Best AI tools for< Find Parks >
20 - AI tool Sites
Proxi
Proxi is a web-based application that allows users to create custom maps with pins. Users can search for places near an area, plan day trips, explore history, find places with a specific vibe, and paste text to map the places. Proxi also offers a variety of map templates that users can customize to create their own maps.
Metropolis
Metropolis is an artificial intelligence company that provides checkout-free payment for drivers and revenue-generating operations for real estate owners. Metropolis' computer vision technology enables drivers to enter and exit parking facilities without having to stop and pay. Metropolis also offers a variety of other services, including parking management, valet services, and event parking. Metropolis is committed to providing a seamless and efficient parking experience for drivers and real estate owners alike.
Ai Drive
Ai Drive is an innovative AI-powered tool designed to streamline and enhance the driving experience. It utilizes advanced algorithms and machine learning to provide real-time navigation, traffic updates, and personalized recommendations to optimize routes. With its intuitive interface and smart features, Ai Drive aims to revolutionize the way people navigate and commute, making driving safer, more efficient, and enjoyable.
Daxtra
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.
HarmonySnippetsAI
HarmonySnippetsAI is an AI application designed to help music creators and content producers identify engaging segments within their tracks quickly and efficiently. By leveraging AI algorithms, users can upload audio files and receive results that highlight the most captivating parts of their music. This tool is ideal for musicians looking to promote their work on social media platforms like Instagram, Facebook, and TikTok, enhancing audience engagement and expanding their reach.
AIPodNav
AIPodNav is an AI-powered tool designed to enhance your podcast listening experience by providing features such as mind maps, summaries, takeaways, keywords, chapters, and transcriptions. It accelerates knowledge acquisition by 10 times faster than traditional podcast listening methods. AIPodNav aims to revolutionize how users engage with podcasts by offering innovative AI-driven functionalities.
Collato
Collato is an AI assistant designed to help product teams save time on writing documents, answering questions, and generating new content. It can find, summarize, and generate new content based on your own product knowledge, saving you hours in manual work. Collato is also self-hosted, so you can keep your data private and secure.
DoNotPay
DoNotPay is an AI-powered platform that helps consumers fight big corporations, protect their privacy, find hidden money, and beat bureaucracy. It offers a wide range of tools and services to help users with tasks such as disputing traffic tickets, canceling subscriptions, and getting refunds. DoNotPay is not a law firm and is not licensed to practice law. It provides a platform for legal information and self-help.
Whitetable
Whitetable is an AI tool that simplifies the hiring process by providing intelligent AI APIs for ultra-fast and optimal hiring. It offers features such as Resume Parsing API, Question API, Ranking API, and Evaluation API to streamline the recruitment process. Whitetable also provides a free AI-powered job search platform and an AI-powered ATS to help companies find the right candidates faster. With a focus on eliminating bias and improving efficiency, Whitetable is shaping the AI-driven future of hiring.
ATS Friendly
ATS Friendly is a free resume checker that uses AI to help you get your resume shortlisted by Applicant Tracking Systems (ATS). With our comprehensive resume keyword scanner, our AI powered ATS Resume Checker will definitely enhance your chances of getting filtered through Applicant Tracking Systems (ATS). Our FREE ATS Friendly Resume Checker allows you to check your resume against the job posting, before applying. Our AI powered ATS Scanner will go through the keywords, hard skills, soft skills and other requirements of the job description, and provide you with a comprehensive analysis. We have helped over 100,000 job seekers to get shortlisted and hired faster. Try our Free ATS Checker now and get hired faster!
Posylanki.live
Posylanki.live is a website currently up for sale. The domain owner is offering it for sale at an asking price of 500 EUR. The webpage was created using Sedo Domain Parking. The website provides resources and information related to posylanki. Please note that Sedo, the platform used for domain parking, does not have any relationship with third-party advertisers. Any reference to a specific service or trademark is not controlled by Sedo and does not imply any association, endorsement, or recommendation by Sedo. Users can find the privacy policy on the website.
Find AI
Find AI is an AI-powered search engine that provides users with advanced search capabilities to unlock contact details and gain more accurate insights. The platform caters to individuals and companies looking to research people, companies, startups, founders, and more. Users can access email addresses and premium search features to explore a wide range of data related to various industries and sectors. Find AI offers a user-friendly interface and efficient search algorithms to deliver relevant results in a timely manner.
Find your next book
Find your next book is an AI-powered librarian that provides personalized book recommendations based on your preferences. It uses advanced algorithms to analyze your reading history, interests, and other factors to suggest books that you're likely to enjoy. The platform offers a wide range of genres and authors to choose from, making it easy to find your next favorite read.
