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Showing 12506 open source projects for "compiler python linux"
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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Dragonfly | An In-Memory Data Store without LimitsDragonfly is a drop-in Redis replacement that is designed for heavy data workloads running on modern cloud hardware. Migrate in less than a day and experience up to 25X the performance on half the infrastructure.
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UnROOT.jl
Native Julia I/O package to work with CERN ROOT files objects
UnROOT.jl is a reader for the CERN ROOT file format written entirely in Julia, without any dependence on ROOT or Python. -
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Qulacs
Variational Quantum Circuit Simulator for Quantum Computation Research
Variational Quantum Circuit Simulator for Quantum Computation Research. Qulacs is a Python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. Qulacs is developed at QunaSys, Osaka University, NTT, and Fujitsu. -
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Hoverfly
Lightweight service virtualization/ API simulation / API mocking tool
...Using Hoverfly, you can create realistic simulations of the APIs your application depends on. Replace unreliable test systems and restrictive API sandboxes with high-performance simulations in seconds. Run on MacOS, Windows or Linux, or use native Java or Python language bindings to get started quickly. Simulate API latency or failure when required by writing custom scripts in the language of your choice. -
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AWS IoT Device Defender Library
Client library for using AWS IoT Defender service on embedded devices
The Device Defender library enables you to send device metrics to the AWS IoT Device Defender Service. This library also supports custom metrics, a feature that helps you monitor operational health metrics that are unique to your fleet or use case. For example, you can define a new metric to monitor the memory usage or CPU usage on your devices. This library has no dependencies on any additional libraries other than the standard C library, and therefore, can be used with any MQTT client... -
The Comprehensive School Dismissal SolutionPikMyKid is the first and only safe & smart dismissal solution for school districts, charter/private schools, after-school programs, YMCAs, JCCs, Summer camps, and daycare facilities. It connects schools, teachers, and parents through real-time tools to make dismissals safer and more efficient. PikMyKid schools are able to confidently organize their dismissals with ease and no longer rely on paper notes or tedious phone calls to the front office.
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and... -
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Blik
Self hosted & open source anonymous 360 review software
Blik is an open source, self-hosted platform for anonymous 360-degree feedback and performance review cycles, built with a strong focus on privacy, transparency, and developer-friendly deployment. It allows organizations to run review cycles where employees get anonymous feedback from peers, managers, and direct reports, without vendor lock-in or per-user licensing costs. The system is built using the Django framework, with a PostgreSQL backend, and is packaged for easy deployment via Docker... -
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Stable Diffusion WebUI Forge
Stable Diffusion WebUI Forge is a platform on top of Stable Diffusion
Stable Diffusion WebUI Forge is a performance- and feature-oriented fork of the popular AUTOMATIC1111 interface that experiments with new backends, memory optimizations, and UX improvements. It targets heavy users and researchers who push large models, control nets, and high-resolution pipelines where default settings can become bottlenecks. The fork typically introduces toggles for scheduler behavior, attention implementations, caching, and precision modes to reach better speed or quality... -
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Pixelization
Stable-diffusion-webui-pixelization
This is a specialized extension for the popular Stable Diffusion Web UI (AUTOMATIC1111) that focuses on converting or “pixelizing” images into a pixel-art aesthetic. It's designed as a plugin you install into the Web UI so that in the “Extras” or “Pixelization” tab you can drag in an input image and produce a stylized, block-based version with control over cell size, color depth, and segmentation. The extension uses pre-trained models and optionally can co-operate with the Web UI’s other... -
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Janus
Unified Multimodal Understanding and Generation Models
Janus is a sophisticated open-source project from DeepSeek AI that aims to unify both visual understanding and image generation in a single model architecture. Rather than having separate systems for “look and describe” and “prompt and generate”, Janus uses an autoregressive transformer framework with a decoupled visual encoder—allowing it to ingest images for comprehension and to produce images from text prompts with shared internal representations. The design tackles long-standing... -
Connecteam Employee Management SoftwareConnecteam is an award-winning all-in-one employee management solution for daily operations, communications, and human resource management.
