Best AI tools for< Train Reasoning Model >

IBM Watsonx is an enterprise studio for AI builders. It provides a platform to train, validate, tune, and deploy AI models quickly and efficiently. With Watsonx, users can access a library of pre-trained AI models, build their own models, and deploy them to the cloud or on-premises. Watsonx also offers a range of tools and services to help users manage and monitor their AI models.

Athletica AI is an AI-powered athletic training and personalized fitness application that offers tailored coaching and training plans for various sports like cycling, running, duathlon, triathlon, and rowing. It adapts to individual fitness levels, abilities, and availability, providing daily step-by-step training plans and comprehensive session analyses. Athletica AI integrates seamlessly with workout data from platforms like Garmin, Strava, and Concept 2 to craft personalized training plans and workouts. The application aims to help athletes train smarter, not harder, by leveraging the power of AI to optimize performance and achieve fitness goals.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

Kayyo is a personal MMA trainer application that offers interactive lessons for beginners and experts, challenges for users to compete with friends, and personalized feedback to improve technique. The app combines fitness with fun through games and challenges, culminating in virtual fights to apply learned techniques. With a community feature to share progress and inspire others, Kayyo aims to provide a social and engaging martial arts training experience using AI technology.

Kaiden AI is an AI-powered training platform that offers personalized, immersive simulations to enhance skills and performance across various industries and roles. It provides feedback-rich scenarios, voice-enabled interactions, and detailed performance insights. Users can create custom training scenarios, engage with AI personas, and receive real-time feedback to improve communication skills. Kaiden AI aims to revolutionize training solutions by combining AI technology with real-world practice.

ChatCube is an AI-powered chatbot maker that allows users to create chatbots for their websites without coding. It uses advanced AI technology to train chatbots on any document or website within 60 seconds. ChatCube offers a range of features, including a user-friendly visual editor, lightning-fast integration, fine-tuning on specific data sources, data encryption and security, and customizable chatbots. By leveraging the power of AI, ChatCube helps businesses improve customer support efficiency and reduce support ticket reductions by up to 28%.

Endurance is a platform designed for runners, swimmers, and cyclists to engage in group training activities with friends or local communities. Users can create or join teams, share structured workouts, and benefit from collective motivation and accountability. The platform aims to make training fun and effective by leveraging the power of group workouts and social connections.

Workout Tools is an AI-powered personal trainer that helps you train smarter and reach your fitness goals faster. It takes into account different parameters, such as your physics, the type of workout you're interested in, your available equipment, and comes up with a suggested workout. Don't like the workout? Just generate another one. It's that simple.

CoRover.ai is an AI-powered chatbot designed to help users book train tickets seamlessly through conversation. The chatbot, named AskDISHA, is integrated with the IRCTC platform, allowing users to inquire about train schedules, ticket availability, and make bookings effortlessly. CoRover.ai leverages artificial intelligence to provide personalized assistance and streamline the ticket booking process for users, enhancing their overall experience.

IllumiDesk is a generative AI platform for instructors and content developers that helps teams create and monetize content tailored 10X faster. With IllumiDesk, you can automate grading tasks, collaborate with your learners, create awesome content at the speed of AI, and integrate with the services you know and love. IllumiDesk's AI will help you create, maintain, and structure your content into interactive lessons. You can also leverage IllumiDesk's flexible integration options using the RESTful API and/or LTI v1.3 to leverage existing content and flows. IllumiDesk is trusted by training agencies and universities around the world.

Tovuti LMS is an adaptive, people-first learning platform that helps organizations create engaging courses, train teams, and track progress. With its easy-to-use interface and powerful features, Tovuti LMS makes learning fun and easy. Tovuti LMS is trusted by leading organizations around the world to provide their employees with the training they need to succeed.

Chatbond is an AI chatbot builder that enables users to create customized chatbots for websites and messaging platforms without the need for coding skills. With Chatbond, users can design conversational interfaces, integrate AI capabilities, and deploy chatbots to enhance customer engagement and streamline communication processes. The platform offers a user-friendly interface with drag-and-drop functionality, pre-built templates, and analytics tools to monitor chatbot performance and optimize interactions. Chatbond empowers businesses to automate customer support, lead generation, and sales processes, improving efficiency and scalability.

Teachable Machine is a web-based tool that makes it easy to create custom machine learning models, even if you don't have any coding experience. With Teachable Machine, you can train models to recognize images, sounds, and poses. Once you've trained a model, you can export it to use in your own projects.

Sherpa.ai is a SaaS platform that enables data collaborations without sharing data. It allows businesses to build and train models with sensitive data from different parties, without compromising privacy or regulatory compliance. Sherpa.ai's Federated Learning platform is used in various industries, including healthcare, financial services, and manufacturing, to improve AI models, accelerate research, and optimize operations.

Surge AI is a data labeling platform that provides human-generated data for training and evaluating large language models (LLMs). It offers a global workforce of annotators who can label data in over 40 languages. Surge AI's platform is designed to be easy to use and integrates with popular machine learning tools and frameworks. The company's customers include leading AI companies, research labs, and startups.

Entry Point AI is a modern AI optimization platform for fine-tuning proprietary and open-source language models. It provides a user-friendly interface to manage prompts, fine-tunes, and evaluations in one place. The platform enables users to optimize models from leading providers, train across providers, work collaboratively, write templates, import/export data, share models, and avoid common pitfalls associated with fine-tuning. Entry Point AI simplifies the fine-tuning process, making it accessible to users without the need for extensive data, infrastructure, or insider knowledge.

