Best AI tools for< Find A Distributor >

Push Lap Wholesale is a powerful Amazon wholesale sourcing tool that helps you find profitable products, save time, and hit your targets. With 97% matching accuracy, you can quickly scan your bulk price lists and never miss a potential profitable product. Our world-class platform provides you with detailed product information, including Keepa charts, historical averages, profit calculations, variation data, competition analysis, and multipack adjustments. You can also create and manage suppliers' purchase lists, export them as CSV files, and get the total cost and profit of each list. Additionally, we provide you with 500+ auto-ungate ASINs for free and access to a list of over 4,000 vetted and verified distributors with contact details.

arXiv.org is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

Letterdrop is a sales enablement platform designed to help businesses find warm leads efficiently and effectively. It empowers sales and marketing teams to build relationships with potential buyers, create thought leadership content, and automate lead nurturing processes. With a focus on social selling and inbound-outbound strategies, Letterdrop aims to increase booking rates, close pipeline gaps, and improve overall sales performance. The platform offers easy setup, proven playbooks, and results-driven solutions to enhance lead generation and conversion. Letterdrop is a valuable tool for organizations looking to optimize their sales processes and drive revenue growth.

Afroverse is an AI-powered music investment platform designed specifically for the Afrobeat industry. It provides tools for demo submissions, cross-border collaborations, music distribution, investment opportunities, community engagement, and more.

Viral Curation is a content management and publishing platform that uses the power of technology and advanced A.I. to make content creation and publishing more effective and time-saving. It offers a range of features to help users write, distribute, publish, and find viral content, including a built-in AI writing assistant, content scheduling, plagiarism checker, and team collaboration tools. Viral Curation is designed for bloggers, social media influencers, Facebook advertisers, copywriters, and website owners who want to create high-quality content quickly and easily.

Revoldiv is a California-based platform that simplifies media creation and consumption for podcast enthusiasts and media creators. Their platform aims to provide a simple space for building a community by connecting podcasters, listeners, and industry professionals.

PimEyes is an online face search engine that uses face recognition technology to find pictures containing given faces. It is a great tool to audit copyright infringement, protect your privacy, and find people.

Jobo is an AI-powered career assistant that helps you find your ideal job, enhance your resume, and apply for jobs, all in one go. It uses OpenAI's technology to personalize and optimize your job search, making it easier for you to land your dream job.

Naming Magic is a tool that uses AI to help you name your company and find an available domain. It was created by Swift Ventures, a venture capital firm that invests in AI and data-first businesses. The tool is designed to help entrepreneurs and business owners come up with creative and memorable names for their companies. It can also help you find a domain name that is available and relevant to your business.

Song Identifier is an AI tool that helps users find a song by entering words from the lyrics. The tool utilizes AI technology to match the input lyrics with a vast database of songs, providing users with accurate results. Created with love by Pablo, Song Identifier aims to assist users in identifying songs stuck in their heads quickly and effortlessly.

Rizz Check is a swipe game where users can befriend AI celebrities and ask them on dates. The game is built with Rizz, a library created by boredhead00.

Existential is an AI-powered career exploration platform that helps you discover your true calling. Our platform uses a combination of psychometric assessments, AI algorithms, and expert career counseling to help you identify your strengths, interests, and values. We then match you with a personalized list of career paths that are a good fit for you.

PetsApp is a comprehensive veterinary engagement and communication platform that offers a range of features including text and SMS chat, appointment booking, reminders, digital payments, video calls, and AI-assisted communication. It is designed to streamline communication between veterinary teams and clients, improve client engagement, and enhance overall clinic efficiency. PetsApp has been widely adopted by veterinary professionals and clinics, helping them save time, increase client satisfaction, and boost wellness plan subscriptions.

MiGuru is a platform designed to help you find your next job quickly and efficiently. Today it has a job search engine that consolidates the public offers of the Chilean market. Through the use of artificial intelligence, we learn from your answers and use information from your CV to complete your applications automatically. In addition, we support you in improving your CV through a complete personalized report with recommendations based on industry best practices, analyzed using artificial intelligence.

