Airports is a JSON collection with detailed information about over 28,000 airports and landing strips worldwide. Each entry includes IATA code, airport name, city, country code, elevation, coordinates, and time zone.

OpenPromptInjection is an open-source toolkit for attacks and defenses in LLM-integrated applications, enabling easy implementation, evaluation, and extension of attacks, defenses, and LLMs. It supports various attack and defense strategies, including prompt injection, paraphrasing, retokenization, data prompt isolation, instructional prevention, sandwich prevention, perplexity-based detection, LLM-based detection, response-based detection, and know-answer detection. Users can create models, tasks, and apps to evaluate different scenarios. The toolkit currently supports PaLM2 and provides a demo for querying models with prompts. Users can also evaluate ASV for different scenarios by injecting tasks and querying models with attacked data prompts.

Open dubbing is an AI dubbing system that uses machine learning models to automatically translate and synchronize audio dialogue into different languages. It is designed as a command line tool. The project is experimental and aims to explore speech-to-text, text-to-speech, and translation systems combined. It supports multiple text-to-speech engines, translation engines, and gender voice detection. The tool can automatically dub videos, detect source language, and is built on open-source models. The roadmap includes better voice control, optimization for long videos, and support for multiple video input formats. Users can post-edit dubbed files by manually adjusting text, voice, and timings. Supported languages vary based on the combination of systems used.

EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.

This repository serves as a support page for the book 'Deciphering Generative AI from Original Papers' released by Gijutsu-Hyohron Co., Ltd. It includes answers to exercises and errata from the book. The exercises are provided in chapter-specific .md files in the 'exercises' directory. Please note that there may be some rendering issues with GitHub's math rendering, and the answers are just examples for reference. Contributions to this repository can be made by following the guidelines in CONTRIBUTING.md.

**rtp-llm** is a Large Language Model (LLM) inference acceleration engine developed by Alibaba's Foundation Model Inference Team. It is widely used within Alibaba Group, supporting LLM service across multiple business units including Taobao, Tmall, Idlefish, Cainiao, Amap, Ele.me, AE, and Lazada. The rtp-llm project is a sub-project of the havenask.

AI Hospital is a research repository focusing on the interactive evaluation and collaboration of Large Language Models (LLMs) as intern doctors for clinical diagnosis. The repository includes a simulation module tailored for various medical roles, introduces the Multi-View Medical Evaluation (MVME) Benchmark, provides dialog history documents of LLMs, replication instructions, performance evaluation, and guidance for creating intern doctor agents. The collaborative diagnosis with LLMs emphasizes dispute resolution. The study was authored by Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xie, Fei Huang, and Jingren Zhou.

Fast-DLLM is a diffusion-based Large Language Model (LLM) inference acceleration framework that supports efficient inference for models like Dream and LLaDA. It offers fast inference support, multiple optimization strategies, code generation, evaluation capabilities, and an interactive chat interface. Key features include Key-Value Cache for Block-Wise Decoding, Confidence-Aware Parallel Decoding, and overall performance improvements. The project structure includes directories for Dream and LLaDA model-related code, with installation and usage instructions provided for using the LLaDA and Dream models.

The Java-AI-Book-Code repository contains code examples for the 2020 edition of 'Practical Artificial Intelligence With Java'. It is a comprehensive update of the previous 2013 edition, featuring new content on deep learning, knowledge graphs, anomaly detection, linked data, genetic algorithms, search algorithms, and more. The repository serves as a valuable resource for Java developers interested in AI applications and provides practical implementations of various AI techniques and algorithms.

FlashInfer is a library for Language Languages Models that provides high-performance implementation of LLM GPU kernels such as FlashAttention, PageAttention and LoRA. FlashInfer focus on LLM serving and inference, and delivers state-the-art performance across diverse scenarios.

BIG-Bench Mistake is a dataset of chain-of-thought (CoT) outputs annotated with the location of the first logical mistake. It was released as part of a research paper focusing on benchmarking LLMs in terms of their mistake-finding ability. The dataset includes CoT traces for tasks like Word Sorting, Tracking Shuffled Objects, Logical Deduction, Multistep Arithmetic, and Dyck Languages. Human annotators were recruited to identify mistake steps in these tasks, with automated annotation for Dyck Languages. Each JSONL file contains input questions, steps in the chain of thoughts, model's answer, correct answer, and the index of the first logical mistake.

ReEdgeGPT is a tool designed for reverse engineering the chat feature of the new version of Bing. It provides documentation and guidance on how to collect and use cookies to access the chat feature. The tool allows users to create a chatbot using the collected cookies and interact with the Bing GPT chatbot. It also offers support for different modes like Copilot and Bing, along with plugins for various tasks. The tool covers historical information about Rome, the Lazio region, and provides troubleshooting tips for common issues encountered while using the tool.

