Search Results for "weight" - Page 2
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Showing 798 open source projects for "weight"
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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Agenda
Lightweight job scheduling for Node.js
A light-weight job scheduling library for Node.js. -
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PolyChaos.jl
Julia package to construct orthogonal polynomials
PolyChaos is a collection of numerical routines for orthogonal polynomials written in the Julia programming language. Starting from some non-negative weight (aka an absolutely continuous nonnegative measure). -
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Hugo Book Theme
Hugo documentation theme as simple as plain book
Hugo documentation theme as simple as a plain book. By default, the theme will render pages from the content/docs section as a menu in a tree structure. You can set title and weight in the front matter of pages to adjust the order and titles in the menu. There are a few configuration options that you can add to your config.toml file. A simple blog is supported in the section posts. A blog is not the primary use case of this theme, so it has only minimal features. The theme supports Hugo's multilingual mode, just follow the configuration guide there. ... -
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real repositories and diverse programming languages. ... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Monster Mash
New Sketch-Based Modeling and Animation Tool
...You sketch a silhouette and interior strokes to hint at limbs or structure, then “inflate” the drawing into a volumetric, puppet-like mesh that preserves the feel of the original art. The interface favors immediacy: draw, inflate, pose, and record motion directly in the canvas, without manual rigging, weight painting, or complicated asset pipelines. Under the hood it builds a lightweight surface and auto-assigns handles so you can grab and move parts intuitively, with smooth deformations propagating across the body. Because it runs interactively, artists iterate rapidly—blocking poses, trying alternate proportions, or recording short performances—before exporting results downstream. ... -
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Gemma Chat
Local AI chat + coding agent for Apple Silicon, powered by Gemma 4
Gemma Chat is a local-first AI chat and coding assistant designed to run fully on-device, particularly optimized for Apple Silicon machines. It leverages Google’s Gemma family of lightweight language models, which are built on the same underlying technology as Gemini and designed for efficient local inference and reasoning tasks. The project enables users to interact with AI through a chat interface while also supporting code generation and editing workflows. It emphasizes privacy and... -
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SparkyFitness
Track food, fitness, water, and health
...It provides tools for logging daily meals with nutritional breakdowns, tracking workouts with an extensive exercise database, and visualizing long-term progress using interactive charts and reports. The system also supports water intake goals, body metric logging (such as weight and measurements for different muscle groups), and customizable goals to help users stay motivated and accountable. An AI-powered nutrition coach is included, allowing users to log food, exercise, and steps through natural language chat and even upload food images for automatic analysis. SparkyFitness includes secure user authentication and profile management, supports multiple user accounts, and can be deployed via Docker or traditional hosting setups. -
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Groq Desktop
Local Groq Desktop chat app with MCP support
Groq Desktop is a cross-platform (Windows / macOS / Linux) local desktop application that provides a graphical chat interface for interacting with Groq-hosted, function-call-capable models. It bundles a built-in MCP (Model Context Protocol) server enabling smart function calling, letting users chat with an AI, send images, or interact with richer multimodal inputs — all from a friendly desktop UI. The app is built with modern web technologies and packaged for native distribution, making it... -
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CoordinateTransformations.jl
A fresh approach to coordinate transformations
...Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes it easy to perform optimization and therefore ideal for computer vision applications such as SLAM (simultaneous localization and mapping). -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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H2O
The optimized HTTP1, HTTP2, and HTTP3 server
...Designed from ground-up, the server takes full advantage of HTTP/2 features including prioritized content serving and server push, promising outstanding experience to the visitors of your web site. Full support for dependency and weight-based prioritization with server-side tweaks. Static file serving, FastCGI, reverse proxy, scriptable using mruby (Rack-based), graceful restart and self-upgrade, BPF-based tracing tool (experimental), and more. H2O is a new generation HTTP server. Not only is it very fast, it also provides much quicker response to end-users when compared to older generations of HTTP servers. ... -
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Get Shit Done
A light-weight and powerful meta-prompting, context engineering
Get Shit Done is a high-impact, open-source meta-prompting and spec-driven development system designed to streamline building software with AI assistants like Claude Code, OpenCode, and Gemini CLI. It solves “context rot” — the degradation of AI quality as a chat session grows — by structuring your idea into precise, context-engineered steps that are researched, scoped, planned, executed, and verified with clear commands and outputs instead of ad-hoc prompts. The project emphasizes... -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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RTP-LLM
Alibaba's high-performance LLM inference engine for diverse apps
