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Showing 3412 open source projects for "you"
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Ultralytics
Ultralytics YOLO
Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. -
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papermill
Parameterize, execute, and analyze notebooks
papermill is a Python library and command-line tool that transforms Jupyter Notebooks into repeatable, parameterized workflows by allowing users to define editable parameters within notebooks and then programmatically execute them with different inputs. Instead of manually opening and running a notebook inside JupyterLab or Notebook every time, Papermill lets you inject new values into a specially tagged parameters cell and execute the entire notebook automatically via a script or automation pipeline, which enables robust automation of data analysis, reports, and experiments. This capability is particularly useful in data science and analytics, where a template notebook might be reused for batching reports across dates, customers, or other variables without rewriting code or duplicating notebooks. ... -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
...It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking. -
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Z80-μLM
Z80-μLM is a 2-bit quantized language model
Z80-μLM is a retro-computing AI project that demonstrates a tiny language model (Z80-μLM) engineered to run on an 8-bit Z80 CPU by aggressively quantizing weights down to 2-bit precision. The repository provides a complete workflow where you train or fine-tune conversational models in Python, then export them into a format that can be executed on classic Z80 systems. A key deliverable is producing CP/M-compatible .COM binaries, enabling a genuinely vintage “chat with your computer” experience on real hardware or accurate emulators. The project sits at the intersection of machine learning and systems constraints, showing how model architecture, quantization, and inference code generation can be adapted to extreme memory and compute limits. ... -
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CLIP
CLIP, Predict the most relevant text snippet given an image
...It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language. -
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Phenaki - Pytorch
Implementation of Phenaki Video, which uses Mask GIT
Implementation of Phenaki Video, which uses Mask GIT to produce text-guided videos of up to 2 minutes in length, in Pytorch. It will also combine another technique involving a token critic for potentially even better generations. A new paper suggests that instead of relying on the predicted probabilities of each token as a measure of confidence, one can train an extra critic to decide what to iteratively mask during sampling. This repository will also endeavor to allow the researcher to... -
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Hy
A dialect of Lisp that's embedded in Python
...Compared to Python, Hy offers a variety of extra features, generalizations, and syntactic simplifications, as would be expected of a Lisp. Compared to other Lisps, Hy provides direct access to Python’s built-ins and third-party Python libraries, while allowing you to freely mix imperative, functional, and object-oriented styles of programming. The first thing a Python programmer will notice about Hy is that it has Lisp’s traditional parenthesis-heavy prefix syntax in place of Python’s C-like infix syntax. As in other Lisps, the value of a simplistic syntax is that it facilitates Lisp’s signature feature, metaprogramming through macros, which are functions that manipulate code objects at compile-time to produce new code objects, which are then executed as if they had been part of the original code. -
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armory
3D Engine with Blender Integration
...Powered by Armory engine, ArmorPaint is a stand-alone software designed for physically-based texture painting. Drag & drop your 3D models and start painting. Receive instant visual feedback in the viewport as you paint. Powered by Armory engine, ArmorLab is stand-alone software designed for AI-powered texture authoring. Generate PBR materials by drag & dropping your photos. In development! Armory is an open-source 3D game engine with full Blender integration. The engine is currently available in a form of early preview. -
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Pixoo
A library to help you make the most out of your Pixoo 64
Pixoo is a Python-based library for controlling Divoom Pixoo LED displays using Bluetooth Low Energy (BLE). It allows users to send images, animations, or text to Pixoo devices, enabling creative integrations like desktop widgets, real-time data displays, or custom artwork. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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zpdf
Zero-copy PDF text extraction library written in Zig
...It also understands both classic cross-reference tables and newer cross-reference streams, including PDF 1.5+ features, and it offers configurable strict vs permissive error handling depending on whether you prioritize correctness or robustness. -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
...The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new language sets. It emphasizes modularity: acoustic modeling, language modeling, tokenization, and decoding are separable pieces you can swap or ablate. The repo is aimed at pushing practical multilingual ASR—robust to accents, code-switching, and domain shifts—rather than language-by-language systems. For practitioners, it’s a starting point to study transfer, zero-shot behavior, and trade-offs between model size, compute cost, and coverage. -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
