation. The tool provides a seamless integration with other techniques for efficient Large Language Model (LLM) inference, without the need for draft models or architectural modifications.

Chinese-Tiny-LLM is a repository containing procedures for cleaning Chinese web corpora and pre-training code. It introduces CT-LLM, a 2B parameter language model focused on the Chinese language. The model primarily uses Chinese data from a 1,200 billion token corpus, showing excellent performance in Chinese language tasks. The repository includes tools for filtering, deduplication, and pre-training, aiming to encourage further research and innovation in language model development.

DashInfer is a C++ runtime tool designed to deliver production-level implementations highly optimized for various hardware architectures, including x86 and ARMv9. It supports Continuous Batching and NUMA-Aware capabilities for CPU, and can fully utilize modern server-grade CPUs to host large language models (LLMs) up to 14B in size. With lightweight architecture, high precision, support for mainstream open-source LLMs, post-training quantization, optimized computation kernels, NUMA-aware design, and multi-language API interfaces, DashInfer provides a versatile solution for efficient inference tasks. It supports x86 CPUs with AVX2 instruction set and ARMv9 CPUs with SVE instruction set, along with various data types like FP32, BF16, and InstantQuant. DashInfer also offers single-NUMA and multi-NUMA architectures for model inference, with detailed performance tests and inference accuracy evaluations available. The tool is supported on mainstream Linux server operating systems and provides documentation and examples for easy integration and usage.

Simplifine is an open-source library designed for easy LLM finetuning, enabling users to perform tasks such as supervised fine tuning, question-answer finetuning, contrastive loss for embedding tasks, multi-label classification finetuning, and more. It provides features like WandB logging, in-built evaluation tools, automated finetuning parameters, and state-of-the-art optimization techniques. The library offers bug fixes, new features, and documentation updates in its latest version. Users can install Simplifine via pip or directly from GitHub. The project welcomes contributors and provides comprehensive documentation and support for users.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

DuoAttention is a framework designed to optimize long-context large language models (LLMs) by reducing memory and latency during inference without compromising their long-context abilities. It introduces a concept of Retrieval Heads and Streaming Heads to efficiently manage attention across tokens. By applying a full Key and Value (KV) cache to retrieval heads and a lightweight, constant-length KV cache to streaming heads, DuoAttention achieves significant reductions in memory usage and decoding time for LLMs. The framework uses an optimization-based algorithm with synthetic data to accurately identify retrieval heads, enabling efficient inference with minimal accuracy loss compared to full attention. DuoAttention also supports quantization techniques for further memory optimization, allowing for decoding of up to 3.3 million tokens on a single GPU.

Call me Data- I draw historical parallels to your queries // An education tool // "Nothing new under the sun"

Generates 3D stereogram pairs for parallel viewing.

The Multiversal Prediction Matrix (MPM) leverages the speculative nature of multiverse theories to create a predictive framework. By simulating parallel universes with varied parameters, MPM explores a multitude of potential outcomes for different events and phenomena.

Expert in CUDA for configuration, installation, troubleshooting, and programming.