RTP-LLM is an open-source large language model inference acceleration engine developed by Alibaba to provide high-performance serving infrastructure for modern LLM deployments. The system focuses on improving throughput, latency, and resource utilization when running large models in production environments. It achieves this by implementing optimized GPU kernels, batching strategies, and memory management techniques tailored for transformer inference workloads. The framework is designed for... -
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Laravel Love
Add Social Reactions to Laravel Eloquent Models
Laravel Love is the emotional part of the application. It lets people express how they feel about the content. Make any model reachable in minutes. This package was developed in mind that it should cover all the possible use cases and be viable in enterprise applications. Fully customizable types of reactions. Any model can react to models and receive reactions at the same time. Reactants can have many types of reactions. Reacter can add many reactions to one reactant. Reacter can react with... -
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MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
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Open Source API Firewall by Wallarm
Fast and light-weight API proxy firewall for request and response
API Firewall is a high-performance proxy with API request and response validation based on OpenAPI/Swagger schema. It is designed to protect REST API endpoints in cloud-native environments. API Firewall provides API hardening with the use of a positive security model allowing calls that match a predefined API specification for requests and responses, while rejecting everything else. -
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Attention Residuals (AttnRes)
Drop-in replacement for standard residual connections in Transformers
...In standard transformers, residual connections simply sum outputs from previous layers, which can lead to uncontrolled growth of hidden states and dilution of early-layer information in deep networks. Attention Residuals introduces a learnable softmax attention mechanism that allows each layer to selectively retrieve and weight useful representations from earlier layers, making depth dynamically adaptive rather than uniformly aggregated. This approach improves gradient stability, preserves meaningful signals throughout the network, and enhances performance in reasoning-heavy tasks such as coding, mathematics, and multi-step problem solving. -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
...For users accessing gpt-oss through third-party providers like HuggingFace, Ollama, or vLLM, Harmony formatting is handled automatically, but developers building custom inference setups must implement it directly. With its flexible design, Harmony serves as the foundation for creating more interpretable, controlled, and extensible interactions with open-weight language models. -
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Bolt NLP
Bolt is a deep learning library with high performance
Bolt is a high-performance deep learning inference framework developed by Huawei Noah's Ark Lab. It is designed to optimize and accelerate the deployment of deep learning models across various hardware platforms. Bolt is a light-weight library for deep learning. Bolt, as a universal deployment tool for all kinds of neural networks, aims to automate the deployment pipeline and achieve extreme acceleration. Bolt has been widely deployed and used in many departments of HUAWEI company, such as 2012 Laboratory, CBG and HUAWEI Product Lines. If you have questions or suggestions, you can submit issue. -
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labwc
A Wayland window-stacking compositor
Labwc is a wlroots-based window-stacking compositor for Wayland, inspired by Openbox. It is light-weight and independent with a focus on simply stacking windows well and rendering some window decorations. It takes a no-bling/frills approach and says no to features such as animations. It relies on clients for panels, screenshots, wallpapers and so on to create a full desktop environment. Labwc tries to stay in keeping with wlroots and sway in terms of general approach and coding style. ... -
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ChainRules.jl
Forward and reverse mode automatic differentiation primitives
...The core logic of ChainRules is implemented in ChainRulesCore.jl. To add ChainRules support to your package, by defining new rules or frules, you only need to depend on the very light-weight package ChainRulesCore.jl. This repository contains ChainRules.jl, which is what people actually use directly. ChainRules reexports all the ChainRulesCore functionality and has all the rules for the Julia standard library. -
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Immutables
Annotation processor to create immutable objects and builders
Java annotation processors to generate simple, safe, and consistent value objects. Do not repeat yourself, try Immutables, the most comprehensive tool in this field. With Immutables you can generate state-of-the-art immutable objects and builders. Type-safe, null-safe and thread-safe, with no boilerplate. Generate builders for immutable objects and even plain static factory methods. Just add jar to classpath and use. No required runtime dependencies! Guava is supported, but not required.... -
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Marx
The classless CSS reset (perfect for Communists)
Marx is a CSS stylesheet to be used in any project (namely small ones). If you don't need the weight of heavy frameworks or you would just like to make an edible website quickly, Marx is perfect for you. It can be used out of the minified box but it can also be customized and styled through the use of HTML classes. Built atop of Sanitize.css, meaning all browsers render consistently. Responsive and mobile-friendly. Clean, beautiful typography. -
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. -
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LLM-Pruner
On the Structural Pruning of Large Language Models
...The framework relies on gradient-based analysis to determine which parameters contribute least to model performance, enabling targeted structural pruning rather than simple weight removal. After pruning, the framework applies lightweight fine-tuning methods such as LoRA to recover performance using relatively small datasets and short training times.
