Best AI tools for< Train Embeddings >

HappyAccidents is an AI-powered art generation tool that makes it easy to create stunning images from text prompts. With HappyAccidents, you can generate images from any open-source model, train your own embeddings, and use powerful features like inpainting and upscaling. HappyAccidents is perfect for artists, designers, and anyone who wants to create beautiful images without the hassle of learning complex AI models.

Stable Diffusion is an AI art generation tool that allows users to create high-quality images from text descriptions. It offers a user-friendly platform for both beginners and experts to explore AI art creation without deep technical knowledge. The tool excels in producing complex, detailed, and customizable images, making it ideal for artists, designers, and anyone looking to integrate AI into their creative process. Stable Diffusion provides unprecedented creative freedom through features like image generation, inpainting, outpainting, and text-guided image-to-image translation.

Chunky is an AI chatbot builder that allows users to create human-like chatbots effortlessly. With Chunky, users can automate customer support, answer frequently asked questions, and save time by setting up their own AI-powered bot in just a few minutes. The platform offers a user-friendly experience with no coding required, integrated chatbot deployment on websites, and customization options for branding. Chunky utilizes the ChatGPT API and Embeddings provided by OpenAI to deliver smart chatbot interactions in close to 95 languages.

StartKit.AI is a boilerplate code for AI products that helps users build their AI startups 100x faster. It includes pre-built REST API routes for all common AI functionality, a pre-configured Pinecone for text embeddings and Retrieval-Augmented Generation (RAG) for chat endpoints, and five React demo apps to help users get started quickly. StartKit.AI also provides a license key and magic link authentication, user & API limit management, and full documentation for all its code. Additionally, users get access to guides to help them get set up and one year of updates.

Exa is a web API designed to provide AI applications with powerful access to the web by organizing and retrieving the best content using embeddings. It offers features like semantic search, similarity search, content scraping, and powerful filters to help developers and companies gather and process data for AI training and analysis. Exa is trusted by thousands of developers and companies for its speed, quality, and ability to provide up-to-date information from various sources on the web.

GPTBots.ai is a powerful no-code platform for creating AI-driven business applications. It seamlessly integrates large language models with organizational data, services, and workflows to empower AI bots in driving business growth. The platform allows users to build and train AI bots without coding experience, access best-practice AI bot templates, optimize and customize AI knowledge base, and adapt to various scenarios with intelligent agent bots. GPTBots supports diverse input types, offers versatile language models, enables seamless chatbot-human handoff, and provides robust API and SDK for embedding capabilities into products. Trusted by over 100k companies worldwide, GPTBots helps enterprises enhance customer service, leads generation, SEO writing, data analysis, and more.

IBM Watsonx is an enterprise studio for AI builders. It provides a platform to train, validate, tune, and deploy AI models quickly and efficiently. With Watsonx, users can access a library of pre-trained AI models, build their own models, and deploy them to the cloud or on-premises. Watsonx also offers a range of tools and services to help users manage and monitor their AI models.

Athletica AI is an AI-powered athletic training and personalized fitness application that offers tailored coaching and training plans for various sports like cycling, running, duathlon, triathlon, and rowing. It adapts to individual fitness levels, abilities, and availability, providing daily step-by-step training plans and comprehensive session analyses. Athletica AI integrates seamlessly with workout data from platforms like Garmin, Strava, and Concept 2 to craft personalized training plans and workouts. The application aims to help athletes train smarter, not harder, by leveraging the power of AI to optimize performance and achieve fitness goals.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

Kaiden AI is an AI-powered training platform that offers personalized, immersive simulations to enhance skills and performance across various industries and roles. It provides feedback-rich scenarios, voice-enabled interactions, and detailed performance insights. Users can create custom training scenarios, engage with AI personas, and receive real-time feedback to improve communication skills. Kaiden AI aims to revolutionize training solutions by combining AI technology with real-world practice.

Endurance is a platform designed for runners, swimmers, and cyclists to engage in group training activities with friends or local communities. Users can create or join teams, share structured workouts, and benefit from collective motivation and accountability. The platform aims to make training fun and effective by leveraging the power of group workouts and social connections.

ChatCube is an AI-powered chatbot maker that allows users to create chatbots for their websites without coding. It uses advanced AI technology to train chatbots on any document or website within 60 seconds. ChatCube offers a range of features, including a user-friendly visual editor, lightning-fast integration, fine-tuning on specific data sources, data encryption and security, and customizable chatbots. By leveraging the power of AI, ChatCube helps businesses improve customer support efficiency and reduce support ticket reductions by up to 28%.

Workout Tools is an AI-powered personal trainer that helps you train smarter and reach your fitness goals faster. It takes into account different parameters, such as your physics, the type of workout you're interested in, your available equipment, and comes up with a suggested workout. Don't like the workout? Just generate another one. It's that simple.

