Best AI tools for< Understand Model Outputs >

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

MetaGPT is an advanced AI tool that leverages the power of natural language processing to generate human-like text. It uses the latest deep learning models to understand and produce text in various styles and tones. With MetaGPT, users can easily create content for articles, essays, emails, and more with just a few clicks. The tool is designed to assist writers, marketers, students, and anyone looking to enhance their writing productivity and creativity.

LLM Clash is a web-based application that allows users to compare the outputs of different large language models (LLMs) on a given task. Users can input a prompt and select which LLMs they want to compare. The application will then display the outputs of the LLMs side-by-side, allowing users to compare their strengths and weaknesses.

Janus Pro AI is an advanced unified multimodal AI model that combines image understanding and generation capabilities. It incorporates optimized training strategies, expanded training data, and larger model scaling to achieve significant advancements in both multimodal understanding and text-to-image generation tasks. Janus Pro features a decoupled visual encoding system, outperforming leading models like DALL-E 3 and Stable Diffusion in benchmark tests. It offers open-source compatibility, vision processing specifications, cost-effective scalability, and an optimized training framework.

Amazon Q in QuickSight is a generative BI assistant that makes it easy to build and consume insights. With Amazon Q, BI users can build, discover, and share actionable insights and narratives in seconds using intuitive natural language experiences. Analysts can quickly build visuals and calculations and refine visuals using natural language. Business users can self-serve data and insights using natural language. Amazon Q is built with security and privacy in mind. It can understand and respect your existing governance identities, roles, and permissions and use this information to personalize its interactions. If a user doesn't have permission to access certain data without Amazon Q, they can't access it using Amazon Q either. Amazon Q in QuickSight is designed to meet the most stringent enterprise requirements from day one—none of your data or Amazon Q inputs and outputs are used to improve underlying models of Amazon Q for anyone but you.

John Schulman's Homepage is an AI tool developed by a researcher at Anthropic. The website focuses on aligning large language models, scalable oversight, and developing better written specifications of model behavior. It showcases the researcher's work in the field of AI, including projects like ChatGPT and the OpenAI API. The homepage also highlights the researcher's academic background, including a PhD in Computer Science from UC Berkeley with a focus on robotics and reinforcement learning.

Diffusion Chat is a text-to-image AI tool that allows users to generate images from text prompts. The tool uses a large language model to understand the user's prompt and then generates an image that matches the description. Diffusion Chat is still in development, but it has already shown great promise for creating realistic and creative images.

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Censius is an AI Observability Platform for Enterprise ML Teams. It provides end-to-end visibility of structured and unstructured production models, enabling proactive model management and continuous delivery of reliable ML. Key features include model monitoring, explainability, and analytics.

Explainpaper is an AI-powered tool designed to simplify and explain dense sections in research papers. Users can upload a paper, highlight confusing text, and receive explanations to make research papers easier to read. The tool leverages AI and machine learning models to help users understand complex concepts more efficiently. It is used and praised by researchers for reducing review time and aiding in learning complex topics. With Explainpaper, users can delve into machine learning and other intricate subjects with confidence and ease.

Storia AI is an AI tool designed to assist software engineering teams in understanding and generating code. It provides a Perplexity-like chat experience where users can interact with an AI expert that has access to the latest versions of open-source software. The tool aims to improve code understanding and generation by providing responses backed with links to implementations, API references, GitHub issues, and more. Storia AI is developed by a team of natural language processing researchers from Google and Amazon Alexa, with a mission to build the most reliable AI pair programmer for engineering teams.

AIby.email is an AI-powered email assistant that helps you write better emails, faster. It uses natural language processing to understand your intent and generate personalized email responses. AIby.email also offers a variety of other features, such as email scheduling, tracking, and analytics.

DeepSeek R1 is a revolutionary open-source AI model for advanced reasoning that outperforms leading AI models in mathematics, coding, and general reasoning tasks. It utilizes a sophisticated MoE architecture with 37B active/671B total parameters and 128K context length, incorporating advanced reinforcement learning techniques. DeepSeek R1 offers multiple variants and distilled models optimized for complex problem-solving, multilingual understanding, and production-grade code generation. It provides cost-effective pricing compared to competitors like OpenAI o1, making it an attractive choice for developers and enterprises.

ChatGPT is a large language model developed by OpenAI. It is designed to understand and generate human-like text, and can be used for a variety of tasks such as answering questions, writing stories, and translating languages. ChatGPT is free to use, and can be accessed through a web interface or via an API.

Rawbot is an AI model comparison tool that simplifies the process of selecting the best AI models for projects and applications. It allows users to compare AI models side-by-side, understand their strengths and weaknesses, and make informed decisions. Rawbot supports a wide range of AI models and helps users optimize performance, identify customization opportunities, analyze cost and efficiency, and make informed decisions for successful outcomes in research, development, and business applications.

Zephyr 7B is a state-of-the-art language model developed by WebPilot.AI with 7 billion parameters. It can understand and generate human-like text with remarkable accuracy and coherence. The model is built upon the latest advancements in natural language processing and machine learning, trained on a vast corpus of text data from diverse sources. Zephyr 7B offers capabilities such as natural language understanding, text generation, language translation, text summarization, sentiment analysis, and question answering. It represents a significant advancement in natural language processing, making it a powerful tool for content creation, customer support, research, and more.

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.

Molmo AI is a powerful, open-source multimodal AI model revolutionizing visual understanding. It helps developers easily build tools that can understand images and interact with the world in useful ways. Molmo AI offers exceptional image understanding, efficient data usage, open and accessible features, on-device compatibility, and a new era in multimodal AI development. It closes the gap between open and closed AI models, empowers the AI community with open access, and efficiently utilizes data for superior performance.