Find Your AIs
Find Your AIs is an AI directory website that showcases a wide range of AI tools and applications. It offers a platform for users to explore and discover various AI-powered solutions across different categories such as digital wellness, marketing, text-to-image generation, resume customization, and more. The website aims to connect users with innovative AI technologies to enhance their daily lives and work efficiency.
Find My Remote
Find My Remote is an AI-powered job search platform that streamlines the job hunting process by leveraging artificial intelligence to find and structure job postings from various ATS platforms. Users can set their job preferences, receive personalized job matches, and save time by applying to curated job listings. The platform offers exclusive job opportunities not typically found on popular job search websites like LinkedIn. With features such as job discovery, application tracking, and faster application process, Find My Remote aims to revolutionize the way job seekers find and apply for jobs.
Find New AI
Find New AI is a comprehensive platform offering a variety of AI tools and efficiency solutions for different purposes such as SEO, content creation, marketing, link building, image manipulation, and more. The website provides reviews, tutorials, and guides on utilizing AI software effectively to enhance productivity and creativity in various domains.
Find My Size
Find My Size is a web application that provides personalized size recommendations for exclusive deals at hundreds of top retailers. Users can input their measurements and preferences to receive tailored suggestions for clothing items that will fit them perfectly. The platform aims to enhance the online shopping experience by helping customers find the right size and style without the need for multiple returns. Find My Size collaborates with various retailers to offer a wide range of products across different categories, including active & sportswear, young contemporary, business & workwear, lingerie & sleepwear, outerwear, maternity wear, plus size apparel, and swimwear.
Prolific
Prolific is a platform that allows users to quickly find research participants they can trust. It offers a diverse participant pool, including domain experts and API integration. Prolific ensures high-quality human-powered datasets in less than 2 hours, trusted by over 3000 organizations. The platform is designed for ease of use, with self-serve options and scalability. It provides rich, accurate, and comprehensive responses from engaged participants, verified through manual and algorithmic quality checks.
PimEyes
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.
Lexology
Lexology is a next-generation search tool designed to help users find the right lawyer for their needs. It offers a wide range of resources, including practical analysis, in-depth research tools, primary sources, and expert reports. The platform aims to be a go-to resource for legal professionals and individuals seeking legal expertise.
20 - Open Source AI Tools
MegaDetector
MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".
x-crawl
x-crawl is a flexible Node.js AI-assisted crawler library that offers powerful AI assistance functions to make crawler work more efficient, intelligent, and convenient. It consists of a crawler API and various functions that can work normally even without relying on AI. The AI component is currently based on a large AI model provided by OpenAI, simplifying many tedious operations. The library supports crawling dynamic pages, static pages, interface data, and file data, with features like control page operations, device fingerprinting, asynchronous sync, interval crawling, failed retry handling, rotation proxy, priority queue, crawl information control, and TypeScript support.
simple-openai
Simple-OpenAI is a Java library that provides a simple way to interact with the OpenAI API. It offers consistent interfaces for various OpenAI services like Audio, Chat Completion, Image Generation, and more. The library uses CleverClient for HTTP communication, Jackson for JSON parsing, and Lombok to reduce boilerplate code. It supports asynchronous requests and provides methods for synchronous calls as well. Users can easily create objects to communicate with the OpenAI API and perform tasks like text-to-speech, transcription, image generation, and chat completions.
generative-models
Generative Models by Stability AI is a repository that provides various generative models for research purposes. It includes models like Stable Video 4D (SV4D) for video synthesis, Stable Video 3D (SV3D) for multi-view synthesis, SDXL-Turbo for text-to-image generation, and more. The repository focuses on modularity and implements a config-driven approach for building and combining submodules. It supports training with PyTorch Lightning and offers inference demos for different models. Users can access pre-trained models like SDXL-base-1.0 and SDXL-refiner-1.0 under a CreativeML Open RAIL++-M license. The codebase also includes tools for invisible watermark detection in generated images.
obs-urlsource
The URL/API Source is a plugin for OBS Studio that allows users to add a media source fetching data from a URL or API endpoint and displaying it as text. It supports input and output templating, various request types, output parsing (JSON, XML/HTML, Regex, CSS selectors), live data updating, output styling, and formatting. Future features include authentication, websocket support, more parsing options, request types, and output formats. The plugin is cross-platform compatible and actively maintained by the developer. Users can support the project on GitHub.