Enterprise h2oGPTe - GenAI RAG is a repository containing code examples, notebooks, and benchmarks for the enterprise version of h2oGPTe, a powerful AI tool for generating text based on the RAG (Retrieval-Augmented Generation) architecture. The repository provides resources for leveraging h2oGPTe in enterprise settings, including implementation guides, performance evaluations, and best practices. Users can explore various applications of h2oGPTe in natural language processing tasks, such as text generation, content creation, and conversational AI.

SatoshiVM Pioneers NFT is a collection of NFTs issued by SatoshiVM team to reward early contributors. The repository contains information about the NFT collection, including the contract address and winner list.

VisionLLM is a series of large language models designed for vision-centric tasks. The latest version, VisionLLM v2, is a generalist multimodal model that supports hundreds of vision-language tasks, including visual understanding, perception, and generation.

Graph of Thoughts (GoT) is an official implementation framework designed to solve complex problems by modeling them as a Graph of Operations (GoO) executed with a Large Language Model (LLM) engine. It offers flexibility to implement various approaches like CoT or ToT, allowing users to solve problems using the new GoT approach. The framework includes setup guides, quick start examples, documentation, and examples for users to understand and utilize the tool effectively.

Airports is a JSON collection with detailed information about over 28,000 airports and landing strips worldwide. Each entry includes IATA code, airport name, city, country code, elevation, coordinates, and time zone.

Airports is a JSON collection with detailed information about over 28,000 airports and landing strips worldwide. Each entry includes IATA code, airport name, city, country code, elevation, coordinates, and time zone.

AirTrail is a web application that allows users to track their flights and view their flight history. It features an interactive world map to view flights, flight history tracking, statistics insights, multiple user management with user authentication, responsive design, dark mode, and flight import from various sources.

A website that tries to make sense of those three-letter airport codes. It provides detailed information about each airport, including its name, location, and a description. The site also includes a search function that allows users to find airports by name, city, or country. Airport content can be found in `/data` in individual files. Use the three-letter airport code as the filename (e.g. `phx.json`). Content in each `json` file: `id` = three-letter code (e.g. phx), `name` = airport name (Sky Harbor International Airport), `city` = primary city name (Phoenix), `state` = state name, if applicable (Arizona), `stateShort` = state abbreviation, if applicable (AZ), `country` = country name (USA), `description` = description, accepts markdown, use * for emphasis on letters, `imageCredit` = name of photographer, `imageCreditLink` = URL of photographer's Flickr page. You can also optionally add for aid in searching: `city2` = another city or country the airport may be known for. Adding a `json` file to `/data` will automatically render it. You do not need to manually add the path anywhere.

This tool is an AIG install for MSFS ONLY EXCLUDING offline AI flight plans. It provides a solution to model matching for online networks along with providing a tool to inject live traffic to your simulator, directly from Flightradar24. The tool is designed for use with online virtual traffic networks like VATSIM, but it will also work for offline traffic. A VMR File for VATSIM usage has been included in the folder.

VacAIgent is an AI tool that automates and enhances trip planning by leveraging the CrewAI framework. It integrates a user-friendly Streamlit interface for interactive travel planning. Users can input preferences and receive tailored travel plans with the help of autonomous AI agents. The tool allows for collaborative decision-making on cities and crafting complete itineraries based on specified preferences, all accessible via a streamlined Streamlit user interface. VacAIgent can be customized to use different AI models like GPT-3.5 or local models like Ollama for enhanced privacy and customization.

Amadeus Node SDK provides a rich set of APIs for the travel industry. It allows developers to interact with various endpoints related to flights, hotels, activities, and more. The SDK simplifies making API calls, handling promises, pagination, logging, and debugging. It supports a wide range of functionalities such as flight search, booking, seat maps, flight status, points of interest, hotel search, sentiment analysis, trip predictions, and more. Developers can easily integrate the SDK into their Node.js applications to access Amadeus APIs and build travel-related applications.

Airports is a repository containing an up-to-date CSV dump of the Travelhackingtool.com airport database. It provides basic information about every IATA airport and city code worldwide, including IATA code, ICAO code, timezone, name, city code, country code, URL, elevation, coordinates, and geo-encoded city, county, and state.

Amadeus Python SDK provides a rich set of APIs for the travel industry. It allows users to make API calls for various travel-related tasks such as flight offers search, hotel bookings, trip purpose prediction, flight delay prediction, airport on-time performance, travel recommendations, and more. The SDK conveniently maps API paths to similar paths, making it easy to interact with the Amadeus APIs. Users can initialize the client with their API key and secret, make API calls, handle responses, and enable logging for debugging purposes. The SDK documentation includes detailed information about each SDK method, arguments, and return types.