video-subtitle-remover

Video-subtitle-remover (VSR) is a software based on AI technology that removes hard subtitles from videos. It achieves the following functions: - Lossless resolution: Remove hard subtitles from videos, generate files with subtitles removed - Fill the region of removed subtitles using a powerful AI algorithm model (non-adjacent pixel filling and mosaic removal) - Support custom subtitle positions, only remove subtitles in defined positions (input position) - Support automatic removal of all text in the entire video (no input position required) - Support batch removal of watermark text from multiple images.

The GPT Server project leverages the basic capabilities of FastChat to provide the capabilities of an openai server. It perfectly adapts more models, optimizes models with poor compatibility in FastChat, and supports loading vllm, LMDeploy, and hf in various ways. It also supports all sentence_transformers compatible semantic vector models, including Chat templates with function roles, Function Calling (Tools) capability, and multi-modal large models. The project aims to reduce the difficulty of model adaptation and project usage, making it easier to deploy the latest models with minimal code changes.

Web Builder is a low-code front-end framework based on Material for Angular, offering a rich component library for excellent digital innovation experience. It allows rapid construction of modern responsive UI, multi-theme, multi-language web pages through drag-and-drop visual configuration. The framework includes a beautiful admin theme, complete front-end solutions, and AI integration in the Pro version for optimizing copy, creating components, and generating pages with a single sentence.

JiwuChat is a lightweight multi-platform chat application built on Tauri2 and Nuxt3, with various real-time messaging features, AI group chat bots (such as 'iFlytek Spark', 'KimiAI' etc.), WebRTC audio-video calling, screen sharing, and AI shopping functions. It supports seamless cross-device communication, covering text, images, files, and voice messages, also supporting group chats and customizable settings. It provides light/dark mode for efficient social networking.

Agentica is a human-centric framework for building large language model agents. It provides functionalities for planning, memory management, tool usage, and supports features like reflection, planning and execution, RAG, multi-agent, multi-role, and workflow. The tool allows users to quickly code and orchestrate agents, customize prompts, and make API calls to various services. It supports API calls to OpenAI, Azure, Deepseek, Moonshot, Claude, Ollama, and Together. Agentica aims to simplify the process of building AI agents by providing a user-friendly interface and a range of functionalities for agent development.

MEGREZ is a modern and elegant open-source high-performance computing platform that efficiently manages GPU resources. It allows for easy container instance creation, supports multiple nodes/multiple GPUs, modern UI environment isolation, customizable performance configurations, and user data isolation. The platform also comes with pre-installed deep learning environments, supports multiple users, features a VSCode web version, resource performance monitoring dashboard, and Jupyter Notebook support.

Jiwu Chat Tauri APP is a desktop chat application based on Nuxt3 + Tauri + Element Plus framework. It provides a beautiful user interface with integrated chat and social functions. It also supports AI shopping chat and global dark mode. Users can engage in real-time chat, share updates, and interact with AI customer service through this application.

Llama中文社区是一个专注于Llama模型在中文方面的优化和上层建设的高级技术社区。 **已经基于大规模中文数据，从预训练开始对Llama2模型进行中文能力的持续迭代升级【Done】**。**正在对Llama3模型进行中文能力的持续迭代升级【Doing】** 我们热忱欢迎对大模型LLM充满热情的开发者和研究者加入我们的行列。

HivisionIDPhoto is a practical algorithm for intelligent ID photo creation. It utilizes a comprehensive model workflow to recognize, cut out, and generate ID photos for various user photo scenarios. The tool offers lightweight cutting, standard ID photo generation based on different size specifications, six-inch layout photo generation, beauty enhancement (waiting), and intelligent outfit swapping (waiting). It aims to solve emergency ID photo creation issues.

Wenda is a platform for large-scale language model invocation designed to efficiently generate content for specific environments, considering the limitations of personal and small business computing resources, as well as knowledge security and privacy issues. The platform integrates capabilities such as knowledge base integration, multiple large language models for offline deployment, auto scripts for additional functionality, and other practical capabilities like conversation history management and multi-user simultaneous usage.

