Search Results for "common" - Page 35
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Showing 6265 open source projects for "common"
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. ... -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can... -
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Graph NotebookAmazon GameLift Unity
Access GameLift resources and integrate GameLift into your Unity game
The Amazon GameLift Plugin for Unity contains libraries and native UI that makes it easier to access GameLift resources and integrate GameLift into your Unity game. You can use the GameLift Unity Plugin to access GameLift APIs and deploy AWS CloudFormation templates for common gaming scenarios. Auth Only, this scenario creates a game backend service that performs only player authentication and no game server capability. It creates a Cognito user pool to store player authentication information, as well as an API gateway REST endpoint backed up AWS Lambda handlers to start a game and view game connection information. ... -
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NeoPixelBus
An Arduino NeoPixel support library
...RMT timing currently is sensitive to high interrupt frequency due to issues in the Core. There are multiple competing libraries, FastLED being the biggest and Adafruit NeoPixel being the most common for beginners. On ESP32, both FastLED and NeoPixelBus can provide more than one channel/bus. FastLED primarily uses RMT to support 8 parallel channels. NeoPixelBus now supports the RMTs 8 channels and two more channels using i2s. -
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rollama
Wrap the Ollama API, which allows you to run different LLMs
...The package emphasizes reproducibility and privacy by enabling local execution of models, which is especially valuable for sensitive or research-oriented workflows. It supports common LLM tasks such as text generation, annotation, and embedding creation, making it useful for tasks like document analysis and data labeling. The design mirrors familiar R workflows, allowing users to integrate AI capabilities into scripts, notebooks, and data pipelines with minimal friction. It also provides flexibility to extend functionality to any feature supported by the underlying Ollama API. -
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Responsible AI Toolbox
Responsible AI Toolbox is a suite of tools providing model
...The project provides tools that assist in analyzing model behavior, detecting bias, improving robustness, and explaining predictions produced by AI systems. It is designed to integrate with common machine learning frameworks, especially PyTorch, allowing developers to apply responsible AI techniques within existing workflows. The toolbox includes methods for adversarial testing, interpretability analysis, and model diagnostics that help developers understand how models behave under different conditions. These capabilities are particularly important for high-impact domains where AI systems must meet strict reliability and fairness requirements. ... -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. ... -
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Open SaaS
Open source SaaS boilerplate for React, NodeJS apps with Wasp stack
...It is built on the Wasp full stack framework, which combines React, NodeJS, and Prisma to manage both client and server code within a unified architecture. Open SaaS provides a production-ready foundation that includes common SaaS functionality such as authentication, payments, analytics, and file uploads. Developers can use it as a boilerplate to avoid writing repetitive setup code and instead focus on building product features. It integrates several commonly used services and tools, including payment processing systems, email providers, analytics platforms, and AI integrations. ... -
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory... -
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Ploomber
The fastest way to build data pipelines
...It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. Ploomber automatically manages task dependencies and execution order, allowing complex pipelines with multiple stages to run reliably. The framework can deploy pipelines across different computing environments including Kubernetes, Airflow, AWS Batch, and high-performance computing clusters. ... -
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DotnetSpider
Lightweight .NET framework for fast web crawling and data scraping
DotnetSpider is a web crawling and data extraction framework built on the .NET Standard platform. It is designed to help developers create efficient and scalable crawlers for collecting structured data from websites. It provides a high-level API that simplifies the process of defining spiders, managing requests, and extracting content from web pages. Developers can create custom spiders by extending base classes and configuring pipelines that handle downloading, parsing, and storing... -
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Pydoll
Async Python library in automating Chromium browsers without WebDriver
...Instead of using external drivers, it connects directly to the Chrome DevTools Protocol through WebSocket, allowing scripts to control browser behavior more efficiently and with fewer compatibility issues. It provides a high-level API that simplifies common browser automation tasks while still offering access to low-level protocol features for advanced control. Its architecture is built around asynchronous programming using Python’s asyncio framework, enabling concurrent automation of multiple tabs and browser contexts. Pydoll also includes tools for monitoring and intercepting network traffic, allowing developers to analyze or modify requests and responses during automation workflows. ... -
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AI CODE GUIDE
AI Code Guide is a roadmap to start coding with AI
...Instead of focusing on a single framework or technology, the guide aggregates information about a wide ecosystem of tools including AI code editors, development platforms, and programming assistants. It also highlights best practices and common pitfalls developers may encounter when relying on AI tools in software engineering workflows. -
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dnstwist
Detects phishing and lookalike domains using DNS fuzzing techniques
