Search Results for "so" - Page 25
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Showing 1270 open source projects for "so"
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SoftVC VITS Singing Voice Conversion
SoftVC VITS Singing Voice Conversion
...It is commonly used in creative audio workflows, especially in communities experimenting with synthetic singing and character voices. The repository includes training and inference pipelines that enable users to build and apply custom voice models. Overall, so-vits-svc serves as a specialized toolkit for neural singing voice conversion and audio synthesis research. -
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bilili
Command-line Bilibili video and danmaku downloader with batch support
...These danmaku comments can be automatically converted into ASS subtitle format for playback compatibility with media players. bilili also implements multi-threaded and segmented downloading techniques to improve download performance and reliability. Additionally, it supports resuming interrupted downloads so partially downloaded content can continue without restarting from the beginning. -
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Sweep AI
Sweep: AI-powered Junior Developer for small features and bug fixes
Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep. -
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Janken
Janken - A Simple Rock, Paper, Scissors Game
Janken is a simple game to play Rock, Paper, Scissors on computer with Windows OS. It's portable, so no need to install it on your computer to play. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
...The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common strategies such as moving average crossovers, momentum trading, and custom indicators on historical stock data. By automating data retrieval, strategy evaluation, and result visualization, the library reduces the barrier to entry for individuals interested in quantitative finance. ... -
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Termux Desktop
Setup A Beautiful Desktop/GUI In Termux
Termux Desktop is a collection of dotfiles and scripts for setting up a graphical Linux-style desktop environment inside Termux on Android. It helps users turn a phone or tablet into a more complete desktop-like workspace without needing root access. The setup uses VNC so the desktop can be opened through a VNC client after installation. It includes an Openbox-based environment with visual themes, menus, app launchers, terminal tools, file management, browser access, and system applets. The project is especially useful for experimenting with coding, Linux tools, classic applications, and lightweight desktop workflows on Android hardware. ... -
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Parveshdhull AutoTyper
A Data Entry Tool for Windows and Linux
...There are many tools available online but almost all of them only provide trial versions. And requires big payment for continued access. And even if they are free, it is not wise to give complete access to a keyboard to any third-party software. So I wrote this simple-short python script that reads content from a text file then simulates keyboard typing. This Script works on both Linux and Windows. -
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ChatGLM Efficient Tuning
Fine-tuning ChatGLM-6B with PEFT
ChatGLM-Efficient-Tuning is a hands-on toolkit for fine-tuning ChatGLM-family models with parameter-efficient methods on everyday hardware. It wraps techniques like LoRA and prompt-tuning into simple training scripts so you can adapt a large model to your domain without full retraining. The project exposes practical switches for quantization and mixed precision, allowing bigger models to fit into limited VRAM. It includes examples for instruction tuning and dialogue datasets, making it straightforward to stand up a task-specific assistant. Because the code leans on widely used libraries, you can bring your own datasets and monitoring tools with minimal glue. ... -
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Crawlab
Distributed web crawler admin platform for spiders management
Golang-based distributed web crawler management platform, supporting various languages including Python, NodeJS, Go, Java, PHP and various web crawler frameworks including Scrapy, Puppeteer, Selenium. Please use docker-compose to one-click to start up. By doing so, you don't even have to configure MongoDB database. The frontend app interacts with the master node, which communicates with other components such as MongoDB, SeaweedFS and worker nodes. Master node and worker nodes communicate with each other via gRPC (a RPC framework). Tasks are scheduled by the task scheduler module in the master node, and received by the task handler module in worker nodes, which executes these tasks in task runners. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Wicogen-windows-icon-generator
Windows folder icon generator
...Supported sources for online search: Google images Bing images IMDB (covers for movies and TV shows) MyAnimeList.net (covers for anime and movies) For Movie/TV, I recommend the disk style available in the "Style:" drop-down. If you find all the settings confusing, hover over them for a second, a Tooltip window will pop up. For any questions or suggestions, feel free to do so in the discussions on the github page! 💬 NOTICE: After generating the icons for existing folders, it can take a couple of minutes to refresh (When creating new folders from icons, It should be instantaneous). -
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Bard
Python SDK/API for reverse engineered Google Bard
...Because Google doesn’t provide a standard public API for Bard, this project works by reverse-engineering the web interactions that power Bard’s interface and exposing them through code-friendly interfaces, enabling chat automation, custom workflows, and bot creation. The repository typically includes authentication handling, session management, and request/response serialization so that developers don’t have to deal with low-level HTTP details. Users can integrate Bard into Python scripts, chatbots, or local testing environments where conversational AI is useful but an official API isn’t yet available. -
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simpleaichat
Python package for easily interfacing with chat apps
...The package emphasizes simplicity over heavy frameworks, making it ideal for scripts, notebooks, and small services that need LLMs without architectural lock-in. It supports structured responses and validation patterns so your app can reliably parse model outputs instead of wrestling with brittle free-text parsing. The project encourages clean separation between system prompts, user messages, and tool outputs to keep conversations predictable. With convenience helpers for logging, environment configuration, and retries, it reduces the friction of moving from a quick experiment to a reliable internal tool. -
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MusicBot
