Best AI tools for< Load Embeddings >

Milo is an AI-powered co-pilot for parents, designed to help them manage the chaos of family life. It uses GPT-4, the latest in large-language models, to sort and organize information, send reminders, and provide updates. Milo is designed to be accurate and solve complex problems, and it learns and gets better based on user feedback. It can be used to manage tasks such as adding items to a grocery list, getting updates on the week's schedule, and sending screenshots of birthday invitations.

Vendorful is an AI-powered tool designed to assist users in responding to Requests for Proposals (RFPs), Requests for Information (RFIs), and Security Questionnaires. The tool leverages artificial intelligence to generate draft responses with better-than-human accuracy based on the user's content. Vendorful aims to streamline the RFP response process, save time, and increase the chances of winning deals by providing contextual smarts and flexible answers.

WebPilot is an AI tool designed to enhance your GPTs by enabling them to perform various tasks such as opening URL/file links, using multiple search engines, accessing all types of websites, loading dynamic web content, and providing enhanced answers. It offers a super easy way to interact with webpages, assisting in tasks like responding to emails, writing in forms, and solving quizzes. WebPilot is free, open-source, and has been featured by Google Extension Store as an established publisher.

VoiceGPT is an Android app that provides a voice-based interface to interact with AI language models like ChatGPT, Bing AI, and Bard. It offers features such as unlimited free messages, voice input and output in 67+ languages, a floating bubble for easy switching between apps, OCR text recognition, code execution, image generation with DALL-E 2, and support for ChatGPT Plus accounts. VoiceGPT is designed to be accessible for users with visual impairments, dyslexia, or other conditions, and it can be set as the default assistant to be activated hands-free with a custom hotword.

Parade is a capacity management platform designed for freight brokerages and 3PLs to streamline operations, automate bookings, and improve margins. The platform leverages advanced AI to optimize pricing, bidding, and carrier management, helping users book more loads efficiently. Parade integrates seamlessly with existing tech stacks, offering precise pricing, optimized bidding, and enhanced shipper connectivity. The platform boasts a range of features and benefits aimed at increasing efficiency, reducing costs, and boosting margins for freight businesses.

The website offers an AI-powered tool called SwapFans that allows users to load balance and receive discounts. Users can easily FaceSwap any social media videos and swap entire Instagram and TikTok accounts with high-speed FaceSwap AI. The tool is designed to help users manage their social media presence effectively and efficiently.

PixieBrix is an AI engagement platform that allows users to build, deploy, and manage internal AI tools to drive team productivity. It unifies AI landscapes with oversight and governance for enterprise scale. The platform is enterprise-ready and fully customizable to meet unique needs, and can be deployed on any site, making it easy to integrate into existing systems. PixieBrix leverages the power of AI and automation to harness the latest technology to streamline workflows and take productivity to new heights.

TLDRai.com is an AI tool designed to help users summarize any text into concise and easy-to-digest content, enabling them to free themselves from information overload. The tool utilizes AI technology to provide efficient text summarization services, making it a valuable resource for individuals seeking quick and accurate summaries of lengthy texts.

The website promptsplitter.com is experiencing an Argo Tunnel error on the Cloudflare network. Users encountering this error are advised to wait a few minutes if they are visitors, or ensure that cloudflared is running and can reach the network if they are the website owners. The error message provides guidance on troubleshooting steps to resolve the issue.

Merlin AI is a YouTube transcript tool that allows users to create summaries of YouTube videos. It is easy to use and can be added to Chrome as an extension. Merlin AI is powered by an undocumented API and features the latest build.

Daxtra is an AI-powered recruitment technology tool designed to help staffing and recruiting professionals find, parse, match, and engage the best candidates quickly and efficiently. The tool offers a suite of products that seamlessly integrate with existing ATS or CRM systems, automating various recruitment processes such as candidate data loading, CV/resume formatting, information extraction, and job matching. Daxtra's solutions cater to corporates, vendors, job boards, and social media partners, providing a comprehensive set of developer components to enhance recruitment workflows.

Lex Fridman is an AI tool developed by Lex Fridman, a Research Scientist at MIT, focusing on human-robot interaction and machine learning. The tool offers various resources such as podcasts, research publications, and studies related to AI-assisted driving data collection, autonomous vehicle systems, gaze estimation, and cognitive load estimation. It aims to provide insights into the safe and enjoyable interaction between humans and AI in driving scenarios.

Kolank is an AI tool that provides a unified API for accessing a wide range of Language Model Models (LLMs) and providers. It offers features such as model comparison based on price, latency, output, context, and throughput, OpenAI compatible API integration, transparency in tracking API calls and token expenditure, cost reduction by paying for performance, load balancing with fallbacks, and easy integration with preferred LLMs using Python, Javascript, and Curl.

LiteLLM is an AI tool that offers a Unified API for Azure OpenAI Vertex AI Bedrock. It provides a proxy server for managing authentication, load balancing, and spend tracking across a wide range of LLMs. LiteLLM is designed to simplify the integration and management of various AI services in the OpenAI format. With features like cloud deployment, open-source availability, and extensive provider integrations, LiteLLM aims to streamline AI development workflows and enhance operational efficiency.