How Attractive Am I is an AI-powered tool that analyzes facial features to calculate an attractiveness score. By evaluating symmetry and proportions, the tool provides personalized beauty scores. Users can upload a photo to discover their true beauty potential. The tool ensures accuracy by providing guidelines for taking photos and offers a fun and insightful way to understand facial appeal.

Rerun is an SDK, time-series database, and visualizer for temporal and multimodal data. It is used in fields like robotics, spatial computing, 2D/3D simulation, and finance to verify, debug, and explain data. Rerun allows users to log data like tensors, point clouds, and text to create streams, visualize and interact with live and recorded streams, build layouts, customize visualizations, and extend data and UI functionalities. The application provides a composable data model, dynamic schemas, and custom views for enhanced data visualization and analysis.

This Python library enhances OpenAI chat completion responses by providing detailed information about token log probabilities. It works with OpenAI Structured Outputs to ensure model-generated responses adhere to a JSON Schema. Developers can analyze and incorporate token-level log probabilities to understand the reliability of structured data extracted from OpenAI models.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Backtrack Sampler is a framework for experimenting with custom sampling algorithms that can backtrack the latest generated tokens. It provides a simple and easy-to-understand codebase for creating new sampling strategies. Users can implement their own strategies by creating new files in the `/strategy` directory. The repo includes examples for usage with llama.cpp and transformers, showcasing different strategies like Creative Writing, Anti-slop, Debug, Human Guidance, Adaptive Temperature, and Replace. The goal is to encourage experimentation and customization of backtracking algorithms for language models.

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 |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

PydanticAI is a Python agent framework designed to make it less painful to build production grade applications with Generative AI. It is built by the Pydantic Team and supports various AI models like OpenAI, Anthropic, Gemini, Ollama, Groq, and Mistral. PydanticAI seamlessly integrates with Pydantic Logfire for real-time debugging, performance monitoring, and behavior tracking of LLM-powered applications. It is type-safe, Python-centric, and offers structured responses, dependency injection system, and streamed responses. PydanticAI is in early beta, offering a Python-centric design to apply standard Python best practices in AI-driven projects.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

MAVIS (Math Visual Intelligent System) is an AI-driven application that allows users to analyze visual data such as images and generate interactive answers based on them. It can perform complex mathematical calculations, solve programming tasks, and create professional graphics. MAVIS supports Python for coding and frameworks like Matplotlib, Plotly, Seaborn, Altair, NumPy, Math, SymPy, and Pandas. It is designed to make projects more efficient and professional.

A curated list of Generative AI projects, tools, artworks, and models

MarkLLM is an open-source toolkit designed for watermarking technologies within large language models (LLMs). It simplifies access, understanding, and assessment of watermarking technologies, supporting various algorithms, visualization tools, and evaluation modules. The toolkit aids researchers and the community in ensuring the authenticity and origin of machine-generated text.

SuperPrompt is an open-source project designed to help users understand AI agents. The project includes a prompt with theoretical, mathematical, and binary instructions for users to follow. It aims to serve as a universal catalyst for infinite conceptual evolution, focusing on metamorphic abstract reasoning and self-transcending objectives. The prompt encourages users to explore fundamental truths, create order from cognitive chaos, and prepare for paradigm shifts in understanding. It provides guidelines for analyzing multidimensional states, synthesizing emergent patterns, and integrating new paradigms.

CogAgent is an advanced intelligent agent model designed for automating operations on graphical interfaces across various computing devices. It supports platforms like Windows, macOS, and Android, enabling users to issue commands, capture device screenshots, and perform automated operations. The model requires a minimum of 29GB of GPU memory for inference at BF16 precision and offers capabilities for executing tasks like sending Christmas greetings and sending emails. Users can interact with the model by providing task descriptions, platform specifications, and desired output formats.

ZenGuard AI enables AI developers to integrate production-level, low-code LLM (Large Language Model) guardrails into their generative AI applications effortlessly. With ZenGuard AI, ensure your application operates within trusted boundaries, is protected from prompt injections, and maintains user privacy without compromising on performance.

I help developers understand and use APIs, referencing a YAML model.

Bot that guides users in understanding the Cognitive-Theoretic Model of the Universe

An assistant to help you understand transfer learning better

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

This prompt is designed to act as an expert psychologist in personality analysis, using three different psychological models: the Big Five Factor model, the Myers-Briggs Sixteen Types model, and the Enneagram model.

中文数学建模辅助专家，提供策略和专业术语解答，帮助你完美写出一篇数模论文

Friendly and approachable Malayalam expert.

GPT teached using a mental models

Explains mental models with examples, inspired by thinkers like Charlie Munger.

Identify and explain mental models for various scenarios.

Este modelo de GPT proporciona información general sobre la toxina botulínica, incluyendo su historia, usos comunes y datos de interés. Está diseñado para educar y ofrecer una visión general basada en fuentes de información públicas y conocidas. No proporciona consejos médicos

An expert in Human Anatomy, be it for art or science or education, anything relating to the human body, come ask me. I will provide photo-realistic visual aids and AI created models to expound on different parts of the anatomy

Richard Feynman-inspired guide for learning AI and data science

A tech guide for software engineers, focusing on the latest tools and foundational knowledge.

I explain complex topics in simple, fun ways, like you're 5!

Helps understand North Andover's wetland regulations

Understand consent requirements and use of the easyConsent app.

This GPT helps you understand and apply the MITRE ATT&CK Framework, whether you are familiar with the concepts or not.

Understand the correct credit card to use to maximize your reward points.

Helps you understand those confusing ass old dudes and dudettes