The original MusicBot for Discord
...The bot includes a configurable queue system and can automatically continue playback from an existing song list when the queue is empty. It also includes a permissions system so server owners can restrict commands to specific people or roles. Configuration is handled through an options file, and the project provides setup guides for installation and Discord connection. MusicBot is useful for communities that want a self-hosted, configurable music bot rather than a hosted service. -
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FastEdit
Editing large language models within 10 seconds
...This approach is valuable when you need urgent corrections—think product names, APIs, or fast-changing facts—without retraining on large corpora. The repository provides evaluation harnesses so you can measure locality (does the change stay contained?) and generalization (does the change apply where it should?). It’s structured for repeatable experiments, making side-by-side comparisons of editing methods and hyperparameters straightforward. For applied teams, FastEdit offers a toolbox to keep models current and compliant while minimizing collateral damage to overall performance. -
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VATSG
Video automatic transcribe and translated subtitle generator
...This is the subtitle generator(VATSG) which use [moviepy](https://github.com/Zulko/moviepy) to generate mp3 and then use [faster-whisper](https://github.com/guillaumekln/faster-whisper) to get text recognition and then use deepl-api to generate your target language subtitle file(srt format) If you are a general user who want to view any video file and mp3 file to your language, It will provide way. It's very easy to use because it has simple gui and very intuitive. So you can easily use it for any purpose. Now, you can choose to download either window installer setup type or uninstalled type. Enjoy and support my consistent development! -
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mindflow
AI-powered CLI git wrapper, boilerplate code generator, chat history
...If you have access, you can run mf config and select GPT 4. If you don't have access, you'll get an error message. Interact with chatGPT directly just like on the chatGPT website. We also have chat persistence, so it will remember the previous chat messages. You can provide single or multi-file context to chatGPT by passing in any number of files as a separate argument in the mf chat call. -
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ParlAI
A framework for training and evaluating AI models
ParlAI is a comprehensive research platform for building, training, and evaluating dialogue agents across a wide variety of tasks and datasets. It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with utilities for multitask training and model selection. ... -
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Sound to Text
Convert a sound file to text to analyze it
...Use the program with songs, movie or TV dialogue, private recordings, to reveal the hidden text messages of the sound. The resulting text will be a long string of mostly repeating characters but, every so often, you will notice an intelligible word, either spelled normally or with repeated letters, missing letters or anagrammed letters. It takes a little allegoric-Freudian psychological exegetic ability to elaborate the right chain of mind associations to infer a convincing interpretation of the resulting text. You may want to share the text with a psychologist to get a professional opinion on your interpretation, but sometimes the meaning will be surprisingly obvious. -
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Image to Text
Convert an image to text to spot intelligible words.
...You can also use it on photos of people or art pieces to have a psychological insight of the person portrayed or of the image author. The resulting text will be a long string of mostly repeating characters but, every so often, you will notice an intelligible word, either spelled normally or with repeated letters, missing letters or anagrammed letters. -
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...Free up valuable disk space by eliminating redundant copies and optimizing your storage usage. Some Antivers may show false virus alert ignore it , this tool delete files so i think thats why they think this is virus. dont use this tool on "C" drive or where you install your windows .
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DeepMind Research
Implementations and code to accompany DeepMind publications
...The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. The codebase is primarily Jupyter Notebooks and Python, reflecting an emphasis on experimentation and pedagogy rather than production packaging. -
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DALL-E in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image
...Currently only the VAE with a codebook size of 1024 is offered, with the hope that it may train a little faster than OpenAI's, which has a size of 8192. In contrast to OpenAI's VAE, it also has an extra layer of downsampling, so the image sequence length is 256 instead of 1024 (this will lead to a 16 reduction in training costs, when you do the math). -
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sense2vec
Contextually-keyed word vectors
sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detailed word vectors. This library is a simple Python implementation for loading, querying and training sense2vec models. For more details, check out our blog post. To explore the semantic similarities across all Reddit comments of 2015 and 2019, see the interactive demo. -
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minimalRL-pytorch
Implementations of basic RL algorithms with minimal lines of codes
...The repository includes examples of widely used reinforcement learning methods such as REINFORCE, Deep Q-Networks, Proximal Policy Optimization, and Actor-Critic architectures. Most experiments are designed to run quickly using the CartPole environment so that users can focus on understanding algorithm logic rather than computational infrastructure. -
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Bot on Anything
Large model-based chatbot builder that can quickly integrate AI models
...At its heart, the project abstracts away the glue logic between AI model APIs and disparate application “channels,” enabling the same bot logic to run in Slack, Telegram, Gmail, enterprise tools, web UIs, or command-line terminals. Configuration is handled simply through a central JSON file where you define which model and which application channel you want to glue together, so developers can create sophisticated AI assistants without rewriting integration code from scratch. The architecture emphasizes reusability and extensibility, allowing the addition of new model backends or new channels with relative ease. It supports switching between multiple AI models and targets within the same project.