Avaturn is a realistic 3D avatar creator that uses generative AI to turn a 2D photo into a recognizable and realistic 3D avatar. With endless options for avatar customization, you can create a unique look for each and everyone. Export your avatar as a 3D model and load it in Blender, Unity, Unreal Engine, Maya, Cinema4D, or any other 3D environment. The avatars come with a standard humanoid body rig, ARKit blendshapes, and visemes. They are compatible with Mixamo animations and VTubing software.

Epicflow is an AI-based multi-project and resource management software designed to help organizations deliver more projects on time with available resources, increase profitability, and make informed project decisions using real-time data and predictive analytics. The software bridges demand and supply by matching talent based on competencies, experience, and availability. It offers features like AI assistant, What-If Analysis, Future Load Graph, Historical Load Graph, Task List, and Competence Management Pipeline. Epicflow is trusted by leading companies in various industries for high performance and flawless project delivery.

Ermine.ai is an AI tool that provides local audio recording and transcription services. Users can easily transcribe audio files into text using this tool. The application currently supports Chrome browser and is working on adding support for Firefox. It requires the browser to load and initialize the transcription model, which may take a few minutes during the first use. The tool is designed to offer fast transcription services with support for English language only.

Knowbo is a custom chatbot tool that allows users to create a chatbot for their website in just 2 minutes. The chatbot learns directly from the website or documentation, providing up-to-date information to users. With features like easy deployment, chat history tracking, and customization options, Knowbo aims to revolutionize customer experience by reducing the load on support teams and offering a seamless way for users to get their questions answered quickly.

LLMFlex is a python package designed for developing AI applications with local Large Language Models (LLMs). It provides classes to load LLM models, embedding models, and vector databases to create AI-powered solutions with prompt engineering and RAG techniques. The package supports multiple LLMs with different generation configurations, embedding toolkits, vector databases, chat memories, prompt templates, custom tools, and a chatbot frontend interface. Users can easily create LLMs, load embeddings toolkit, use tools, chat with models in a Streamlit web app, and serve an OpenAI API with a GGUF model. LLMFlex aims to offer a simple interface for developers to work with LLMs and build private AI solutions using local resources.

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.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

WordLlama is a fast, lightweight NLP toolkit optimized for CPU hardware. It recycles components from large language models to create efficient word representations. It offers features like Matryoshka Representations, low resource requirements, binarization, and numpy-only inference. The tool is suitable for tasks like semantic matching, fuzzy deduplication, ranking, and clustering, making it a good option for NLP-lite tasks and exploratory analysis.

This repository provides the official implementation of the paper 'On Embeddings for Numerical Features in Tabular Deep Learning'. It focuses on transforming scalar continuous features into vectors before integrating them into the main backbone of tabular neural networks, showcasing improved performance. The embeddings for continuous features are shown to enhance the performance of tabular DL models and are applicable to various conventional backbones, offering efficiency comparable to Transformer-based models. The repository includes Python packages for practical usage, exploration of metrics and hyperparameters, and reproducing reported results for different algorithms and datasets.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

Wllama is a WebAssembly binding for llama.cpp, a high-performance and lightweight language model library. It enables you to run inference directly on the browser without the need for a backend or GPU. Wllama provides both high-level and low-level APIs, allowing you to perform various tasks such as completions, embeddings, tokenization, and more. It also supports model splitting, enabling you to load large models in parallel for faster download. With its Typescript support and pre-built npm package, Wllama is easy to integrate into your React Typescript projects.

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.

yt-fts is a command line program that uses yt-dlp to scrape all of a YouTube channels subtitles and load them into a sqlite database for full text search. It allows users to query a channel for specific keywords or phrases and generates time stamped YouTube URLs to the videos containing the keyword. Additionally, it supports semantic search via the OpenAI embeddings API using chromadb.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

CurateGPT is a prototype web application and framework for performing general purpose AI-guided curation and curation-related operations over collections of objects. It allows users to load JSON, YAML, or CSV data, build vector database indexes for ontologies, and interact with various data sources like GitHub, Google Drives, Google Sheets, and more. The tool supports ontology curation, knowledge base querying, term autocompletion, and all-by-all comparisons for objects in a collection.

gemini-cli is a versatile command-line interface for Google's Gemini LLMs, written in Go. It includes tools for chatting with models, generating/comparing embeddings, and storing data in SQLite for analysis. Users can interact with Gemini models through various subcommands like prompt, chat, counttok, embed content, embed db, and embed similar.

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.

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.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

This repository contains code for the paper 'Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models'. It focuses on fine-tuning CLIP in an unsupervised manner to enhance its robustness against visual adversarial attacks. By replacing the vision encoder of large vision-language models with the fine-tuned CLIP models, it achieves state-of-the-art adversarial robustness on various vision-language tasks. The repository provides adversarially fine-tuned ViT-L/14 CLIP models and offers insights into zero-shot classification settings and clean accuracy improvements.

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.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

Hezar is an all-in-one AI library designed specifically for the Persian community. It brings together various AI models and tools, making it easy to use AI with just a few lines of code. The library seamlessly integrates with Hugging Face Hub, offering a developer-friendly interface and task-based model interface. In addition to models, Hezar provides tools like word embeddings, tokenizers, feature extractors, and more. It also includes supplementary ML tools for deployment, benchmarking, and optimization.

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