Showing 409 open source projects for "key"

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  • 1
    Bootstrap Your Own Latent (BYOL)

    Bootstrap Your Own Latent (BYOL)

    Usable Implementation of "Bootstrap Your Own Latent" self-supervised

    ...This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. Simply plugin your neural network, specifying (1) the image dimensions as well as (2) the name (or index) of the hidden layer, whose output is used as the latent representation used for self-supervised training.
    Downloads: 0 This Week
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  • 2
    zvt

    zvt

    Modular quant framework

    For practical trading, a complex algorithm is fragile, a complex algorithm building on a complex facility is more fragile, complex algorithm building on a complex facility by a complex team is more and more fragile. zvt wants to provide a simple facility for building a straightforward algorithm. Technologies come and technologies go, but market insight is forever. Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt....
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  • 3
    oscar

    oscar

    Domain-driven eCommerce for Django

    ...Oscar makes few assumptions about your project, allowing virtually any part of the framework to be extended and customized. In this way, complex business rules can be captured in an elegant and cohesive way. Any class can be overridden, replaced and extended. This is the key feature that allows any project to be captured accurately in the codebase, no workarounds! A well-designed set of models built on the experience of many e-commerce projects, both large and small. Comprehensive documentation including recipes for solving common problems. Handling of a catalogue of around 15 million products, with stock provided by a range of international partners. ...
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  • 4
    MiniCPM4.1

    MiniCPM4.1

    Achieving 3+ generation speedup on reasoning tasks

    ...It builds upon the same efficiency-focused philosophy but further optimizes decoding performance, achieving substantial speed gains in reasoning-intensive tasks while maintaining high-quality outputs. One of its key innovations is the hybrid reasoning mode, which allows developers to control whether the model engages in deeper reasoning processes or faster responses depending on the use case. The model also supports both dense and sparse attention mechanisms, enabling more efficient computation depending on the selected inference framework. With improved pretraining on longer sequences and enhanced scaling techniques, MiniCPM4.1 delivers better performance in long-context tasks and complex problem solving.
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  • 5
    PyQt-SiliconUI

    PyQt-SiliconUI

    A powerful and artistic UI library based on PyQt5

    ...It also provides core modules for animations, event handling, and custom painting, enabling developers to create smooth, interactive desktop experiences beyond standard PyQt capabilities. A key aspect of the project is its ongoing refactoring effort, which aims to modernize components, improve performance, and replace older implementations with more stable and maintainable versions.
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  • 6
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    ...The framework is built around the concept of an Agent Development Kit (ADK), providing structured components for memory, reasoning, and task decomposition while allowing agents to iteratively improve their own design. A key innovation is its hierarchical and graph-based memory system, which enables agents to store, retrieve, and organize information across complex workflows with improved efficiency and contextual awareness.
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  • 7
    AgentEvolver

    AgentEvolver

    Towards Efficient Self-Evolving Agent System

    ...The system focuses on improving the efficiency and scalability of training autonomous agents by allowing them to generate tasks, explore environments, and refine strategies without heavy reliance on manually curated datasets. Its architecture combines reinforcement learning with LLM-driven reasoning mechanisms to guide exploration and learning. The framework introduces several key mechanisms, including self-questioning to create new learning tasks, self-navigating to improve exploration through experience reuse, and self-attributing to assign rewards based on the usefulness of actions. These mechanisms enable agents to continuously improve their capabilities while interacting with complex environments and tools. ...
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  • 8
    sqlit

    sqlit

    A user friendly TUI for SQL databases

    sqlit is a keyboard-first terminal UI that lets you connect to, browse, and query SQL databases quickly without relying on heavyweight GUI clients. It positions itself as a “lazygit-style” experience for databases, aiming for fast startup, intuitive navigation, and developer-friendly workflows directly inside your terminal. The tool supports a wide range of database providers, so you can use one interface across local databases, remote servers, and cloud-hosted instances rather than juggling...
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  • 9
    LLM TLDR

    LLM TLDR

    95% token savings. 155x faster queries. 16 languages

    ...The system supports both extractive and abstractive summarization styles so that users can choose whether they want condensed highlights or a more narrative paraphrase of key ideas. To enhance usability, LLM-TLDR includes command-line tools and integration examples for common workflows like batch summarization, webhook ingestion, and automation in documentation pipelines.
    Downloads: 0 This Week
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  • 10
    Perfect Pixel

    Perfect Pixel

    Refine and quantize messy AI pixel art into clean, perfect pixels

    ...This makes it useful for game developers, sprite artists, and hobbyists who want to use AI-assisted ideation without shipping “almost pixel art” assets. It is designed to be easy to slot into an existing pipeline, whether you are batch-processing images or cleaning up a few key assets for a project.
    Downloads: 0 This Week
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  • 11
    RLax

    RLax

    Library of JAX-based building blocks for reinforcement learning agents

    ...The library implements tools for Bellman equations, return distributions, general value functions, and policy optimization in both continuous and discrete action spaces. It integrates seamlessly with DeepMind’s Haiku (for neural network definition) and Optax (for optimization), making it a key component in modular RL pipelines.
    Downloads: 0 This Week
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  • 12
    LMCache