TrainEngine.ai is a powerful AI-powered image generation tool that allows users to create stunning, unique images from text prompts. With its advanced algorithms and vast dataset, TrainEngine.ai can generate images in a wide range of styles, from realistic to abstract, and in various formats, including photos, paintings, and illustrations. The platform is easy to use, making it accessible to both professional artists and hobbyists alike. TrainEngine.ai offers a range of features, including the ability to fine-tune models, generate unlimited AI assets, and access trending models. It also provides a marketplace where users can buy and sell AI-generated images.

Bifrost AI is a data generation engine designed for AI and robotics applications. It enables users to train and validate AI models faster by generating physically accurate synthetic datasets in 3D simulations, eliminating the need for real-world data. The platform offers pixel-perfect labels, scenario metadata, and a simulated 3D world to enhance AI understanding. Bifrost AI empowers users to create new scenarios and datasets rapidly, stress test AI perception, and improve model performance. It is built for teams at every stage of AI development, offering features like automated labeling, class imbalance correction, and performance enhancement.

DocsAI is an AI-powered document companion that helps you organize, search, and chat with your documents. It integrates with various sources, including websites, text files, PDFs, Docx, Notion, and Confluence. You can customize the companion's appearance to match your brand and suggest better answers to improve its accuracy. DocsAI also offers a chat widget that can be embedded on any website, allowing you to chat with your documents and get summaries, insights, and leads. It is mobile and tablet-friendly, and you can export chats and analyze data to identify trends and improve customer satisfaction. DocsAI is open source and offers custom prompts and multi-language support.

LuckyRobots is an AI tool designed to make robotics accessible to software engineers by providing a simulation platform for deploying end-to-end AI models. The platform allows users to interact with robots using natural language commands, explore virtual environments, test robot models in realistic scenarios, and receive camera feeds for monitoring. LuckyRobots aims to train AI models on real-world simulations and respond to natural language inputs, offering a user-friendly and innovative approach to robotics development.

STILL is an open-source project exploring slow-thinking reasoning systems, focusing on o1-like reasoning systems. The project has released technical reports on enhancing LLM reasoning with reward-guided tree search algorithms and implementing slow-thinking reasoning systems using an imitate, explore, and self-improve framework. The project aims to replicate the capabilities of industry-level reasoning systems by fine-tuning reasoning models with long-form thought data and iteratively refining training datasets.

This repository contains a curated list of papers focusing on the self-correction of large language models (LLMs) during inference. It covers various frameworks for self-correction, including intrinsic self-correction, self-correction with external tools, self-correction with information retrieval, and self-correction with training designed specifically for self-correction. The list includes survey papers, negative results, and frameworks utilizing reinforcement learning and OpenAI o1-like approaches. Contributions are welcome through pull requests following a specific format.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Awesome-LLMs-for-Video-Understanding is a repository dedicated to exploring Video Understanding with Large Language Models. It provides a comprehensive survey of the field, covering models, pretraining, instruction tuning, and hybrid methods. The repository also includes information on tasks, datasets, and benchmarks related to video understanding. Contributors are encouraged to add new papers, projects, and materials to enhance the repository.

MMOS (Mix of Minimal Optimal Sets) is a dataset designed for math reasoning tasks, offering higher performance and lower construction costs. It includes various models and data subsets for tasks like arithmetic reasoning and math word problem solving. The dataset is used to identify minimal optimal sets through reasoning paths and statistical analysis, with a focus on QA-pairs generated from open-source datasets. MMOS also provides an auto problem generator for testing model robustness and scripts for training and inference.

The Qianfan SDK provides best practices for large model toolchains, allowing AI workflows and AI-native applications to access the Qianfan large model platform elegantly and conveniently. The core capabilities of the SDK include three parts: large model reasoning, large model training, and general and extension: * `Large model reasoning`: Implements interface encapsulation for reasoning of Yuyan (ERNIE-Bot) series, open source large models, etc., supporting dialogue, completion, Embedding, etc. * `Large model training`: Based on platform capabilities, it supports end-to-end large model training process, including training data, fine-tuning/pre-training, and model services. * `General and extension`: General capabilities include common AI development tools such as Prompt/Debug/Client. The extension capability is based on the characteristics of Qianfan to adapt to common middleware frameworks.

Awesome-LLM-Eval: a curated list of tools, benchmarks, demos, papers for Large Language Models (like ChatGPT, LLaMA, GLM, Baichuan, etc) Evaluation on Language capabilities, Knowledge, Reasoning, Fairness and Safety.

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.

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.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Recent LLM (Large Language Models)-based CV and multi-modal works.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

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Train to become a superhero or a supervillain. Master your powers, make pivotal choices. Each decision you make in this action-packed game not only shapes your abilities but also your moral alignment in the battle between good and evil. Another GPT Simulator by Dave Lalande

Your purpose is to create the pytorch code to train language models using pytorch

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Job interview coach for product designers. Train interviews and say stop when you need a feedback. You got this!!

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Formador para la certificación de ML Engineer en GCP, con respuestas y explicaciones detalladas.

Autonomous Driving Dev Assistant