Widgets is a desktop component front-end open source component. The project is still being continuously improved. The desktop component client can be downloaded and run in two ways: 1. https://www.microsoft.com/store/productId/9NPR50GQ7T53 2. https://widgetjs.cn After cloning the code, you need to download the dependency in the project directory: `shell pnpm install` and run: `shell pnpm serve`

AstrBot is a powerful and versatile tool that leverages the capabilities of large language models (LLMs) like GPT-3, GPT-3.5, and GPT-4 to enhance communication and automate tasks. It seamlessly integrates with popular messaging platforms such as QQ, QQ Channel, and Telegram, enabling users to harness the power of AI within their daily conversations and workflows.

MedicalGPT is a training medical GPT model with ChatGPT training pipeline, implement of Pretraining, Supervised Finetuning, RLHF(Reward Modeling and Reinforcement Learning) and DPO(Direct Preference Optimization).

Chatluna is a machine learning model plugin that provides chat services with large language models. It is highly extensible, supports multiple output formats, and offers features like custom conversation presets, rate limiting, and context awareness. Users can deploy Chatluna under Koishi without additional configuration. The plugin supports various models/platforms like OpenAI, Azure OpenAI, Google Gemini, and more. It also provides preset customization using YAML files and allows for easy forking and development within Koishi projects. However, the project lacks web UI, HTTP server, and project documentation, inviting contributions from the community.

Chinese-Mixtral-8x7B is an open-source project based on Mistral's Mixtral-8x7B model for incremental pre-training of Chinese vocabulary, aiming to advance research on MoE models in the Chinese natural language processing community. The expanded vocabulary significantly improves the model's encoding and decoding efficiency for Chinese, and the model is pre-trained incrementally on a large-scale open-source corpus, enabling it with powerful Chinese generation and comprehension capabilities. The project includes a large model with expanded Chinese vocabulary and incremental pre-training code.

This repository aims to build a low-parameter LLM model through pretraining, fine-tuning, model rewarding, and reinforcement learning stages to create a chat model capable of simple conversation tasks. It features using the bert4torch training framework, seamless integration with transformers package for inference, optimized file reading during training to reduce memory usage, providing complete training logs for reproducibility, and the ability to customize robot attributes. The chat model supports multi-turn conversations. The trained model currently only supports basic chat functionality due to limitations in corpus size, model scale, SFT corpus size, and quality.

Video-subtitle-remover (VSR) is a software based on AI technology that removes hard subtitles from videos. It achieves the following functions: - Lossless resolution: Remove hard subtitles from videos, generate files with subtitles removed - Fill the region of removed subtitles using a powerful AI algorithm model (non-adjacent pixel filling and mosaic removal) - Support custom subtitle positions, only remove subtitles in defined positions (input position) - Support automatic removal of all text in the entire video (no input position required) - Support batch removal of watermark text from multiple images.

Video GigaGAN - Pytorch is an implementation of Video GigaGAN, a state-of-the-art video upsampling technique developed by Adobe AI labs. The project aims to provide a Pytorch implementation for researchers and developers interested in video super-resolution. The codebase allows users to replicate the results of the original research paper and experiment with video upscaling techniques. The repository includes the necessary code and resources to train and test the GigaGAN model on video datasets. Researchers can leverage this implementation to enhance the visual quality of low-resolution videos and explore advancements in video super-resolution technology.

Intel® Library for Video Super Resolution (Intel® Library for VSR) is a project that offers a variety of algorithms, including machine learning and deep learning implementations, to convert low-resolution videos to high resolution. It enhances the RAISR algorithm to provide better visual quality and real-time performance for upscaling on Intel® Xeon® platforms and Intel® GPUs. The project is developed in C++ and utilizes Intel® AVX-512 on Intel® Xeon® Scalable Processor family and OpenCL support on Intel® GPUs. It includes an FFmpeg plugin inside a Docker container for ease of testing and deployment.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.