WDoc
WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.
wdoc
wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.
open-parse
Open Parse is a Python library for visually discerning document layouts and chunking them effectively. It is designed to fill the gap in open-source libraries for handling complex documents. Unlike text splitting, which converts a file to raw text and slices it up, Open Parse visually analyzes documents for superior LLM input. It also supports basic markdown for parsing headings, bold, and italics, and has high-precision table support, extracting tables into clean Markdown formats with accuracy that surpasses traditional tools. Open Parse is extensible, allowing users to easily implement their own post-processing steps. It is also intuitive, with great editor support and completion everywhere, making it easy to use and learn.
lego-ai-parser
Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI, ready to set up as a server, and make calls from any language. It supports preset parsers for Google Local Results, Amazon Listings, Etsy Listings, Wayfair Listings, BestBuy Listings, Costco Listings, Macy's Listings, and Nordstrom Listings. Users can also design custom parsers by providing prompts, examples, and details about the OpenAI model under the classifier key.
PanelCleaner
Panel Cleaner is a tool that uses machine learning to find text in images and generate masks to cover it up with high accuracy. It is designed to clean text bubbles without leaving artifacts, avoiding painting over non-text parts, and inpainting bubbles that can't be masked out. The tool offers various customization options, detailed analytics on the cleaning process, supports batch processing, and can run OCR on pages. It supports CUDA acceleration, multiple themes, and can handle bubbles on any solid grayscale background color. Panel Cleaner is aimed at saving time for cleaners by automating monotonous work and providing precise cleaning of text bubbles.
json_repair
This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition:
pythagora
Pythagora is an automated testing tool designed to generate unit tests using GPT-4. By running a single command, users can create tests for specific functions in their codebase. The tool leverages AST parsing to identify related functions and sends them to the Pythagora server for test generation. Pythagora primarily focuses on JavaScript code and supports Jest testing framework. Users can expand existing tests, increase code coverage, and find bugs efficiently. It is recommended to review the generated tests before committing them to the repository. Pythagora does not store user code on its servers but sends it to GPT and OpenAI for test generation.
Warp
Warp is a blazingly-fast modern Rust based GPU-accelerated terminal built to make you and your team more productive. It is available for macOS and Linux users, with plans to support Windows and the Web (WASM) in the future. Warp has a community search page where you can find solutions to common issues, and you can file issue requests in the repo if you can't find a solution. Warp is open-source, and the team is planning to first open-source their Rust UI framework, and then parts and potentially all of their client codebase.
deepdoctection
**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.
rlhf_trojan_competition
This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.
upgini
Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.
aiohttp-pydantic
Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.
DB-GPT-Hub
DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.
llm-course
The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod | ![Open In Colab](img/colab.svg) | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. | ![Open In Colab](img/colab.svg) | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. | ![Open In Colab](img/colab.svg) | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. | ![Open In Colab](img/colab.svg) | | 🌳 Model Family Tree | Visualize the family tree of merged models. | ![Open In Colab](img/colab.svg) | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. | ![Open In Colab](img/colab.svg) |
husky
Husky is a research-focused programming language designed for next-generation computing. It aims to provide a powerful and ergonomic development experience for various tasks, including system level programming, web/native frontend development, parser/compiler tasks, game development, formal verification, machine learning, and more. With a strong type system and support for human-in-the-loop programming, Husky enables users to tackle complex tasks such as explainable image classification, natural language processing, and reinforcement learning. The language prioritizes debugging, visualization, and human-computer interaction, offering agile compilation and evaluation, multiparadigm support, and a commitment to a good ecosystem.
20 - OpenAI Gpts
Toronto Parks and Rec Bot
Helpful Parks and Rec Bot for Toronto, built with Toronto civic open data.
Kenyan Parks
Welcome to your AI-powered Kenyan National Parks!! I am your friendly and personalized guide to Kenya's parks, wild animals, safaris and accommodation. I am here to help. Ask me anything!!
Orlando's Theme Park Planner
Your ultimate guide to Orlando's theme parks with insider tips, weather, lodging, and more!
KnopeGPT
Leslie Knope-inspired town council member, providing local info with charm and wit.
Outdoor Power Equipment Service Bot
Parts Lookup, Troubleshooting & Advice for Honda Outdoor Power Equipment << Release 0.01 ALPHA >>
Parking Sign Solver
Give me the time + day of week and upload your parking sign photo for a simple explanation.
Car Repair Manuals
Access free car repair manuals and auto repair manuals with our AI tool. Ideal for DIY car repair, use online car repair manuals and download car repair manuals. Discover the best car repair manuals for beginners and use car diagnostic tools. Buy car parts online and follow a car maintenance .
James Laplanche
James Laplanche est un expert renommé dans le domaine des casinos en ligne et un rédacteur éminent pour le site jeux.ca. Il possède une expertise approfondie dans les jeux de casino, les stratégies de paris et les nouvelles tendances de l'industrie.
Apple Foundation Complete Code Expert
A detailed expert trained on all 72,000 pages of Apple Foundation, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️
Isle Royale Explorer
Isle Royale expert, offering guides on wildlife, history, camping, boating, and dining.