CoRover.ai is an AI-powered chatbot designed to help users book train tickets seamlessly through conversation. The chatbot, named AskDISHA, is integrated with the IRCTC platform, allowing users to inquire about train schedules, ticket availability, and make bookings effortlessly. CoRover.ai leverages artificial intelligence to provide personalized assistance and streamline the ticket booking process for users, enhancing their overall experience.

IllumiDesk is a generative AI platform for instructors and content developers that helps teams create and monetize content tailored 10X faster. With IllumiDesk, you can automate grading tasks, collaborate with your learners, create awesome content at the speed of AI, and integrate with the services you know and love. IllumiDesk's AI will help you create, maintain, and structure your content into interactive lessons. You can also leverage IllumiDesk's flexible integration options using the RESTful API and/or LTI v1.3 to leverage existing content and flows. IllumiDesk is trusted by training agencies and universities around the world.

Tovuti LMS is an adaptive, people-first learning platform that helps organizations create engaging courses, train teams, and track progress. With its easy-to-use interface and powerful features, Tovuti LMS makes learning fun and easy. Tovuti LMS is trusted by leading organizations around the world to provide their employees with the training they need to succeed.

Chatbond is an AI chatbot builder that enables users to create customized chatbots for websites and messaging platforms without the need for coding skills. With Chatbond, users can design conversational interfaces, integrate AI capabilities, and deploy chatbots to enhance customer engagement and streamline communication processes. The platform offers a user-friendly interface with drag-and-drop functionality, pre-built templates, and analytics tools to monitor chatbot performance and optimize interactions. Chatbond empowers businesses to automate customer support, lead generation, and sales processes, improving efficiency and scalability.

Teachable Machine is a web-based tool that makes it easy to create custom machine learning models, even if you don't have any coding experience. With Teachable Machine, you can train models to recognize images, sounds, and poses. Once you've trained a model, you can export it to use in your own projects.

Sherpa.ai is a SaaS platform that enables data collaborations without sharing data. It allows businesses to build and train models with sensitive data from different parties, without compromising privacy or regulatory compliance. Sherpa.ai's Federated Learning platform is used in various industries, including healthcare, financial services, and manufacturing, to improve AI models, accelerate research, and optimize operations.

Surge AI is a data labeling platform that provides human-generated data for training and evaluating large language models (LLMs). It offers a global workforce of annotators who can label data in over 40 languages. Surge AI's platform is designed to be easy to use and integrates with popular machine learning tools and frameworks. The company's customers include leading AI companies, research labs, and startups.

Catalyst is a C# Natural Language Processing library designed for speed, inspired by spaCy's design. It provides pre-trained models, support for training word and document embeddings, and flexible entity recognition models. The library is fast, modern, and pure-C#, supporting .NET standard 2.0. It is cross-platform, running on Windows, Linux, macOS, and ARM. Catalyst offers non-destructive tokenization, named entity recognition, part-of-speech tagging, language detection, and efficient binary serialization. It includes pre-built models for language packages and lemmatization. Users can store and load models using streams. Getting started with Catalyst involves installing its NuGet Package and setting the storage to use the online repository. The library supports lazy loading of models from disk or online. Users can take advantage of C# lazy evaluation and native multi-threading support to process documents in parallel. Training a new FastText word2vec embedding model is straightforward, and Catalyst also provides algorithms for fast embedding search and dimensionality reduction.

Stable Diffusion web UI is a web interface for Stable Diffusion, implemented using Gradio library. It provides a user-friendly interface to access the powerful image generation capabilities of Stable Diffusion. With Stable Diffusion web UI, users can easily generate images from text prompts, edit and refine images using inpainting and outpainting, and explore different artistic styles and techniques. The web UI also includes a range of advanced features such as textual inversion, hypernetworks, and embeddings, allowing users to customize and fine-tune the image generation process. Whether you're an artist, designer, or simply curious about the possibilities of AI-generated art, Stable Diffusion web UI is a valuable tool that empowers you to create stunning and unique images.

AnglE is a library for training state-of-the-art BERT/LLM-based sentence embeddings with just a few lines of code. It also serves as a general sentence embedding inference framework, allowing for inferring a variety of transformer-based sentence embeddings. The library supports various loss functions such as AnglE loss, Contrastive loss, CoSENT loss, and Espresso loss. It provides backbones like BERT-based models, LLM-based models, and Bi-directional LLM-based models for training on single or multi-GPU setups. AnglE has achieved significant performance on various benchmarks and offers official pretrained models for both BERT-based and LLM-based models.

CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

LLoCO is a technique that learns documents offline through context compression and in-domain parameter-efficient finetuning using LoRA, which enables LLMs to handle long context efficiently.

Fastc is a tool focused on CPU execution, using efficient models for embedding generation and cosine similarity classification. It allows for efficient multi-classifier execution without extra overhead. Users can easily train text classifiers, export models, publish to HuggingFace, load existing models, make class predictions, use instruct templates, and launch an inference server. The tool provides an HTTP API for text classification with JSON payloads and supports multiple languages for language identification.

