Search Results for "command-line kill linux" - Page 27

GAP (Grid Agents Platform) Toolkit for Modeling and Simulation of Mobile Agents in Grid Environments. GAP is an abstraction over GridSim, a Grid Simulation Toolkit for Resource Modelling and Application Scheduling for Parallel and Distributed Computing.

JavaGO is an Open Source Java library for the Game of GO (weiqi, baduk) analysis. Implements: base game classes, montecarlo simulations, SGF reader/writer, game variants, GTP, etc. Elegant interfaces/class design. Speed efficient w/small footprint. TDD.

The OBO-Annotator is a semantic NLP tool that is designed to give its end-users a great deal of flexibility to combine any number of OBO ontologies from the OBO foundry regardless of their format and use them to annotate text-bases.

This project aims at creating rationally thinking agents. The agent gather information through command line or network and stores it in its memory. It uses Stanford's NLP library to understand the language statements.

Luna Code Checker An advanced web-based tool for checking JavaScript code using ESLint. How to Use Clone the repository. Run npm install to install the dependencies. Run npm start to start the server. Open http://localhost:3000 in your web browser. Write or paste your JavaScript code in the textarea. Click the "Check Code" button to see linting results. Features Comprehensive syntax and style checking using ESLint. Detailed error messages including line numbers and...

SuperGemma4 is a locally deployable large language model built on the Gemma 4 26B A4B instruction base, optimized for speed, flexibility, and less restricted conversational behavior. It is designed to provide a more open and natural chat experience compared to standard censored models, while still maintaining practical usability across general text, coding, and multilingual tasks, especially Korean. Unlike raw base models, it inherits improvements from the SuperGemma Fast line, resulting in...

Ministral 3 14B Base 2512 is the largest model in the Ministral 3 line, offering state-of-the-art language and vision capabilities in a dense, base-pretrained form. It combines a 13.5B-parameter language model with a 0.4B-parameter vision encoder, enabling both high-quality text understanding/generation and image-aware tasks. As a “base” model (i.e. not fine-tuned for instruction or reasoning), it provides a flexible foundation ideal for custom fine-tuning or downstream specialization. The...