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OSS-Fuzz Gen
LLM powered fuzzing via OSS-Fuzz
OSS-Fuzz-Gen is a companion project that helps automatically create or improve fuzz targets for open-source codebases, aiming to increase coverage in OSS-Fuzz with minimal maintainer effort. It analyses a library’s APIs, examples, and tests to propose harnesses that exercise parsers, decoders, or protocol handlers—precisely the code where fuzzing pays off. The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage... -
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BIG-bench
Beyond the Imitation Game collaborative benchmark for measuring
BIG-bench (Beyond the Imitation Game Benchmark) is a large, collaborative benchmark suite designed to probe the capabilities and limitations of large language models across hundreds of diverse tasks. Rather than focusing on a single metric or domain, it aggregates many hand-authored tasks that test reasoning, commonsense, math, linguistics, ethics, and creativity. Tasks are intentionally heterogeneous: some are multiple-choice with exact scoring, others are free-form generation judged by... -
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Petri
An alignment auditing agent capable of exploring alignment hypothesis
Petri is an open-source alignment auditing agent that lets researchers rapidly test concrete safety hypotheses against target models using realistic, multi-turn scenarios. Instead of building bespoke evals, Petri automatically generates audit environments from seed “special instructions,” orchestrates an auditor model to probe a target model, and simulates tool use and rollbacks to surface risky behaviors. Each interaction transcript is then scored by a judge model using a consistent rubric... -
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FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools
fastapi_mcp lets you expose existing FastAPI endpoints as Model Context Protocol (MCP) tools with minimal setup, so AI agents can call your app as first-class tools. Rather than acting as a thin converter, it’s built as a native FastAPI extension that understands dependency injection, so you can reuse Depends() for authentication and authorization across your MCP tools. The server speaks directly to your app over its ASGI interface, avoiding extra HTTP hops between the MCP layer and your... -
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fvcore
Collection of common code shared among different research projects
fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A... -
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vJEPA-2
PyTorch code and models for VJEPA2 self-supervised learning from video
VJEPA2 is a next-generation self-supervised learning framework for video that extends the “predict in representation space” idea from i-JEPA to the temporal domain. Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The... -
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically... -
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Claude Code Security Review
An AI-powered security review GitHub Action using Claude
The claude-code-security-review repository implements a GitHub Action that uses Claude (via the Anthropic API) to perform semantic security audits of code changes in pull requests. Rather than relying purely on pattern matching or static analysis, this action feeds diffs and surrounding context to Claude to reason about potential vulnerabilities (e.g. injection, misconfigurations, secrets exposure, etc). When a PR is opened, the action analyzes only the changed files (diff-aware scanning),... -
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Automated Interpretability
Code for Language models can explain neurons in language models paper
The automated-interpretability repository implements tools and pipelines for automatically generating, simulating, and scoring explanations of neuron (or latent feature) behavior in neural networks. Instead of relying purely on manual, ad hoc interpretability probing, this repo aims to scale interpretability by using algorithmic methods that produce candidate explanations and assess their quality. It includes a “neuron explainer” component that, given a target neuron or latent feature,... -
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Evals
Evals is a framework for evaluating LLMs and LLM systems
The openai/evals repository is a framework and registry for evaluating large language models and systems built with LLMs. It’s designed to let you define “evals” (evaluation tasks) in a structured way and run them against different models or agents, with the ability to score, compare, and analyze results. The framework supports templated YAML eval definitions, solver-based evaluations, custom metrics, and composition of multi-step evaluations. It includes utilities and APIs to plug in... -
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ChatGPT Retrieval Plugin
The ChatGPT Retrieval Plugin lets you easily find personal documents
The chatgpt-retrieval-plugin repository implements a semantic retrieval backend that lets ChatGPT (or GPT-powered tools) access private or organizational documents in natural language by combining vector search, embedding models, and plugin infrastructure. It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge... -
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OpenAI Swarm
Educational framework exploring multi-agent orchestration
Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions; Agents and handoffs. An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning... -
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
Qwen2.5-Math is a series of mathematics-specialized large language models in the Qwen2 family, released by Alibaba’s QwenLM. It includes base models (1.5B / 7B / 72B parameters), instruction-tuned versions, and a reward model (RM) to improve alignment. Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical... -
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Super Tiny Icons
Super Tiny Icons are miniscule SVG versions of your favourite website
SuperTinyIcons is a collection of brand and service logos distilled into extremely small, hand-tuned SVGs, often targeting sub-kilobyte file sizes. Each icon is crafted to preserve recognizable shapes with the fewest possible paths and nodes, trading photorealism for clarity at common UI sizes. The project emphasizes performance: tiny inline SVGs reduce network transfer, speed up rendering, and scale crisply on high-DPI displays. Designers and developers can embed the icons directly, recolor... -
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,... -
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Habitat-Lab
A modular high-level library to train embodied AI agents
Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks. Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. Configuring and...
