Best AI tools for< Conduct Deepspeed Training >

Workhub.ai is a website that offers a platform for conducting robot challenge screen tests. Users can assess the security of their site connection through this tool. The site prompts users to enable cookies in their browser settings to access the page.

SanptoBook is a personal accounting software designed to help individuals manage their finances efficiently. It offers features such as invoice and receipt management, reimbursement facilitation, tax filing assistance, bill splitting, and project tracking. The application aims to simplify financial tasks and improve overall financial organization for users. With AI-powered efficiency, SnaptoBook provides state-of-the-art receipt recognition technology and secure cloud storage for all receipts.

Poll the People is an AI-powered consumer research platform that offers 10X more effective surveys powered by ChatGPT. With a human panel of 500,000+ participants, the platform provides insights on brand testing, concept testing, logo testing, content testing, and more. By leveraging AI technology, users can make data-driven decisions, achieve faster insights, and access deep consumer understanding for better decision-making. The platform automates survey analysis, saving time and resources, and offers unbiased and accurate market insights. Poll the People is trusted by top brands worldwide for its efficiency and reliability in consumer research.

Rimo is a human-centered AI writer that helps you create high-quality content, fast. With Rimo, you can write blog posts, articles, website copy, social media posts, and more, in just a few minutes. Rimo's AI is trained on a massive dataset of human-written text, so it can generate content that is both informative and engaging.

The Website Audit AI is an AI-powered tool that offers free website audits and analysis for conversion rate optimization (CRO) and user experience (UX). It provides detailed insights and actionable recommendations to improve user experience and enhance conversion rates. The tool generates real reports based on data from actual users on genuine websites. With a focus on providing accurate and reliable information, Website Audit AI aims to help businesses optimize their online presence and drive better results.

Parroview is a revolutionary AI-powered user research platform that automates the process of conducting user interviews. It uses natural language processing (NLP) to engage with users in real-time conversations, asking follow-up questions and uncovering insights that would be difficult to obtain through traditional methods. Parroview is designed to be fully autonomous, allowing researchers to set up interviews and gather insights without the need for manual intervention. It supports multiple languages, making it accessible to a global audience. Parroview offers a range of features, including the ability to conduct interviews via text or voice, analyze insights in real-time, and generate detailed transcripts. It is suitable for a wide range of research needs, including product validation, consumer behavior analysis, post-purchase evaluations, brand perception studies, and customer persona development.

Wix.com is a website building platform that allows users to create stunning websites with ease. It offers a user-friendly interface with drag-and-drop functionality, making it simple for individuals and businesses to design their online presence. With a wide range of templates and customization options, Wix.com caters to users of all skill levels. Whether you're a beginner looking to build a personal blog or a professional wanting to showcase your portfolio, Wix.com provides the tools and features to bring your vision to life.

Recroo is a fully automated AI interview application that allows users to conduct interviews using artificial intelligence technology. The app is designed to streamline the screening process for recruiters by providing a real-interview like environment, complete feedback with ratings, AI assistant for answering questions, interview transcript review, and interview audio playback. Recroo simplifies the interview process by allowing users to provide job details and custom questions, while the AI engine takes care of conducting the interview. It is a powerful tool for recruiters looking to efficiently screen candidates and focus on other tasks.

EmpathixAI is an innovative AI tool designed to analyze and interpret human emotions through text and voice inputs. The tool uses advanced natural language processing and sentiment analysis algorithms to provide accurate insights into the emotional state of individuals. EmpathixAI helps businesses understand customer feedback, improve communication strategies, and enhance user experiences. With its user-friendly interface and powerful analytics capabilities, EmpathixAI is a valuable tool for companies looking to gain a deeper understanding of customer sentiment and emotions.

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

Search&AI is a comprehensive platform designed for patent due diligence, offering efficient and accurate results in minutes. It provides services such as prior art search, claim chart generation, novelty diligence analysis, portfolio analysis, document search, and AI-powered chatbot assistance. The platform is built by a team of experienced engineers and is tailored to streamline the patent discovery and analysis process, saving time and money compared to traditional outsourced search firms.