TripOffice.com is a comprehensive platform offering over 200,000 hotels tailored for remote workers. The website enables users to search for accommodations in various destinations worldwide, specifically curated for individuals seeking a comfortable workation experience. With a focus on providing ergonomic workspaces, TripOffice.com aims to enhance productivity and convenience for digital nomads and remote professionals. The platform also offers a wide range of travel destinations, hotels, and apartments to cater to diverse preferences and needs.

AI Fragrance Finder is a website that uses artificial intelligence to help users find the perfect fragrance. The website has a database of over 1,000 fragrances, and users can search for fragrances by scent, notes, and occasion. AI Fragrance Finder also provides personalized recommendations based on the user's preferences.

Deferred.com is a free AI tool designed to assist users with 1031 exchanges, a tax-deferral strategy in real estate investment. The platform offers a range of resources, including an exchange calculator, expert answers, and matching with 1031 professionals. Users can optimize tax savings, find the right intermediary, and access essential reading materials on tax deferral and exchange rules. With a focus on simplifying the complex process of 1031 exchanges, Deferred.com aims to empower real estate investors to make informed decisions and maximize their financial benefits.

AI Date ideas is a free AI-based date idea generator that provides users with unique and personalized date ideas based on their preferences. The tool is designed to help users find amazing date ideas faster and easier, and it offers a variety of filters to help users narrow down their search. AI Date ideas is also fully customizable, so users can create their own date ideas or modify existing ones to fit their needs.

Cuspera is an AI-powered software recommendation platform that helps businesses find the right software for their marketing and sales needs. It provides personalized software recommendations based on a business's specific needs and has a knowledgebase of over 17,000 software products. Cuspera's AI is trained on insights from peers and experts to guide businesses to the right software and recommends best practices from peer and expert experiences.

PouncerAI is an AI proposal tool designed to help freelancers on Upwork win more jobs by providing intelligent features that streamline the proposal process. It offers a Chrome Extension that assists in creating customized cover letters, real-time job notifications, and a unique Upstyler Toolbar for enhancing proposals. PouncerAI aims to save time and increase the chances of getting clients to reply by leveraging AI technology to generate tailored proposals quickly and efficiently.

Smile (Statistical Machine Intelligence and Learning Engine) is a comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. It covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc. Smile implements major machine learning algorithms and provides interactive shells for Java, Scala, and Kotlin. It supports model serialization, data visualization using SmilePlot and declarative approach, and offers a gallery showcasing various algorithms and visualizations.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

The 'airwin2rack' repository is a collection of Airwindows audio plugins presented in various formats, including as a static library, a module for VCV Rack, and as CLAP/VST3/AU/LV2/Standalone plugins for DAWs. Users can access these plugins through different methods and interfaces, such as a uniform registry and access pattern, making it easy to integrate Airwindows plugins into their audio projects. The repository also provides instructions for updating the Airwindows sub-library and information on licensing, ensuring that users can utilize the plugins in both open and closed source environments.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

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 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

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

Mobius is an AI infra platform including realtime computing and training. It is built on Ray, a distributed computing framework, and provides a number of features that make it well-suited for online machine learning tasks. These features include: * **Cross Language**: Mobius can run in multiple languages (only Python and Java are supported currently) with high efficiency. You can implement your operator in different languages and run them in one job. * **Single Node Failover**: Mobius has a special failover mechanism that only needs to rollback the failed node itself, in most cases, to recover the job. This is a huge benefit if your job is sensitive about failure recovery time. * **AutoScaling**: Mobius can generate a new graph with different configurations in runtime without stopping the job. * **Fusion Training**: Mobius can combine TensorFlow/Pytorch and streaming, then building an e2e online machine learning pipeline. Mobius is still under development, but it has already been used to power a number of real-world applications, including: * A real-time recommendation system for a major e-commerce company * A fraud detection system for a large financial institution * A personalized news feed for a major news organization If you are interested in using Mobius for your own online machine learning projects, you can find more information in the documentation.

