QAbot-zh/query-key is a pure front-end API testing tool that supports various API formats such as oneapi/newapi and can also verify OpenAI formatted APIs. The main advantage of this tool lies in its front-end implementation, eliminating concerns about gateway timeouts while ensuring data security. It provides comprehensive test data displays, including response times and model consistency, allowing users to intuitively understand API performance. Additionally, it supports local one-click execution and online hosting via pages, making it convenient for users to deploy and use quickly.

gmft is a toolkit designed to convert tables in PDFs into various formats. It is lightweight, modular, and delivers exceptional performance. gmft relies on Microsoft's Table Transformers, recognized as one of the best-performing and most reliable solutions among many alternatives. It operates without the need for a GPU, offering high throughput and easy installation, requiring only a single line of code. It utilizes PyPDFium2, favored for its high throughput and permissive licensing. The training model TATR used by gmft is trained on the diverse dataset PubTables-1M, ensuring high reliability.

Transformer Explainer is an online visualization tool dedicated to helping users thoroughly understand Transformer models. It graphically displays various components of the Transformer model, including the self-attention mechanism and feedforward networks, allowing users to visually see the flow and processing of data within the model. This tool holds significant importance in the education and research fields, aiding students and researchers in better comprehending advanced technologies in natural language processing.

This GitHub repository contains training and inference code to replicate our winning solution in the AI Mathematics Olympic (AIMO) Progress Prize 1. Our solution consists of four main parts: a recipe for fine-tuning DeepSeekMath-Base 7B for use in solving math problems using Tool Integrated Reasoning (TIR); two high-quality datasets of about 10 million math questions and solutions; an algorithm for generating solution candidates with coding execution feedback (SC-TIR); and four carefully selected validation sets from AMC, AIME, and MATH to guide model selection and avoid overfitting the public leaderboard.

BrainyAI is a completely free Chrome browser extension. Users only need to log in once to use various AI websites. Through a convenient sidebar interface, BrainyAI provides AI chat aggregation, AI search, AI reading, and enhanced AI web browsing features. It supports multiple large language models, such as GPT3.5, GPT4, and prioritizes user privacy. All chat history, settings, and login data are securely stored on the user's local device.

Awesome-ChatTTS is an open-source project aimed at providing FAQs and resource compilations related to the ChatTTS project, helping users quickly get started and resolve potential issues during use. The project not only compiles detailed installation guides and parameter descriptions but also provides examples of various voice seeds and auxiliary materials such as video tutorials.

HippoRAG is a novel Retriever-Augmented Generation (RAG) framework inspired by human long-term memory, enabling Large Language Models (LLMs) to continuously integrate knowledge across external documents. Experiments demonstrate that HippoRAG can provide the capabilities of RAG systems, typically requiring expensive and high-latency iterative LLM pipelines, at a lower computational cost.

Tap4 AI Web UI is an open-source AI tool directory built upon Tap4 AI Tools Directory. This project aims to empower everyone to easily construct their own AI tool directory. You can fork the project, deploy it to Vercel with one click, and update your own AI tools through the provided dataList.

awesome-LLM-resources is a platform that aggregates global resources for large language models (LLMs), offering a range of tools and resources from data acquisition and fine-tuning to inference, evaluation, and real-world applications. Its significance lies in providing researchers and developers with a comprehensive resource library to facilitate the efficient development and optimization of their language models. Maintained by Wang Rongsheng, the platform is continuously updated, providing robust support for the advancement of the LLM field.

The Intel? Core? Ultra 200 series desktop processors are the first AI PC processors designed for the desktop platform, delivering exceptional gaming experiences and industry-leading computing performance while significantly reducing power consumption. These processors feature up to 8 next-generation performance cores (P-cores) and up to 16 next-generation efficiency cores (E-cores), resulting in up to a 14% performance improvement in multi-threaded workloads compared to the previous generation. They are also the first desktop processors equipped with a neural processing unit (NPU) for enthusiasts, and include built-in Xe GPU technology, supporting advanced media features.

Geekits is an open-source and free platform created by YGeeker, providing a suite of practical tools across various domains including Artificial Intelligence, Everyday Use, Image and Video Processing, and Programming Development. It offers convenient services for general users while also providing programming-related support for developers. The main advantages of Geekits lie in its diversity and practicality, allowing users to find tools ranging from simple everyday utilities to professional development aids, greatly enhancing work and life efficiency.

The Intel? Gaudi? 3 AI Accelerator is a high-performance artificial intelligence accelerator launched by Intel, built on the efficient Intel? Gaudi? platform. It boasts outstanding MLPerf benchmark performance and is designed to handle demanding training and inference tasks. The accelerator supports AI applications such as large language models, multimodal models, and enterprise RAG in data centers or the cloud, operating on your existing Ethernet infrastructure. Whether you need a single accelerator or thousands, Intel Gaudi 3 can play a crucial role in your AI success.

Hoody AI is a privacy-focused unified interface designed to provide anonymous access to a range of large language models (LLMs). Users can easily access multiple AI models and functions while maintaining anonymity. The platform employs advanced encryption methods to ensure data security and supports anonymous payments, protecting users' identities from being tracked. It features an intuitive, responsive dashboard that supports cross-platform access on both mobile and desktop devices.

AIbase is a comprehensive platform with an extensive database of over 7,000 outstanding artificial intelligence websites and products across more than 40 different fields, such as AI-generated art, AI copywriting, AI video editing, and AI-driven marketing. Users can easily find the AI tools that best meet their needs and unlock the power of AI.

QAbot-zh/query-key is a pure front-end API testing tool that supports various API formats such as oneapi/newapi and can also verify OpenAI formatted APIs. The main advantage of this tool lies in its front-end implementation, eliminating concerns about gateway timeouts while ensuring data security. It provides comprehensive test data displays, including response times and model consistency, allowing users to intuitively understand API performance. Additionally, it supports local one-click execution and online hosting via pages, making it convenient for users to deploy and use quickly.

gmft is a toolkit designed to convert tables in PDFs into various formats. It is lightweight, modular, and delivers exceptional performance. gmft relies on Microsoft's Table Transformers, recognized as one of the best-performing and most reliable solutions among many alternatives. It operates without the need for a GPU, offering high throughput and easy installation, requiring only a single line of code. It utilizes PyPDFium2, favored for its high throughput and permissive licensing. The training model TATR used by gmft is trained on the diverse dataset PubTables-1M, ensuring high reliability.

Transformer Explainer is an online visualization tool dedicated to helping users thoroughly understand Transformer models. It graphically displays various components of the Transformer model, including the self-attention mechanism and feedforward networks, allowing users to visually see the flow and processing of data within the model. This tool holds significant importance in the education and research fields, aiding students and researchers in better comprehending advanced technologies in natural language processing.