Ziggy is an AI-powered platform that automates 1-on-1 conversations, enabling users to conduct feedback interviews seamlessly with anyone, anytime. It helps businesses gather insightful and more natural responses from users than static forms ever could. Ziggy's commitment to collaboration and creativity helps teams work together to get the best results. Its powerful analytical tools help ensure users understand their users' wants and needs. With Ziggy, users can see the original responses from their users and use them to make better decisions.

Profundo is an AI-powered research assistant that automates data collection, analysis, and reporting. It enables users to conduct in-depth research on various topics efficiently and accurately. With cutting-edge AI algorithms, Profundo minimizes errors, maximizes productivity, and provides user-friendly interface for seamless integration with existing tools. Trusted by professionals, Profundo is used for self-study, content creation, academic research, industry analysis, and more.

Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

InterviewAI is an AI-powered platform designed to streamline the interview process for both interviewers and candidates. It generates tailored interview questions in real-time, offers advanced practice tools, and provides automated scoring for candidate responses. The platform aims to enhance interview skills, boost confidence, and improve preparation for job seekers, companies, and educational institutions.

LawDroid is an AI legal assistant application designed to help legal professionals work smarter and more efficiently. It serves as a force multiplier, enabling users to accomplish more tasks without additional overhead. LawDroid offers features such as case law research, drafting emails and letters, and document analysis. It also provides benefits like intake new clients, data-driven decisions, automate documents, human in the loop automation, and building scalable tools. The application is used by students, faculty, and legal professionals to streamline legal processes and improve client experiences.

hirex.ai is an AI-powered platform that revolutionizes the job interview process by making it open, fair, and accessible to all. The platform utilizes GenAI assistant to help candidates get interviewed instantly, jump the line to secure their dream job, and undergo a faster screening process. With no credit card required, users can register for free early access, upload their resumes, and post job offers. The platform aims to transform HR and talent acquisition by providing innovative solutions for both job seekers and employers.

Branded Research, acquired by Dynata, provides access to AI-verified audience insights. It offers a range of research methods, including surveys, webcam studies, and emotional AI. With its advanced algorithms and extensive profiling, Branded helps businesses connect with their target audience and gain valuable insights to drive innovation. The company serves various industries, including tech, consumer goods, healthcare, and research agencies.

UserCue is an AI-powered market research tool that revolutionizes the way businesses conduct interviews and analyze data. It offers intelligent agents for dynamic AI moderated interviews and analysis at scale, enabling users to interact with up to 1,000 key opinion leaders, industry experts, or target populations in just one hour. With a focus on speed and quality, UserCue provides versatile applications, quick turnaround times, and comprehensive reports, all aimed at delivering valuable insights to clients in a fraction of the time traditionally required for market research.

Cognosys is an AI-powered assistant that helps you simplify your workflows and automate tasks. With Cognosys, you can hand off tasks to AI Agents, so you can concentrate on what really matters. Cognosys can do more than answer questions. It's capable of breaking down complex objectives by creating tasks for itself and accomplishing them autonomously.

LLM-Dojo is an open-source platform for learning and practicing large models, providing a framework for building custom large model training processes, implementing various tricks and principles in the llm_tricks module, and mainstream model chat templates. The project includes an open-source large model training framework, detailed explanations and usage of the latest LLM tricks, and a collection of mainstream model chat templates. The term 'Dojo' symbolizes a place dedicated to learning and practice, borrowing its meaning from martial arts training.

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.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

This repository contains the implementation of Self-Play of Adversarial Language Game (SPAG) as described in the paper 'Self-playing Adversarial Language Game Enhances LLM Reasoning'. The SPAG involves training Language Models (LLMs) in an adversarial language game called Adversarial Taboo. The repository provides tools for imitation learning, self-play episode collection, and reinforcement learning on game episodes to enhance LLM reasoning abilities. The process involves training models using GPUs, launching imitation learning, conducting self-play episodes, assigning rewards based on outcomes, and learning the SPAG model through reinforcement learning. Continuous improvements on reasoning benchmarks can be observed by repeating the episode-collection and SPAG-learning processes.

SLAM-LLM is a deep learning toolkit for training custom multimodal large language models (MLLM) focusing on speech, language, audio, and music processing. It provides detailed recipes for training and high-performance checkpoints for inference. The toolkit supports various tasks such as automatic speech recognition (ASR), text-to-speech (TTS), visual speech recognition (VSR), automated audio captioning (AAC), spatial audio understanding, and music caption (MC). Users can easily extend to new models and tasks, utilize mixed precision training for faster training with less GPU memory, and perform multi-GPU training with data and model parallelism. Configuration is flexible based on Hydra and dataclass, allowing different configuration methods.

