Tiny Qwen3 Village Generator is a character-level language model designed to generate Turkish village names. Built on a minimal version of the Qwen3 transformer architecture, it was trained from scratch for educational purposes using a dataset of 11,104 unique Turkish village names. The model's primary function is to create plausible new names that resemble authentic Turkish village names, as demonstrated by example outputs such as Ebrailler, Aşağıkarakış, and Sazarören.
This model operates at the character level, utilizing a vocabulary of 64 characters and a context length of 32. It contains 20,672 parameters and was trained over 8,000 steps. The training dataset, Uunan/turkish-village-names, consists of one village name per line, providing a focused and domain-specific corpus for the model's learning process. The tool is intended for educational and research use, allowing users to experiment with small-scale text generation models and to explore the capabilities of transformer architectures in generating structured, culturally relevant text.
Tiny Qwen3 Village Generator is delivered as a model hosted on Hugging Face, and usage instructions are provided via a Python script (generate.py). The model is distributed under the MIT license, making it freely available for use, modification, and distribution. Its compact size and open licensing make it accessible for experimentation, learning, and research in natural language processing and generative modeling.
Tiny Qwen3 Village Generator is a Foundation models & chat product. It focuses on enabling the generation of Turkish village names for educational and research purposes. Tiny Qwen3 Village Generator is an open-source project aimed at AI researchers and educators. The project is open source (Open Source). It runs on the web and the command line, and it can be self-hosted.
It is developed by Uunan, and the product first shipped in 2026. The project is developed in the open on GitHub with 8 commits in the last 90 days. Among its 5 catalogued features are village name generation, character-level modeling, and educational use.
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