Search Results for "python code" - Page 34
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Showing 2323 open source projects for "python code"
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Vidi2
Large Multimodal Models for Video Understanding and Editing
Vidi is a family of large multimodal models developed for deep video understanding and editing tasks, integrating vision, audio, and language to allow sophisticated querying and manipulation of video content. It’s designed to process long-form, real-world videos and answer complex queries such as “when in this clip does X happen?” or “where in the frame is object Y during that moment?” — offering temporal retrieval, spatio-temporal grounding (i.e. locating objects over time + space), and... -
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TraceRoot
Find the Root Cause in Your Code's Trace
...AI agents operate over this structured view to summarize issues, pinpoint likely root causes, and even suggest actionable fixes or draft GitHub issues and pull requests. It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context. -
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Story Flicks
Generate high-definition story short videos with one click using AI
Story Flicks is another open-source project in the AI-assisted video generation / editing space, focused on creating short, story-style videos from script or prompt inputs. It aims to let users generate high-definition short movies or video stories with minimal manual effort, using AI models under the hood to assemble visuals, timing, and possibly narration or subtitles. For creators who want to produce narrative short-form content — whether for social media, storytelling, or prototyping... -
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Patch-NetVLAD
Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
This repository contains code for the CVPR2021 paper "Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition". -
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Better Chatbot
Just a Better Chatbot. Powered by MCP Client & Workflows
Better‑chatbot is an AI chatbot framework powered by MCP protocols and workflows, allowing developers to deploy and integrate AI-powered chat systems with ease. Integrates all major LLMs: OpenAI, Anthropic, Google, xAI, Ollama, and more. MCP protocol, web search, JS/Python code execution, data visualization. Custom agents, visual workflows, artifact generation. Custom agents, visual workflows, artifact generation. Realtime voice chat with full MCP tool integration. -
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SolidGPT
Developer AI Persona Search Agent
SolidGPT is a AI searching assistant for developers that helps code and workspace semantic search. -
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ARIS
Lightweight Markdown-only skills for autonomous ML research
ARIS is an experimental automation framework that leverages AI coding agents to perform continuous research and development tasks autonomously, even without active user supervision. The system is designed to run iterative cycles of research, coding, testing, and refinement, effectively simulating a “sleep mode” where productive work continues in the background. It integrates with AI tools such as Claude Code to generate solutions, analyze results, and improve outputs over time. The project... -
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SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
SimpleHTR is an open-source implementation of a handwriting text recognition system based on deep learning techniques. The project focuses on converting images of handwritten text into machine-readable digital text using neural networks. The system uses a combination of convolutional neural networks and recurrent neural networks to extract visual features and model sequential character patterns in handwriting. It also employs connectionist temporal classification (CTC) to align predicted... -
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LLMs-Zero-to-Hero
From nobody to big model (LLM) hero
LLMs-Zero-to-Hero is an open-source educational project designed to guide learners through the complete process of understanding and building large language models from the ground up. The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement... -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer... -
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Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
Hugging Face Skills is a repository of standardized task definitions that package instructions, scripts, and resources so coding agents can reliably perform AI and machine learning workflows. Each skill is a self-contained folder with structured metadata and guidance that tells an agent how to execute tasks such as dataset creation, model training, evaluation, or Hub operations. The project is designed to be interoperable across major agent ecosystems, including Claude Code, OpenAI Codex,... -
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they... -
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Tally
Let agents classify your bank transactions
Tally is an open-source, AI-assisted tool designed to automate the classification of personal financial transactions, helping users turn raw bank data into meaningful categories without manual tagging. At its core, Tally pairs a local rule engine with large language models so that an AI assistant (like Claude Code, Copilot, or any CLI agent) interprets, suggests, and categorizes expenses, savings, subscriptions, and income events based on your own rules and behavior. It generates... -
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D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
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llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and... -
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MobileCLIP
Implementation of "MobileCLIP" CVPR 2024
MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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mergekit
Tools for merging pretrained large language models
mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of... -
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OctoBot
Cryptocurrency trading bot for TA, arbitrage and social trading
OctoBot is a trading robot that is designed to be easy to use and infinitely customizable. OctoBot is built for people who don't have much time or do not easily trust crypto-world projects. Many trading automation tools exist but most of them are complicated to use, expensive, do not behave as intended, or are meant to be used by professional traders. Moreover, when a favorable trend is spotted, it can be difficult to maximize profit from it: trading takes a lot of time, and when it's done... -
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Laminar
Open-source all-in-one platform for engineering AI products
Laminar is an open source all-in-one platform for engineering best-in-class LLM products. Data governs the quality of your LLM application. Laminar helps you collect it, understand it, and use it. When you trace your LLM application, you get a clear picture of every step of execution and simultaneously collect invaluable data. You can use it to set up better evaluations, as dynamic few-shot examples, and for fine-tuning. All traces are sent in the background via gRPC with minimal overhead.... -
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handson-ml
Teaching you the fundamentals of Machine Learning in python
handson-ml hosts the notebooks for the first edition of the same hands-on ML book, reflecting the tooling and idioms of its time while teaching durable concepts. It walks through supervised and unsupervised learning with scikit-learn, then introduces deep learning using the earlier TensorFlow 1 graph-execution style. The examples underscore fundamentals like bias-variance trade-offs, regularization, and proper validation, grounding learners before they move to deep nets. Even though the deep... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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OGRE
scene-oriented, flexible 3D engine (C++, Python, C#, Java)
OGRE (Object-Oriented Graphics Rendering Engine) is a scene-oriented, flexible 3D engine written in C++ designed to make it easier and more intuitive for developers to produce games and demos utilizing 3D hardware. The class library abstracts all the details of using the underlying system libraries like Direct3D and OpenGL and provides an interface based on world objects and other intuitive classes. We consider the results of our GL3Plus RenderSystem as the gold standard. The respective... -
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spdlog
Fast C++ logging library
spdlog is a header only library. Just copy the files under include to your build tree and use a C++11 compiler. It provides a python like formatting API using the bundled fmt lib. spdlog takes the "include what you need" approach, your code should include the features that actually needed. For example, if you only need rotating logger, you need to include "spdlog/sinks/rotating_file_sink.h". spdlog provides various log targets, which are, rotating log files, daily log files, console logging (colors supported), syslog, Windows event log, and Windows debugger (OutputDebugString(..)). ...