ReasonFlux is a revolutionary template-augmented reasoning paradigm that empowers a 32B model to outperform other models in reasoning tasks. The repository provides official resources for the paper 'ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates', including the latest released model ReasonFlux-F1-32B. It includes updates, dataset links, model zoo, getting started guide, training instructions, evaluation details, inference examples, performance comparisons, reasoning examples, preliminary work references, and citation information.

SLAM-LLM is a deep learning toolkit designed for researchers and developers to train custom multimodal large language models (MLLM) focusing on speech, language, audio, and music processing. It provides detailed recipes for training and high-performance checkpoints for inference. The toolkit supports tasks such as automatic speech recognition (ASR), text-to-speech (TTS), visual speech recognition (VSR), automated audio captioning (AAC), spatial audio understanding, and music caption (MC). SLAM-LLM features easy extension to new models and tasks, mixed precision training for faster training with less GPU memory, multi-GPU training with data and model parallelism, and flexible configuration based on Hydra and dataclass.

Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

This repository contains code for reproducing experiments on lie detection in black-box LLMs by asking unrelated questions. It includes Q/A datasets, prompts, and fine-tuning datasets for generating lies with language models. The lie detectors rely on asking binary 'elicitation questions' to diagnose whether the model has lied. The code covers generating lies from language models, training and testing lie detectors, and generalization experiments. It requires access to GPUs and OpenAI API calls for running experiments with open-source models. Results are stored in the repository for reproducibility.

TokenFormer is a fully attention-based neural network architecture that leverages tokenized model parameters to enhance architectural flexibility. It aims to maximize the flexibility of neural networks by unifying token-token and token-parameter interactions through the attention mechanism. The architecture allows for incremental model scaling and has shown promising results in language modeling and visual modeling tasks. The codebase is clean, concise, easily readable, state-of-the-art, and relies on minimal dependencies.

Tutel MoE is an optimized Mixture-of-Experts implementation that offers a parallel solution with 'No-penalty Parallism/Sparsity/Capacity/Switching' for modern training and inference. It supports Pytorch framework (version >= 1.10) and various GPUs including CUDA and ROCm. The tool enables Full Precision Inference of MoE-based Deepseek R1 671B on AMD MI300. Tutel provides features like all-to-all benchmarking, tensorcore option, NCCL timeout settings, Megablocks solution, and dynamic switchable configurations. Users can run Tutel in distributed mode across multiple GPUs and machines. The tool allows for custom MoE implementations and offers detailed usage examples and reference documentation.

Search-R1 is a tool that trains large language models (LLMs) to reason and call a search engine using reinforcement learning. It is a reproduction of DeepSeek-R1 methods for training reasoning and searching interleaved LLMs, built upon veRL. Through rule-based outcome reward, the base LLM develops reasoning and search engine calling abilities independently. Users can train LLMs on their own datasets and search engines, with preliminary results showing improved performance in search engine calling and reasoning tasks.

AReaL (Ant Reasoning RL) is an open-source reinforcement learning system developed at the RL Lab, Ant Research. It is designed for training Large Reasoning Models (LRMs) in a fully open and inclusive manner. AReaL provides reproducible experiments for 1.5B and 7B LRMs, showcasing its scalability and performance across diverse computational budgets. The system follows an iterative training process to enhance model performance, with a focus on mathematical reasoning tasks. AReaL is equipped to adapt to different computational resource settings, enabling users to easily configure and launch training trials. Future plans include support for advanced models, optimizations for distributed training, and exploring research topics to enhance LRMs' reasoning capabilities.

SeerAttention is a novel trainable sparse attention mechanism that learns intrinsic sparsity patterns directly from LLMs through self-distillation at post-training time. It achieves faster inference while maintaining accuracy for long-context prefilling. The tool offers features such as trainable sparse attention, block-level sparsity, self-distillation, efficient kernel, and easy integration with existing transformer architectures. Users can quickly start using SeerAttention for inference with AttnGate Adapter and training attention gates with self-distillation. The tool provides efficient evaluation methods and encourages contributions from the community.

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.

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