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Showing 2452 open source projects for "vb6 source code"
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iTerm2 Color Schemes
Over 425 terminal color schemes/themes for iTerm/iTerm2
This project curates a large collection of terminal color schemes and makes them available in formats for many terminal emulators, not just iTerm2. You’ll find well-known palettes like Solarized, Dracula, Nord, and hundreds more, each with previews that showcase how code, prompts, and text look under the theme. The repository includes export files for multiple terminals—such as iTerm2, Apple Terminal, Alacritty, Kitty, Windows Terminal, and others—so you can apply the same aesthetic... -
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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AI Agent Deep Dive
AI Agent Source Code Deep Research Report
AI Agent Deep Dive is a comprehensive educational repository designed to provide a deep and structured understanding of how modern AI agents work, focusing on architecture, workflows, and real-world implementation patterns. It breaks down complex concepts such as planning, tool usage, memory management, and multi-step reasoning into digestible explanations and practical examples. The project is organized as a learning resource rather than a standalone framework, making it particularly useful... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project... -
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Fish Speech
SOTA Open Source TTS
Fish Speech is a state-of-the-art open-source text-to-speech project that has evolved into the OpenAudio series of advanced TTS models. The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong intelligibility and alignment between text and audio. ... -
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AgentHandover
AgentHandover observes, learns and teaches agents with skills
AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection... -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to... -
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Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
Unsloth-MLX offers developers the power of Unsloth’s efficient large language model fine-tuning experience on Apple Silicon Macs by wrapping Apple’s native MLX framework with an API fully compatible with Unsloth workflows. This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs.... -
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H2O LLM Studio
Framework and no-code GUI for fine-tuning LLMs
Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an... -
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Ansible-lint
Best practices checker for Ansible
Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible lint is also supposed to help users upgrade their code to work with newer versions of Ansible. Due to this reason we recommend using it with the newest version of Ansible, even if the version used in production... -
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MCP for Unity
AI bridge enabling assistants to control and automate Unity Editor
Unity MCP is an open source integration that connects AI assistants with the Unity Editor through the Model Context Protocol (MCP). It acts as a bridge that allows language models and AI coding tools to interact directly with a Unity development environment using structured commands and tools. By linking an AI assistant to a running Unity project, the system enables automated operations such as managing project assets, modifying scenes, editing scripts, and performing other development tasks... -
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Python Progressbar
Progressbar 2 - A progress bar for Python 2 and Python 3
A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. This package is still backward compatible with the original progressbar package so you can safely... -
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PaperSpine
Motivation-driven skill for learning from strong academic papers
PaperSpine is a motivation-driven writing skill suite for academic papers, reports, reviews, and technical manuscripts. It is built for AI tools such as Codex, Claude Code, and OpenClaw, where the agent can follow structured writing workflows. The project asks the agent to study target formats and strong examples before drafting or revising. It emphasizes the central motivation of a paper, helping writers connect claims, structure, evidence, citations, and revisions into a coherent argument.... -
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LeWorldModel
Official code base for LeWorldModel: Stable End-to-End Joint-Embedding
...It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. Its architecture avoids unnecessary complexity, making it easy to understand, modify, and extend. -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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wikmd
A file based wiki that uses markdown
It’s a file-based wiki that aims to simplicity. Instead of storing the data in a database I chose to have a file-based system. The advantage of this system is that every file is directly readable inside a terminal etc. Also when you have direct access to the system you can export the files to anything you like. -
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BlackSheep
Fast ASGI web framework for Python
BlackSheep is an asynchronous web framework to build event-based web applications with Python. A rich code API, based on dependency injection and inspired by Flask and ASP.NET Core. A typing-friendly codebase, which enables a comfortable development experience thanks to hints when coding with IDEs. Built-in generation of OpenAPI Documentation, supporting version 3, YAML, and JSON. A cross-platform framework, using the most modern versions of Python. BlackSheep supports automatic binding of... -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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Microsoft Azure CLI
Azure command-line interface
A great cloud needs great tools; we're excited to introduce Azure CLI, our next-generation multi-platform command-line experience for Azure. Take a test run now from Azure Cloud Shell! We support tab completion for groups, commands, and some parameters. You can use the --query parameter and the JMESPath query syntax to customize your output. With the Azure CLI Tools Visual Studio Code extension, you can create .azcli files and use these features. IntelliSense for commands and their... -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant... -
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Freqtrade
Free, open source crypto trading bot
...We strongly recommend you have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. Find the best parameters for your strategy using hyper optimization which employs machining learning methods. -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU,... -
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Manim Python
Animation engine for explanatory math videos
Manim is a Python library and animation engine designed for creating precise, programmatic mathematical visuals—famously used by 3Blue1Brown. It enables developers and educators to script animations using code and produce high-quality explanatory math videos. -
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that...