...The focus is on readability, correctness, and experimentation, making it ideal for students and practitioners transitioning from theory to working systems. By the end, you have a grounded sense of how data pipelines, optimization, and inference interact to produce fluent text. -
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GenAI Processors
GenAI Processors is a lightweight Python library
...Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking. -
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Ring
Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI
...Its architectures and training approaches are tuned to enable efficient and capable reasoning performance. Reasoning-optimized model with reinforcement learning enhancements. Efficient architecture and memory design for large-scale reasoning. If you are located in mainland China, we also provide the model on ModelScope.cn to speed up the download process. -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer... -
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Hivemind
Decentralized deep learning in PyTorch. Built to train models
...Decentralized parameter averaging: iteratively aggregate updates from multiple workers without the need to synchronize across the entire network. Train neural networks of arbitrary size: parts of their layers are distributed across the participants with the Decentralized Mixture-of-Experts. If you have succesfully trained a model or created a downstream repository with the help of our library, feel free to submit a pull request that adds your project to the list. -
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Make-A-Video - Pytorch (wip)
Implementation of Make-A-Video, new SOTA text to video generator
...The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning points would easily apply to Imagen), make a few minor modifications for attention across time and other ways to skimp on the compute cost, do frame interpolation correctly, get a great video model out. Passing in images (if one were to pretrain on images first), both temporal convolution and attention will be automatically skipped. In other words, you can use this straightforwardly in your 2d Unet and then port it over to a 3d Unet once that phase of the training is done. -
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Panda-Helper
Panda-Helper: Data profiling utility for Pandas DataFrames and Series
Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis. -
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Starlette
The little ASGI framework that shines
Starlette is a lightweight ASGI framework/toolkit, which is ideal for building async web services in Python. It is production-ready and gives you a lightweight, low-complexity HTTP web framework. WebSocket support. In-process background tasks. Startup and shutdown events. Test client built on httpx. CORS, GZip, Static Files, streaming responses. Session and Cookie support. 100% test coverage. 100% type annotated codebase. Few hard dependencies. Compatible with asyncio and trio backends. -
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Best-of Python Developer Tools
A ranked list of awesome python developer tools and libraries
...All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! -
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Nafas
Breathing Gymnastics Application
Breathing gymnastics is a system of breathing exercises that focuses on the treatment of various diseases and general health promotion. Nafas is a collection of breathing gymnastics designed to reduce the exhaustion of long working hours. With multiple breathing patterns, Nafas helps you find your way to a detoxified energetic workday and also improves your concentration by increasing the oxygen level. No need to walk away to take a break, just sit comfortably, run Nafas and let the journey begin. Nafas means breath in Persian. -
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Learn Claude Code
Bash is all you need, write a claude code with only 16 line code
Learn Claude Code is an educational repository that teaches how modern AI coding agents work by walking learners through a sequence of progressively more complex agent implementations, starting with a minimal Bash-based agent and culminating in agents with explicit planning, subagents, and skills. It emphasizes a hands-on learning path where each version (from v0 to v4) adds conceptual building blocks like the core agent loop, todo planning, task decomposition, and domain knowledge skills,... -
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django-organizations
Multi-user accounts for Django projects
...Users can belong to and own more than one organization (account, group) Invitation and registration functionality works out of the box for many situations and can be extended as needed to fit specific requirements. Start with the base models or use your own for greater customization. Testing each change on all the environments takes some time, you may want to test faster and avoid slowing down development by using pytest against your current environment. -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. The same quantum circuit model can be run on different devices. ... -
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Wagtail
A Django content management system focused on flexibility & UX
...Built on Django, Wagtail offers precise control and flexibility for designers, developers and editors. Designed by developers for developers, Wagtail plays nicely with everything else in your tech stack so you can do more and focus on perfecting your site. Designers will find Wagtail’s simple templating system ideal for building beautiful websites just the way they want, without any CMS constraints. Editors can create beautiful, modular streams of content that they can create once and publish everywhere. Simply put, it’s the CMS that makes everyone happy!
