AI tools for 躺平
Related Tools:
Unicode 字符映射转换器
这是李继刚(即刻同名)创建的用于美化英文样式的 Bot。可以将英文字符转换成好看的样式,粘贴到微信等不支持切换字体的软件中。 输入中文会先翻译为英文,再做转换。
PythonPark
PythonPark is a paradise for learning Python, providing babysitter-level tutorials on AI labs, treasure videos, data structures, study guides, machine learning practicals, deep learning practicals, Python basics, web scraping, big company interview experiences, programming life, and resource sharing. Original articles are published at least twice a week, with the latest articles being first released on WeChat and videos on Bilibili. Join the WeChat group for technical discussions or to provide feedback. Continuously improving and outputting content!
blog
This repository contains a simple blog application built using Python and Flask framework. It allows users to create, read, update, and delete blog posts. The application uses SQLite database for storing blog data and provides a basic user interface for interacting with the blog. The code is well-organized and easy to understand, making it suitable for beginners looking to learn web development with Python and Flask.
everyday
Everyday is a story generator tool that uses AI to weave fantasy stories based on daily quotes. It features an intelligent writing engine that expands quotes into captivating short stories, a time capsule storage system for story archiving, an immersive document site with a real-time story gallery, and cloud automation for daily story generation. Users can clone the repository, activate the Python environment, configure AI keys, and start the story furnace to witness quotes transform into complete stories. The project follows the MIT open convention, allowing users to freely use, modify, and share the generated stories while preserving the original magic touch.
Interview-for-Algorithm-Engineer
This repository provides a collection of interview questions and answers for algorithm engineers. The questions are organized by topic, and each question includes a detailed explanation of the answer. This repository is a valuable resource for anyone preparing for an algorithm engineering interview.
LLMBook-zh.github.io
This book aims to provide readers with a comprehensive understanding of large language model technology, including its basic principles, key technologies, and application prospects. Through in-depth research and practice, we can continuously explore and improve large language model technology, and contribute to the development of the field of artificial intelligence.
Verbiverse
Verbiverse is a tool that uses a large language model to assist in reading PDFs and watching videos, aimed at improving language proficiency. It provides a more convenient and efficient way to use large models through predefined prompts, designed for those looking to enhance their language skills. The tool analyzes unfamiliar words and sentences in foreign language PDFs or video subtitles, providing better contextual understanding compared to traditional dictionary translations or ambiguous meanings. It offers features such as automatic loading of subtitles, word analysis by clicking or double-clicking, and a word database for collecting words. Users can run the tool on Windows x86_64 or ubuntu_22.04 x86_64 platforms by downloading the precompiled packages or by cloning the source code and setting up a virtual environment with Python. It is recommended to use a local model or smaller PDF files for testing due to potential token consumption issues with large files.
bert4torch
**bert4torch** is a high-level framework for training and deploying transformer models in PyTorch. It provides a simple and efficient API for building, training, and evaluating transformer models, and supports a wide range of pre-trained models, including BERT, RoBERTa, ALBERT, XLNet, and GPT-2. bert4torch also includes a number of useful features, such as data loading, tokenization, and model evaluation. It is a powerful and versatile tool for natural language processing tasks.
gpt_academic
GPT Academic is a powerful tool that leverages the capabilities of large language models (LLMs) to enhance academic research and writing. It provides a user-friendly interface that allows researchers, students, and professionals to interact with LLMs and utilize their abilities for various academic tasks. With GPT Academic, users can access a wide range of features and functionalities, including: * **Summarization and Paraphrasing:** GPT Academic can summarize complex texts, articles, and research papers into concise and informative summaries. It can also paraphrase text to improve clarity and readability. * **Question Answering:** Users can ask GPT Academic questions related to their research or studies, and the tool will provide comprehensive and well-informed answers based on its knowledge and understanding of the relevant literature. * **Code Generation and Explanation:** GPT Academic can generate code snippets and provide explanations for complex coding concepts. It can also help debug code and suggest improvements. * **Translation:** GPT Academic supports translation of text between multiple languages, making it a valuable tool for researchers working with international collaborations or accessing resources in different languages. * **Citation and Reference Management:** GPT Academic can help users manage their citations and references by automatically generating citations in various formats and providing suggestions for relevant references based on the user's research topic. * **Collaboration and Note-Taking:** GPT Academic allows users to collaborate on projects and take notes within the tool. They can share their work with others and access a shared workspace for real-time collaboration. * **Customizable Interface:** GPT Academic offers a customizable interface that allows users to tailor the tool to their specific needs and preferences. They can choose from a variety of themes, adjust the layout, and add or remove features to create a personalized workspace. Overall, GPT Academic is a versatile and powerful tool that can significantly enhance the productivity and efficiency of academic research and writing. It empowers users to leverage the capabilities of LLMs and unlock new possibilities for academic exploration and knowledge creation.
