Search Results for "python-4suite-xml" - Page 50
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GLM-4.5V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.5V is the preceding iteration in the GLM-V series that laid much of the groundwork for general multimodal reasoning and vision-language understanding. It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding,... -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about... -
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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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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. Each day mixes explanation with at least one concrete project or lab, such as deploying applications on EC2, designing secure VPCs,... -
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BentoCache
Bentocache is a robust multi-tier caching library for Node.js app
Bentocache is a flexible caching library for Python that supports multiple backends like memory, disk, and Redis. It offers decorators for easy function-level caching and is designed to be lightweight, extensible, and developer-friendly. Bentocache is well-suited for performance optimization in web apps, scripts, and data pipelines. -
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Flint Chart
Visualization language that lets AI agents create expressive charts
...One Flint input can compile into native Vega-Lite, ECharts, or Chart.js specifications. The repository includes a TypeScript library, an MCP server, a demo site, documentation, test data, and an early Python port. It is especially useful for AI agents that need to create reliable visualizations from structured data during analysis or reporting workflows. -
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glbinding
A C++ binding for the OpenGL API, generated using the gl.xml specifica
...It provides type-safe parameters, per-feature API headers, lazy function resolution, multi-context and multi-thread support, global and local function callbacks, meta information about the generated OpenGL binding and the OpenGL runtime, as well as tools and examples for quick-starting your projects. Based on the OpenGL API specification (gl.xml) glbinding is generated using Python scripts and templates that can be easily adapted to fit custom needs. -
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PaSa
An advanced paper search agent powered by large language models
PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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Sample GenLayer project
Includes the boilerplate code for a GenLayer use case implementation
...It includes a complete working example of a prediction market application, demonstrating how developers can structure, deploy, and test decentralized logic in a real-world scenario. The project integrates both backend contract development written in Python and frontend components built with modern frameworks, enabling a seamless full-stack development workflow. It emphasizes best practices such as environment configuration, modular architecture, and comprehensive testing, helping developers avoid common pitfalls when building blockchain-based applications. The boilerplate also includes a testing framework that simulates realistic contract interactions, ensuring reliability and correctness before deployment. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and... -
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Desktop Commander MCP
AI-powered MCP server for desktop file and terminal automation
Desktop Commander MCP is an advanced Model Context Protocol server designed to extend AI assistants with direct control over a user’s local machine, including the file system and terminal. It integrates with clients like Claude Desktop to enable AI-driven workflows such as editing files, executing commands, and automating development tasks from a single conversational interface. Desktop Commander MCP builds on top of an MCP filesystem server and enhances it with powerful search, replace, and... -
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shimmy
Python-free Rust inference server
The shimmy project is a lightweight local inference server designed to run large language models with minimal overhead. Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture... -
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books-collection
To the programmer's open source and free books collection
...The collection contains both Chinese and English material, with markers identifying language and downloadable files. Topics include databases, security, Java, Go, Python, Rust, web development, JavaScript, Node.js, CSS, Linux, architecture, cloud computing, operating systems, and artificial intelligence. Entries link to official manuals, specifications, tutorials, ebooks, reference guides, and community translations. The repository acts as a discovery index rather than hosting or reading every book itself. ... -
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EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
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XLS
XLS: Accelerated HW Synthesis
XLS is an open-source toolkit for building high-level hardware with a modern compiler stack that spans from a functional DSL to optimized IR and hardware generation. At the front end, DSLX lets you describe algorithms with strong typing and familiar control flow while remaining synthesis-friendly. The compiler lowers DSLX into a rich intermediate representation, applies aggressive optimization and scheduling passes, and can either JIT the design for software simulation or emit Verilog for... -
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httpstat
It's like curl -v, with colours
Windows/BSD/Linux supported, HTTP and HTTPS supported as well. For self-signed certificates use -k, and skip timing the body of a response with -I. Follow 30x redirects with -L. Change HTTP method with -X METHOD. Provide a PUT or POST request body with -d string. To supply the PUT or POST body as a file, use -d @filename. Add extra request headers with -H 'Name: value'. The response body is usually discarded, you can use -o filename to save it to a file, or -O to save it to the file name... -
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Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a... -
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Lexbor
Lexbor is development of an open source HTML Renderer library
...Lexbor’s code is optimized for ease of access in end-user applications and across programming languages. You can effortlessly wrap all the capabilities of the library in, say, Python to power your end-user or backend applications in a new environment. In other words, lexbor offers a feature-rich core that developers can build upon as they see fit. -
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CS-Books
Collection of computer science textbooks, learning materials
CS-Books is a massive curated collection of computer science textbooks, learning materials, and resource links that covers a wide range of topics from programming languages like C/C++ and Python to core subjects such as data structures, algorithms, operating systems, databases, networks, and design patterns. The repository aggregates over a thousand classic reference books and educational resources into a single index, making it a valuable starting point for self-learners, students preparing for technical interviews, and professionals deepening their knowledge across different CS domains. ... -
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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
...It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively. -
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Project Based Learning
Curated list of project-based tutorials
project-based-learning is a community-curated open source repository that compiles programming tutorials focused on building real-world applications from scratch. It organizes resources by programming languages such as Python, Java, JavaScript, C++, Go, Rust, and many others. Each tutorial emphasizes practical, hands-on learning through project development rather than theoretical study. The collection spans various domains including web development, game programming, systems programming, and machine learning. By following the projects, learners can strengthen problem-solving skills, gain experience with different technologies, and build portfolios. ... -
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LuaUnit
LuaUnit is a popular unit-testing framework for Lua
LuaUnit is a popular unit-testing framework for Lua, with an interface typical of xUnit libraries (Python unittest, Junit, NUnit, ...). It supports several output formats (Text, TAP, JUnit, etc.) that can be used directly or work with continuous integration platforms (Jenkins, Maven, etc.). LuaUnit may be installed as a rock or directly added to your project. For simplicity, LuaUnit is contained into a single file and has no external dependency. -
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Dependabot
Dependabot's core logic for creating update PR's
Dependabot-Core is the library at the heart of Dependabot security/version updates. Use it to generate automated pull requests updating dependencies for projects written in Ruby, JavaScript, Python, PHP, Dart, Elixir, Elm, Go, Rust, Java and .NET. It can also update git submodules, Docker files, and Terraform files. Check for the latest version of a dependency that's resolvable given a project's other dependencies. Generate updated manifest and lockfiles for a new dependency version. Generate PR descriptions that include the updated dependency's changelogs, release notes, and commits.