Search Results for "training" - Page 36

This application checks the remaining training time of EVE Skills. It comes as a GNOME applet and as a command-line tool. EVE is a subscription-based MMORPG set in the far future with space combat, travel, research and marketing.

ASR-Builder provides an easy-to-use interface to the HTK toolkit, that allows users to build ASR systems. ASR-Builder provides a platform that performs house-keeping tasks when using HTK and also provides default training/testing/recognition scripts.

This small python script will generate mp3 and corresponding text files for learning / training the morse code. It follows the method of Koch for teaching the characters and the method described in N0HFFs book for improving the skills even more.

Learning Japanese in a fun way on a Nintendo DS.

SimTor is an easy authoring tool for creating interactive simulations for application training. It supports the complete develepment-workflow. The deliverances of the tool are an xml-database, bitmaps and a flash-engine.

FlashE is an VERY simple electronic flash card system written in python. FlashE is very general and is intended to be as well suited to vocabulary training as math or Biology. The quiz files can be edited or shared.

A Genetic Algorithm Training System in Python. Gatspy provides the framework, the user provides the error (fitness) function. Gatspy will evolve a solution that attempts to minimize the error.

Personal training diary for saveing and analyzing trainings. - pyGTK, MySQL. - training as part (every part have sport type, feelling...) - Garmin *.tcx files/Forerunner 305 - support for orienteering

A script to generate random text using Markov chains. Output text will be stylistically similar to the training text.

...The model was notably used in competitive AI challenges such as the 2025 International Mathematical Olympiad (IMO) and IOI, achieving top-tier results. DeepSeek-V3.2 also features a large-scale agentic task synthesis pipeline, which generates training data to enhance tool-use intelligence and multi-step reasoning. It introduces a new “thinking with tools” chat template, allowing it to reason and decide when to invoke specific tools during problem solving.

Think Python intends to be an interactive online learning environment for Python. It consists of two parts: A small IDE which is able to run your Python code in the browser without installing any plugins and an interactive training system which can contain explainations, questions and practical tasks.

Crujisim is a tool to allow Air Traffic Controllers trainees to practice in a radar environment. Different users connect to a hosting server to act either as controllers for adjacent positions or pseudopilots.

Hunyuan-MT-7B is a large-scale multilingual translation model developed by Tencent, designed to deliver state-of-the-art translation quality across 36 languages, including several Chinese ethnic minority languages. It forms part of the Hunyuan Translation Model family, alongside Hunyuan-MT-Chimera, which ensembles outputs for even higher accuracy. Trained with a comprehensive framework spanning pretraining, cross-lingual pretraining, supervised fine-tuning, enhancement, and ensemble...

DeepSeek-V3.2-Speciale is the high-compute, ultra-reasoning variant of DeepSeek-V3.2, designed specifically to push the boundaries of mathematical, logical, and algorithmic intelligence. It builds on the DeepSeek Sparse Attention (DSA) framework, delivering dramatically improved long-context efficiency while preserving full model quality. Unlike the standard version, Speciale is tuned exclusively for deep reasoning and therefore does not support tool-calling, focusing its full capacity on...

...With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. The model is efficient for both cloud inference with vLLM and local deployment using llama.cpp or Ollama, thanks to its bf16 precision and AMP training. While the base model is not fine-tuned for downstream tasks, it is designed to be easily adapted through supervised fine-tuning (SFT) or reinforcement learning (RL). Benchmarks on RepoBench, SAFIM, and HumanEval demonstrate its competitive performance, with specialized fine-tuned versions for Python already showing strong improvements.