stylellm_models
**stylellm** is a text style transfer project based on large language models (llms). The project utilizes large language models to learn the writing style of specific literary works (commonly used vocabulary, sentence structure, rhetoric, character dialogue, etc.), forming a series of specific style models. Using the **stylellm** model, the learned style can be transferred to other general texts, that is: input a piece of original text, the model can rewrite it, output text with the characteristics of that style, achieving the effect of text modification,润色or style imitation.
Tutorial
The Bookworm·Puyu large model training camp aims to promote the implementation of large models in more industries and provide developers with a more efficient platform for learning the development and application of large models. Within two weeks, you will learn the entire process of fine-tuning, deploying, and evaluating large models.
AiLearning-Theory-Applying
This repository provides a comprehensive guide to understanding and applying artificial intelligence (AI) theory, including basic knowledge, machine learning, deep learning, and natural language processing (BERT). It features detailed explanations, annotated code, and datasets to help users grasp the concepts and implement them in practice. The repository is continuously updated to ensure the latest information and best practices are covered.
AIProductHome
AI Product Home is a repository dedicated to collecting various AI commercial or open-source products. It provides assistance in submitting issues, self-recommendation, correcting resources, and more. The repository also features AI tools like Build Naidia, Autopod, Rytr, Mubert, and a virtual town driven by AI. It includes sections for AI models, chat dialogues, AI assistants, code assistance, artistic creation, content creation, and more. The repository covers a wide range of AI-related tools and resources for users interested in AI products and services.
Wechat-AI-Assistant
Wechat AI Assistant is a project that enables multi-modal interaction with ChatGPT AI assistant within WeChat. It allows users to engage in conversations, role-playing, respond to voice messages, analyze images and videos, summarize articles and web links, and search the internet. The project utilizes the WeChatFerry library to control the Windows PC desktop WeChat client and leverages the OpenAI Assistant API for intelligent multi-modal message processing. Users can interact with ChatGPT AI in WeChat through text or voice, access various tools like bing_search, browse_link, image_to_text, text_to_image, text_to_speech, video_analysis, and more. The AI autonomously determines which code interpreter and external tools to use to complete tasks. Future developments include file uploads for AI to reference content, integration with other APIs, and login support for enterprise WeChat and WeChat official accounts.
do-research-in-AI
This repository is a collection of research lectures and experience sharing posts from frontline researchers in the field of AI. It aims to help individuals upgrade their research skills and knowledge through insightful talks and experiences shared by experts. The content covers various topics such as evaluating research papers, choosing research directions, research methodologies, and tips for writing high-quality scientific papers. The repository also includes discussions on academic career paths, research ethics, and the emotional aspects of research work. Overall, it serves as a valuable resource for individuals interested in advancing their research capabilities in the field of AI.
XiaoFeiShu
XiaoFeiShu is a specialized automation software developed closely following the quality user rules of Xiaohongshu. It provides a set of automation workflows for Xiaohongshu operations, avoiding the issues of traditional RPA being mechanical, rule-based, and easily detected. The software is easy to use, with simple operation and powerful functionality.
bookmark-summary
The 'bookmark-summary' repository reads bookmarks from 'bookmark-collection', extracts text content using Jina Reader, and then summarizes the text using LLM. The detailed implementation can be found in 'process_changes.py'. It needs to be used together with the Github Action in 'bookmark-collection'.