    LMCache

    Supercharge Your LLM with the Fastest KV Cache Layer

    LMCache is an extension layer for LLM serving engines that accelerates inference, especially with long contexts, by storing and reusing key-value (KV) attention caches across requests. Instead of rebuilding KV states for repeated or shared text segments, LMCache persists and retrieves them from multiple tiers—GPU memory, CPU DRAM, and local disk—then injects them into subsequent requests to reduce TTFT and increase throughput. Its design supports reuse beyond strict prefix matching and enables sharing across serving instances, improving efficiency under real multi-tenant traffic. ...
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  • 13
    xFormers

    xFormers

    Hackable and optimized Transformers building blocks

    ...It abstracts components like attention layers, feedforward modules, normalization, and positional encoding, so you can mix and match or swap optimized kernels easily. One of its key goals is efficient attention: it supports dense, sparse, low-rank, and approximate attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. ...
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  • 14
    Mem0

    Mem0

    The Memory layer for AI Agents

    Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by leveraging historical context, and offering easy integration compatible with platforms like OpenAI and Claude. ...
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  • 15
    Argilla

    Argilla

    The open-source data curation platform for LLMs

    ...In fact, you can use and combine your preferred libraries without implementing any specific interface. Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Argilla is designed to close this gap, enabling you to iterate as much as you need.
    Downloads: 0 This Week
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  • 16
    Django Two-Factor Authentication

    Django Two-Factor Authentication

    Complete Two-Factor Authentication for Django

    ...Test drive this app through the example app. It demos most features except the Twilio integration. The example also includes django-user-sessions for providing Django sessions with a foreign key to the user.
    Downloads: 0 This Week
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  • 17
    Cobbler

    Cobbler

    Cobbler is a versatile Linux deployment server

    ...Cobbler can help with provisioning, managing DNS and DHCP, package updates, power management, configuration management orchestration, and much more. Automation is the key to speed, consistency and repeatability. These properties are critical to managing infrastructure, whether it is comprised of a few servers or a few thousand servers. Cobbler helps by automating the process of provisioning servers from bare metal, or when deploying virtual machines onto various hypervisors. Just as configuration management systems rely on templates to simplify updates, so too does Cobbler.
    Downloads: 0 This Week
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  • 18
    AWS ParallelCluster Node

    AWS ParallelCluster Node

    Python package installed on the Amazon EC2 instances

    aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources...
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  • 19
    Downloads: 2 This Week
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  • 20
    JamAI Base

    JamAI Base

    The collaborative spreadsheet for AI

    ...It includes built-in orchestration for large language models, vector search, and reranking pipelines so that AI applications can retrieve relevant information before generating responses. JamAI Base exposes its functionality through a simple REST API and a spreadsheet-style interface that allows users to manage AI workflows visually. One of the key ideas behind the platform is the concept of generative tables, which allow database columns to automatically populate with AI-generated content. The system also supports action tables and chat tables that simplify the creation of interactive AI features such as conversational interfaces and dynamic workflows.
    Downloads: 0 This Week
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  • 21
    BackAnt CLI

    BackAnt CLI

    Let your AI agent create clean, easy to maintain flask backends

    BackAnt CLI is an AI-native backend scaffolding tool designed to generate production-ready Flask APIs from a JSON specification or a small set of CLI commands. Its main goal is to reduce the repetitive work involved in setting up layered backend projects by generating key application components automatically rather than forcing developers to assemble them by hand. The tool creates a structured backend architecture that includes routes, services, repositories, models, startup files, Docker Compose configurations, and CI/CD workflows, which makes it especially useful for teams that want consistency across projects. ...
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  • 22
    handy-ollama

    handy-ollama

    Implement CPU from scratch and play with large model deployments

    ...The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based inference pipelines. The project includes step-by-step guides that walk learners through tasks such as installing Ollama, managing local models, calling model APIs, and building simple AI applications on top of locally hosted models. ...
    Downloads: 0 This Week
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  • 23
    TextFSM

    TextFSM

    Python module for parsing semi-structured text into python tables

    ...By defining parsing logic through reusable template files, TextFSM transforms unstructured text into structured data like lists or tables without requiring complex regular expression code. Each template defines states, transitions, and regex patterns that determine how to interpret text line by line, enabling precise extraction of key information from varied sources. This modular approach allows users to maintain a library of templates for different data formats, improving automation in network operations and system administration. Widely used in network automation workflows, TextFSM integrates easily with Python scripts, making it an essential tool for engineers.
    Downloads: 0 This Week
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  • 24
    Dough

    Dough

    Dough is a open source tool for steering AI animations with precision

    We believe that AI has the potential to allow billions to experience creative fulfillment this century. However, in order to reach this potential, artistic control is key - it's the difference between something feeling like it was made by you rather than for you. To unlock the multitude of control types and artistic flows possible with AI, we want to build tooling and infrastructure to empower a community of tool-builders, who in turn empower a world of budding artists. If you have a powerful computer, you can run Dough locally for free. ...
    Downloads: 0 This Week
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  • 25
    Every Code

    Every Code

    Local AI coding agent CLI with multi-agent orchestration tools

    ...Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. Customization is a key focus, with support for theming, configurable settings, and reasoning controls that allow developers to fine-tune how the agent behaves.
    Downloads: 0 This Week
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