Parrot is a distributed serving system for LLM-based Applications, designed to efficiently serve LLM-based applications by adding Semantic Variable in the OpenAI-style API. It allows for horizontal scalability with multiple Engine instances running LLM models communicating with ServeCore. The system enables AI agents to interact with LLMs via natural language prompts for collaborative tasks.

cake is a pure Rust implementation of the llama3 LLM distributed inference based on Candle. The project aims to enable running large models on consumer hardware clusters of iOS, macOS, Linux, and Windows devices by sharding transformer blocks. It allows running inferences on models that wouldn't fit in a single device's GPU memory by batching contiguous transformer blocks on the same worker to minimize latency. The tool provides a way to optimize memory and disk space by splitting the model into smaller bundles for workers, ensuring they only have the necessary data. cake supports various OS, architectures, and accelerations, with different statuses for each configuration.

ReaLHF is a distributed system designed for efficient RLHF training with Large Language Models (LLMs). It introduces a novel approach called parameter reallocation to dynamically redistribute LLM parameters across the cluster, optimizing allocations and parallelism for each computation workload. ReaL minimizes redundant communication while maximizing GPU utilization, achieving significantly higher Proximal Policy Optimization (PPO) training throughput compared to other systems. It supports large-scale training with various parallelism strategies and enables memory-efficient training with parameter and optimizer offloading. The system seamlessly integrates with HuggingFace checkpoints and inference frameworks, allowing for easy launching of local or distributed experiments. ReaLHF offers flexibility through versatile configuration customization and supports various RLHF algorithms, including DPO, PPO, RAFT, and more, while allowing the addition of custom algorithms for high efficiency.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

Oat is a simple and efficient framework for running online LLM alignment algorithms. It implements a distributed Actor-Learner-Oracle architecture, with components optimized using state-of-the-art tools. Oat simplifies the experimental pipeline of LLM alignment by serving an Oracle online for preference data labeling and model evaluation. It provides a variety of oracles for simulating feedback and supports verifiable rewards. Oat's modular structure allows for easy inheritance and modification of classes, enabling rapid prototyping and experimentation with new algorithms. The framework implements cutting-edge online algorithms like PPO for math reasoning and various online exploration algorithms.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

This repository contains the official codebase for Bittensor Subnet 1 (SN1) v1.0.0+, released on 22nd January 2024. It defines an incentive mechanism to create a distributed conversational AI for Subnet 1. Validators and miners are based on large language models (LLM) using internet-scale datasets and goal-driven behavior to drive human-like conversations. The repository requires python3.9 or higher and provides compute requirements for running validators and miners. Users can run miners or validators using specific commands and are encouraged to run on the testnet before deploying on the main network. The repository also highlights limitations and provides resources for understanding the architecture and methodology of SN1.

Assists with film/video production, editing, and distribution advice.

Assists in finding suitable lawyers based on user needs. Disclaimer - always do your own extra research

Find the perfect match for your design needs

I help you find a Show or Sporting Event on a Streaming Platform or Channel.

Helps users find stores and businesses with practical, location-based advice.

Find a recruiter in your industry, specialism, and location

This GPT assists in finding a top-rated accountant CPA - local or virtual. We account for their qualifications, experience, testimonials and reviews. Whether business or personal, provide a short description of the services wanted and city or state.

This GPT assists in finding a top-rated Virtual Creator specialized CPA - local or virtual. Accounting or Taxes, a CPA that aligns with your business! We account for their qualifications, experience, testimonials and reviews. Provide the services you require and your city or state.

Find a home in Europe (GPT for homestra.com)

Find a fishing spot in Australia

This AI tool by Learning Revolution and Hepler Consulting helps you find a good book to read, as well as its corresponding record on WorldCat.org.

This GPT will help you choose a market you could start creating a business in using Ed Dales 30 Day Challenge version of the Japanese Ikigai Process

Je t'aide à trouver ton métier idéal !

A mental health assistant to help choose a therapist based on needs, insurance, and location.

A helpful assistant for finding the perfect campground

Starts with a quiz to assess your personality across 10 dating-related areas, crafts a custom development road-map, and coaches you towards finding a fulfilling relationship.

A comprehensive Nationwide database of law firms and lawyers, including specialties, locations, and contact information with live URLs.

A funny virtual Dating Game Show.

I assist with finding businesses on Yellowpages, providing factual and updated information.

Have you ever wondered what it's like to own a flat in the heart of London? Let's dive into this exciting prospect. But why buy a flat here? For starters, London's property market is known for its resilience and long-term value. Isn't it time you considered being a part of London's unfolding story?