...It works by generating a large set of domain name permutations based on a target domain and analyzing whether any of those variants are actively registered or used. These permutations simulate common techniques used in phishing attacks, typosquatting, and brand impersonation campaigns. Security teams can use the tool to discover potential threats where attackers attempt to deceive users with lookalike domains. dnstwist also helps detect phishing activity by comparing web page content and visual similarity between domains using fuzzy hashing and perceptual hashing techniques. ... -
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Intel LLM Library for PyTorch
Accelerate local LLM inference and finetuning
...IPEX-LLM supports a wide range of popular models, including architectures such as LLaMA, Mistral, Qwen, and other transformer-based systems. The library can integrate with common AI frameworks and serving tools such as Hugging Face Transformers, LangChain, and vLLM, allowing developers to incorporate optimized inference into existing pipelines. -
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PowerInfer
High-speed Large Language Model Serving for Local Deployment
...Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into GPU memory while processing less common activations on the CPU. This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. PowerInfer incorporates specialized algorithms and sparse operators to manage neuron activation patterns and minimize data transfers between hardware components. As a result, it enables powerful language models to run on consumer hardware while achieving performance comparable to more expensive server-grade systems. -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live runtime context — to generate SQL queries that are both technically correct and semantically meaningful. ... -
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Mydia
Your personal media companion, built with Phoenix LiveView
...The system supports automation workflows around acquiring and managing media, including quality profiles and smarter release selection, so it can act as a hub rather than just a catalog. It integrates with common download clients and indexers, enabling an end-to-end workflow where requests, discovery, and acquisition are connected through a single interface. Mydia also supports multi-user setups with roles and request workflows, making it usable in households or shared servers without giving everyone full administrative power. -
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Sygil WebUI
Stable Diffusion web UI
Sygil WebUI is a browser-based interface for running Stable Diffusion image generation locally or on a server, wrapping common text-to-image and image-to-image workflows into a practical UI. It provides multiple UI modes (including a legacy Gradio interface) and focuses on making iterative prompting, parameter tuning, and post-processing accessible without writing code. The UI exposes core generation controls like resolution, CFG guidance, sampling steps, samplers, seeds, and batch generation so users can reproduce results and refine outputs systematically. ... -
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RSC Explorer
A tool for people curious about the React Server Components protocol
RSC Explorer is an educational, experiment-friendly tool for understanding the React Server Components (RSC) protocol by making the streaming process visible and inspectable. It runs both the “server” and “client” sides of RSC in the browser, removing the need to set up a full backend just to learn how the protocol behaves. The core experience is the ability to step through the RSC stream incrementally, seeing what data arrives at each moment and how that data maps to the React tree being... -
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History LLMs
Information hub for our project training the largest possible LLMs
...The History LLMs aim to be trained on massive curated datasets of time-stamped documents so that the resulting models can offer responses grounded only in the knowledge available before their cutoff, such as 1913, thereby avoiding hindsight contamination common in modern LLMs. This approach enables researchers in the humanities and social sciences to explore how people at different historical moments would have discussed world events, norms, and ideas without later developments influencing the model. It contains documentation about model families like Ranke-4B, which are trained from scratch with historical corpora and can act as “aggregate witnesses” to the textual culture of their era. -
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ticket
Fast, powerful, git-native ticket tracking in a single bash script
...It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. Its design is rooted in the Unix philosophy of simplicity, composability, and transparency, meaning it integrates well with other standard tools like grep, jq, and ripgrep when installed. ... -
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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. -
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Learn Go
Master the fundamentals and advanced features of the Go language
...It also anchors learning in credible references, pointing to official documentation, the Go blog, and widely used learning resources. In practice, it serves as a guided path you can follow linearly or revisit as a reference when you hit common Go questions in day-to-day work. -
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Menubar Electron
High level way to create menubar desktop applications with electron
Menubar Electron is a lightweight JavaScript library for creating desktop applications with persistent menu bar (Mac) or system tray (Windows/Linux) icons/interfaces, allowing developers to build utility apps that live in the user’s system bar and open a small window or popup when clicked. It serves as a wrapper around frameworks like Electron or Node GUI backends, abstracting common tasks such as positioning the popup window, handling click events, and integrating native tray interactions without writing platform-specific code. The library makes it easy to build cross-platform utilities like clipboard managers, quick note popups, status displays, or background tools that users access from the bar icon without filling taskbars or docks. menubar handles the lifecycle of the UI window, system tray icon, and related events so developers can focus on the application logic rather than boilerplate integration.
