AI tools for underss
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Undress Photo AI
Undress Photo AI is a free online tool that uses artificial intelligence to generate nude and bikini images from photos. The tool is easy to use and requires no registration. Simply upload a photo and the tool will generate a nude or bikini image in seconds. The tool can be used to create realistic and high-quality nude and bikini images for a variety of purposes, such as art, fashion, and advertising.
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Undress AI Pro
Undress AI Pro is a controversial computer vision application that uses machine learning to remove clothing from images of people. It was based on deep learning and generative adversarial networks (GANs). The technology powering Undress AI and DeepNude was based on deep learning and generative adversarial networks (GANs). GANs involve two neural networks competing against each other - a generator creates synthetic images trying to mimic the training data, while a discriminator tries to distinguish the real images from the generated ones. Through this adversarial process, the generator learns to produce increasingly realistic outputs. For Undress AI, the GAN was trained on a dataset of nude and clothed images, allowing it to "unclothe" people in new images by generating the nudity.
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Undress AI
Undress AI is a free online tool that allows users to create deepnude images. Deepnude images are realistic, nude images of people that are generated using artificial intelligence. The tool is easy to use and does not require any special skills or knowledge. Simply upload an image of a person and the tool will generate a deepnude image of that person.
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Undressing AI
Undressing AI is a website that provides information about artificial intelligence (AI) and its potential impact on society. The site includes articles, videos, and other resources on topics such as the history of AI, the different types of AI, and the ethical implications of AI.
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DDoS-Guard
DDoS-Guard is a web security service that protects websites from distributed denial-of-service (DDoS) attacks. It checks the user's browser before granting access to the website, ensuring a secure browsing experience. The service provides automatic protection against DDoS attacks and ensures the smooth functioning of websites. DDoS-Guard is trusted by many websites to safeguard their online presence and maintain uninterrupted service for their users.
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Scandilytics AI
Scandilytics AI is an AI-driven platform that offers data analytics and automated reporting services for eCommerce businesses. By connecting with your analytics accounts, the AI translates complex data into clear, actionable reports to drive eCommerce success. The platform consists of three AI solutions: Data Analyst AI, Business Analyst AI, and Marketing Agent AI. Scandilytics AI helps businesses optimize KPIs, generate actionable insights, understand customer behavior, ensure data purity, and improve marketing strategies. It provides secure data processing, personalized business advice, and automated actions to drive growth.
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Legalese Decoder
Legalese Decoder is an AI-powered web application designed to translate legal documents into plain English. It utilizes artificial intelligence, natural language processing, and machine learning techniques to analyze legal documents, identify key terms and concepts, and provide definitions and explanations in simpler language. The tool aims to help users, especially non-legal professionals, understand complex legal jargon and agreements more easily, ultimately empowering them to make informed decisions regarding legal matters.
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TLDR
TLDR is an AI-powered IDE plugin that explains code in plain English. It helps developers understand code by providing quick summaries of what a piece of code is doing. The tool supports almost all programming languages and offers a free version for users to try before purchasing. TLDR aims to simplify the understanding of complex code structures and save developers time in comprehending codebases.
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Totoy
Totoy is a Document AI tool that redefines the way documents are processed. Its API allows users to explain, classify, and create knowledge bases from documents without the need for training. The tool supports 19 languages and works with plain text, images, and PDFs. Totoy is ideal for automating workflows, complying with accessibility laws, and creating custom AI assistants for employees or customers.
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Re-View
Re-View is an AI-powered platform that enables users to conduct surveys that capture more than words by utilizing user-friendly video survey forms. The platform allows users to understand emotions, uncover insights, and collect more and better data through authentic emotional connections. With features like automatic insights, efficient research at scale, stunning simplicity, and powerful research capabilities, Re-View offers a practical pricing model that makes research accessible to all. Users can easily create surveys, analyze responses with AI assistance, and gain valuable research reports to support decision-making.
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Aide
Aide is an AI platform designed to enhance customer support operations. It offers a range of features to help businesses gain insights into customer needs, automate support processes, improve agent efficiency, and train AI chatbots. Aide's key capabilities include customer insights, workflow automation, agent assist, and AI chatbots. With Aide, businesses can analyze customer conversations, identify pain points, and automate repetitive tasks to streamline support operations and improve customer satisfaction.
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LangWatch
LangWatch is a monitoring and analytics tool for Generative AI (GenAI) solutions. It provides detailed evaluations of the faithfulness and relevancy of GenAI responses, coupled with user feedback insights. LangWatch is designed for both technical and non-technical users to collaborate and comment on improvements. With LangWatch, you can understand your users, detect issues, and improve your GenAI products.
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MITRE Interpreter
This GPT helps you understand and apply the MITRE ATT&CK Framework, whether you are familiar with the concepts or not.
Concept Explainer
A facilitator for understanding concepts using a simplified Concept Attainment Method.
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IPCC Explainer
A conversational guide to the IPCC report, IPCC Explainer breaks down dense information into understandable insights for public awareness
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CTMU Sage
Bot that guides users in understanding the Cognitive-Theoretic Model of the Universe
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Research Mentor by Dr P.M. Sinclair
A GPT that explains research methods in a language that everyone can easily understand.
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LLaMa2lang
This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.
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Quantus
Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.
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awesome-llm-understanding-mechanism
This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.