IG-LLM is a framework for solving inverse-graphics problems by instruction-tuning a Large Language Model (LLM) to decode visual embeddings into graphics code. The framework demonstrates natural generalization across distribution shifts without special inductive biases. It provides training and evaluation data for various scenarios like CLEVR, 2D, SO(3), 6-DoF, and ShapeNet. The environment setup can be done using conda/micromamba or Dockerfile. Training can be initiated for each scenario with specific commands, and inference can be performed using the provided script.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

Transformer Lab is an app that allows users to experiment with Large Language Models by providing features such as one-click download of popular models, finetuning across different hardware, RLHF and Preference Optimization, working with LLMs across different operating systems, chatting with models, using different inference engines, evaluating models, building datasets for training, calculating embeddings, providing a full REST API, running in the cloud, converting models across platforms, supporting plugins, embedded Monaco code editor, prompt editing, inference logs, all through a simple cross-platform GUI.

DeepPavlov is an open-source conversational AI library built on PyTorch. It is designed for the development of production-ready chatbots and complex conversational systems, as well as for research in the area of NLP and dialog systems. The library offers a wide range of models for tasks such as Named Entity Recognition, Intent/Sentence Classification, Question Answering, Sentence Similarity/Ranking, Syntactic Parsing, and more. DeepPavlov also provides embeddings like BERT, ELMo, and FastText for various languages, along with AutoML capabilities and integrations with REST API, Socket API, and Amazon AWS.

CALF (LLaTA) is a cross-modal fine-tuning framework that bridges the distribution discrepancy between temporal data and the textual nature of LLMs. It introduces three cross-modal fine-tuning techniques: Cross-Modal Match Module, Feature Regularization Loss, and Output Consistency Loss. The framework aligns time series and textual inputs, ensures effective weight updates, and maintains consistent semantic context for time series data. CALF provides scripts for long-term and short-term forecasting, requires Python 3.9, and utilizes word token embeddings for model training.

WebWhiz is an open-source tool that allows users to train ChatGPT on website data to build AI chatbots for customer queries. It offers easy integration, data-specific responses, regular data updates, no-code builder, chatbot customization, fine-tuning, and offline messaging. Users can create and train chatbots in a few simple steps by entering their website URL, automatically fetching and preparing training data, training ChatGPT, and embedding the chatbot on their website. WebWhiz can crawl websites monthly, collect text data and metadata, and process text data using tokens. Users can train custom data, but bringing custom open AI keys is not yet supported. The tool has no limitations on context size but may limit the number of pages based on the chosen plan. WebWhiz SDK is available on NPM, CDNs, and GitHub, and users can self-host it using Docker or manual setup involving MongoDB, Redis, Node, Python, and environment variables setup. For any issues, users can contact [email protected].

LL3DA is a Large Language 3D Assistant that responds to both visual and textual interactions within complex 3D environments. It aims to help Large Multimodal Models (LMM) comprehend, reason, and plan in diverse 3D scenes by directly taking point cloud input and responding to textual instructions and visual prompts. LL3DA achieves remarkable results in 3D Dense Captioning and 3D Question Answering, surpassing various 3D vision-language models. The code is fully released, allowing users to train customized models and work with pre-trained weights. The tool supports training with different LLM backends and provides scripts for tuning and evaluating models on various tasks.

RAGoon is a high-level library designed for batched embeddings generation, fast web-based RAG (Retrieval-Augmented Generation) processing, and quantized indexes processing. It provides NLP utilities for multi-model embedding production, high-dimensional vector visualization, and enhancing language model performance through search-based querying, web scraping, and data augmentation techniques.

Model2Vec is a technique to turn any sentence transformer into a really small static model, reducing model size by 15x and making the models up to 500x faster, with a small drop in performance. It outperforms other static embedding models like GLoVe and BPEmb, is lightweight with only `numpy` as a major dependency, offers fast inference, dataset-free distillation, and is integrated into Sentence Transformers, txtai, and Chonkie. Model2Vec creates powerful models by passing a vocabulary through a sentence transformer model, reducing dimensionality using PCA, and weighting embeddings using zipf weighting. Users can distill their own models or use pre-trained models from the HuggingFace hub. Evaluation can be done using the provided evaluation package. Model2Vec is licensed under MIT.

Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

The 'vector-search-class-notes' repository contains class materials for a course on Long Term Memory in AI, focusing on vector search and databases. The course covers theoretical foundations and practical implementation of vector search applications, algorithms, and systems. It explores the intersection of Artificial Intelligence and Database Management Systems, with topics including text embeddings, image embeddings, low dimensional vector search, dimensionality reduction, approximate nearest neighbor search, clustering, quantization, and graph-based indexes. The repository also includes information on the course syllabus, project details, selected literature, and contributions from industry experts in the field.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

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