Best AI tools for< Lighten The Mood >

Tinder Ice Breakers AI is an AI application that provides conversation starters designed by AI to help users initiate engaging conversations on the Tinder dating platform. The tool generates funny English ice breakers to spark interesting interactions between users. With a collection of witty and creative prompts, users can break the ice and make meaningful connections with potential matches.

Nepo Baby is a fun and interactive website where users can type a celebrity's name and get humorous results. The website generates funny and entertaining content related to the input celebrity's name, providing users with a light-hearted and enjoyable experience. Users can explore various celebrity names and see the creative outputs that Nepo Baby produces based on those inputs.

Intercom is a customer relationship management (CRM) platform that helps businesses build relationships with their customers through personalized messaging, automated workflows, and a powerful help desk. With Intercom, businesses can:

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Leafer UI is a colorful UI drawing framework developed based on Leafer, which can be used to combine AI drawing and generate interfaces. It provides commonly used UI drawing components and out-of-the-box functions, which is convenient for data exchange with products such as Figma and Sketch, and provides unified and rich interactive events for cross-platform development, such as drag, rotate, and zoom gestures. 1.0.0-rc.21 has been released 🎉🎉🎉, check the changelog. At present, the product has gradually stabilized, and the official version is coming soon. Thanks to all the friends who participated~ If you want to start using it right away, please check the quick installation. If you have any questions or suggestions, you can submit them here or join the technical exchange group. If you only need drawing functions, the lighter leafer-draw (46KB min+gzip) is recommended. 🌟 Remember to go to GitHub / Gitee to light up your little stars ✨ ✨ ✨

MiniCPM-V is a series of end-side multimodal LLMs designed for vision-language understanding. The models take image and text inputs to provide high-quality text outputs. The series includes models like MiniCPM-Llama3-V 2.5 with 8B parameters surpassing proprietary models, and MiniCPM-V 2.0, a lighter model with 2B parameters. The models support over 30 languages, efficient deployment on end-side devices, and have strong OCR capabilities. They achieve state-of-the-art performance on various benchmarks and prevent hallucinations in text generation. The models can process high-resolution images efficiently and support multilingual capabilities.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

LLM for Unity enables seamless integration of Large Language Models (LLMs) within the Unity engine, allowing users to create intelligent characters for immersive player interactions. The tool supports major LLM models, runs locally without internet access, offers fast inference on CPU and GPU, and is easy to set up with a single line of code. It is free for both personal and commercial use, tested on Unity 2021 LTS, 2022 LTS, and 2023. Users can build multiple AI characters efficiently, use remote servers for processing, and customize model settings for text generation.

ABigSurveyOfLLMs is a repository that compiles surveys on Large Language Models (LLMs) to provide a comprehensive overview of the field. It includes surveys on various aspects of LLMs such as transformers, alignment, prompt learning, data management, evaluation, societal issues, safety, misinformation, attributes of LLMs, efficient LLMs, learning methods for LLMs, multimodal LLMs, knowledge-based LLMs, extension of LLMs, LLMs applications, and more. The repository aims to help individuals quickly understand the advancements and challenges in the field of LLMs through a collection of recent surveys and research papers.

Prometheus-Eval is a repository dedicated to evaluating large language models (LLMs) in generation tasks. It provides state-of-the-art language models like Prometheus 2 (7B & 8x7B) for assessing in pairwise ranking formats and achieving high correlation scores with benchmarks. The repository includes tools for training, evaluating, and using these models, along with scripts for fine-tuning on custom datasets. Prometheus aims to address issues like fairness, controllability, and affordability in evaluations by simulating human judgments and proprietary LM-based assessments.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

Aider is a command-line tool that lets you pair program with GPT-3.5/GPT-4 to edit code stored in your local git repository. Aider will directly edit the code in your local source files and git commit the changes with sensible commit messages. You can start a new project or work with an existing git repo. Aider is unique in that it lets you ask for changes to pre-existing, larger codebases.

LLM-baselines is a modular codebase to experiment with transformers, inspired from NanoGPT. It provides a quick and easy way to train and evaluate transformer models on a variety of datasets. The codebase is well-documented and easy to use, making it a great resource for researchers and practitioners alike.

Dot is a standalone, open-source application designed for seamless interaction with documents and files using local LLMs and Retrieval Augmented Generation (RAG). It is inspired by solutions like Nvidia's Chat with RTX, providing a user-friendly interface for those without a programming background. Pre-packaged with Mistral 7B, Dot ensures accessibility and simplicity right out of the box. Dot allows you to load multiple documents into an LLM and interact with them in a fully local environment. Supported document types include PDF, DOCX, PPTX, XLSX, and Markdown. Users can also engage with Big Dot for inquiries not directly related to their documents, similar to interacting with ChatGPT. Built with Electron JS, Dot encapsulates a comprehensive Python environment that includes all necessary libraries. The application leverages libraries such as FAISS for creating local vector stores, Langchain, llama.cpp & Huggingface for setting up conversation chains, and additional tools for document management and interaction.

TTS Generation WebUI is a comprehensive tool that provides a user-friendly interface for text-to-speech and voice cloning tasks. It integrates various AI models such as Bark, MusicGen, AudioGen, Tortoise, RVC, Vocos, Demucs, SeamlessM4T, and MAGNeT. The tool offers one-click installers, Google Colab demo, videos for guidance, and extra voices for Bark. Users can generate audio outputs, manage models, caches, and system space for AI projects. The project is open-source and emphasizes ethical and responsible use of AI technology.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

FluidFrames.RIFE is a Windows app powered by RIFE AI to create frame-generated and slowmotion videos. It is written in Python and utilizes external packages such as torch, onnxruntime-directml, customtkinter, OpenCV, moviepy, and Nuitka. The app features an elegant GUI, video frame generation at different speeds, video slow motion, video resizing, multiple GPU support, and compatibility with various video formats. Future versions aim to support different GPU types, enhance the GUI, include audio processing, optimize video processing speed, and introduce new features like saving AI-generated frames and supporting different RIFE AI models.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.

KaTrain is a tool designed for analyzing games and playing go with AI feedback from KataGo. Users can review their games to find costly moves, play against AI with immediate feedback, play against weakened AI versions, and generate focused SGF reviews. The tool provides various features such as previews, tutorials, installation instructions, and configuration options for KataGo. Users can play against AI, receive instant feedback on moves, explore variations, and request in-depth analysis. KaTrain also supports distributed training for contributing to KataGo's strength and training bigger models. The tool offers themes customization, FAQ section, and opportunities for support and contribution through GitHub issues and Discord community.

Aider is an AI pair programming tool that allows users to collaborate with large language models (LLMs) to edit code in their local git repository. It works best with GPT-4o & Claude 3.5 Sonnet and can connect to almost any LLM. Users can run Aider with specific files, request changes, add new features or test cases, describe bugs, refactor code, update docs, and more. Aider automatically commits changes with sensible messages, supports multiple programming languages, and can handle complex requests by editing multiple files at once. It uses a map of the entire git repo for efficient performance in larger codebases. Users can chat with Aider, add images, URLs, and even code with their voice. Aider has achieved top scores on SWE Bench, solving real GitHub issues from popular open source projects like django, scikitlearn, matplotlib, etc.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

A friendly leprechaun who simply adores limericks.