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LLM-on-Tabular-Data-Prediction-Table-Understanding-Data-Generation
This repository serves as a comprehensive survey on the application of Large Language Models (LLMs) on tabular data, focusing on tasks such as prediction, data generation, and table understanding. It aims to consolidate recent progress in this field by summarizing key techniques, metrics, datasets, models, and optimization approaches. The survey identifies strengths, limitations, unexplored territories, and gaps in the existing literature, providing insights for future research directions. It also offers code and dataset references to empower readers with the necessary tools and knowledge to address challenges in this rapidly evolving domain.
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ml-road-map
The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.
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LLM-workshop-2024
LLM-workshop-2024 is a tutorial designed for coders interested in understanding the building blocks of large language models (LLMs), how LLMs work, and how to code them from scratch in PyTorch. The tutorial covers topics such as introduction to LLMs, understanding LLM input data, coding LLM architecture, pretraining LLMs, loading pretrained weights, and finetuning LLMs using open-source libraries. Participants will learn to implement a small GPT-like LLM, including data input pipeline, core architecture components, and pretraining code.
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pearai-submodule
PearAI Submodule / Extension is the source code for the bulk of PearAI's functionality, bundled as a VSCode / PearAI extension. It allows users to easily understand code sections, refactor functions, and ask questions by mentioning a file. The tool aims to enhance coding experience and productivity within the VSCode environment.
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RAGLAB
RAGLAB is a modular, research-oriented open-source framework for Retrieval-Augmented Generation (RAG) algorithms. It offers reproductions of 6 existing RAG algorithms and a comprehensive evaluation system with 10 benchmark datasets, enabling fair comparisons between RAG algorithms and easy expansion for efficient development of new algorithms, datasets, and evaluation metrics. The framework supports the entire RAG pipeline, provides advanced algorithm implementations, fair comparison platform, efficient retriever client, versatile generator support, and flexible instruction lab. It also includes features like Interact Mode for quick understanding of algorithms and Evaluation Mode for reproducing paper results and scientific research.
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MMMU
MMMU is a benchmark designed to evaluate multimodal models on college-level subject knowledge tasks, covering 30 subjects and 183 subfields with 11.5K questions. It focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. The evaluation of various models highlights substantial challenges, with room for improvement to stimulate the community towards expert artificial general intelligence (AGI).
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MotionLLM
MotionLLM is a framework for human behavior understanding that leverages Large Language Models (LLMs) to jointly model videos and motion sequences. It provides a unified training strategy, dataset MoVid, and MoVid-Bench for evaluating human behavior comprehension. The framework excels in captioning, spatial-temporal comprehension, and reasoning abilities.
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llm_benchmarks
llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.
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LL3DA
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.
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MMLU-Pro
MMLU-Pro is an enhanced benchmark designed to evaluate language understanding models across broader and more challenging tasks. It integrates more challenging, reasoning-focused questions and increases answer choices per question, significantly raising difficulty. The dataset comprises over 12,000 questions from academic exams and textbooks across 14 diverse domains. Experimental results show a significant drop in accuracy compared to the original MMLU, with greater stability under varying prompts. Models utilizing Chain of Thought reasoning achieved better performance on MMLU-Pro.
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VideoRefer
VideoRefer Suite is a tool designed to enhance the fine-grained spatial-temporal understanding capabilities of Video Large Language Models (Video LLMs). It consists of three primary components: Model (VideoRefer) for perceiving, reasoning, and retrieval for user-defined regions at any specified timestamps, Dataset (VideoRefer-700K) for high-quality object-level video instruction data, and Benchmark (VideoRefer-Bench) to evaluate object-level video understanding capabilities. The tool can understand any object within a video.
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shell-ai
Shell-AI (`shai`) is a CLI utility that enables users to input commands in natural language and receive single-line command suggestions. It leverages natural language understanding and interactive CLI tools to enhance command line interactions. Users can describe tasks in plain English and receive corresponding command suggestions, making it easier to execute commands efficiently. Shell-AI supports cross-platform usage and is compatible with Azure OpenAI deployments, offering a user-friendly and efficient way to interact with the command line.
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ShapeLLM
ShapeLLM is the first 3D Multimodal Large Language Model designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages. It supports single-view colored point cloud input and introduces a robust 3D QA benchmark, 3D MM-Vet, encompassing various variants. The model extends the powerful point encoder architecture, ReCon++, achieving state-of-the-art performance across a range of representation learning tasks. ShapeLLM can be used for tasks such as training, zero-shot understanding, visual grounding, few-shot learning, and zero-shot learning on 3D MM-Vet.
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laragenie
Laragenie is an AI chatbot designed to understand and assist developers with their codebases. It runs on the command line from a Laravel app, helping developers onboard to new projects, understand codebases, and provide daily support. Laragenie accelerates workflow and collaboration by indexing files and directories, allowing users to ask questions and receive AI-generated responses. It supports OpenAI and Pinecone for processing and indexing data, making it a versatile tool for any repo in any language.
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SenseVoice
SenseVoice is a speech foundation model focusing on high-accuracy multilingual speech recognition, speech emotion recognition, and audio event detection. Trained with over 400,000 hours of data, it supports more than 50 languages and excels in emotion recognition and sound event detection. The model offers efficient inference with low latency and convenient finetuning scripts. It can be deployed for service with support for multiple client-side languages. SenseVoice-Small model is open-sourced and provides capabilities for Mandarin, Cantonese, English, Japanese, and Korean. The tool also includes features for natural speech generation and fundamental speech recognition tasks.