Instructions to use kungaa/TuvanGemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kungaa/TuvanGemma with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf kungaa/TuvanGemma:Q5_K_M # Run inference directly in the terminal: llama cli -hf kungaa/TuvanGemma:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kungaa/TuvanGemma:Q5_K_M # Run inference directly in the terminal: llama cli -hf kungaa/TuvanGemma:Q5_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf kungaa/TuvanGemma:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf kungaa/TuvanGemma:Q5_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf kungaa/TuvanGemma:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf kungaa/TuvanGemma:Q5_K_M
Use Docker
docker model run hf.co/kungaa/TuvanGemma:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use kungaa/TuvanGemma with Ollama:
ollama run hf.co/kungaa/TuvanGemma:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use kungaa/TuvanGemma with Docker Model Runner:
docker model run hf.co/kungaa/TuvanGemma:Q5_K_M
- Lemonade
How to use kungaa/TuvanGemma with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kungaa/TuvanGemma:Q5_K_M
Run and chat with the model
lemonade run user.TuvanGemma-Q5_K_M
List all available models
lemonade list
- Atomic Chat
TuvanGemma
TuvanGemma is a local Russian ↔ Tuvan translation model distributed as a
GGUF file for llama.cpp. The Windows portable application is
TuvanTranslator-windows-x64-v0.1.0.zip.
The model is a Gemma-derived model. Read and comply with the Gemma Terms of Use included with the package and linked from the desktop repository before using or redistributing it.
Evaluation results
The E3 release was trained for one epoch on 370,902 directional examples and evaluated on 3,824 held-out pairs in each direction:
| direction | baseline chrF++ | TuvanGemma chrF++ | baseline BLEU | TuvanGemma BLEU |
|---|---|---|---|---|
| RU → TYV | 13.0657 | 45.4822 | 1.1298 | 16.2996 |
| TYV → RU | 19.6637 | 44.7172 | 2.1083 | 20.8963 |
This is a specialized Russian ↔ Tuvan model. Review names, numbers, idioms, and important translations before relying on its output.
Dataset acknowledgment
This model was fine-tuned using Agisight's tyv-rus-200k dataset:
Agisight/tyv-rus-200k on Hugging Face.
The dataset is attributed under CC BY 4.0. The complete attribution notice is
included in the Windows package.
Desktop application
Source code, build instructions, third-party notices, and the complete Gemma terms are available at kungaa/TuvanTranslator on GitHub.
The ZIP is a self-contained Windows x64 package with CUDA, Vulkan, and CPU
llama.cpp runtimes, the model, and a fixed WebView2 runtime. Auto mode tries
CUDA, then Vulkan, then CPU. Vulkan requires a working Vulkan-capable Windows
graphics driver; vulkan-1.dll is intentionally not bundled.
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Base model
google/translategemma-4b-it