Instructions to use vishinvents/OpenEuroLLM-Czech-Ollama-GGUF 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 vishinvents/OpenEuroLLM-Czech-Ollama-GGUF 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 vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_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 vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_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 vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
Use Docker
docker model run hf.co/vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use vishinvents/OpenEuroLLM-Czech-Ollama-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vishinvents/OpenEuroLLM-Czech-Ollama-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vishinvents/OpenEuroLLM-Czech-Ollama-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
- Ollama
How to use vishinvents/OpenEuroLLM-Czech-Ollama-GGUF with Ollama:
ollama run hf.co/vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use vishinvents/OpenEuroLLM-Czech-Ollama-GGUF with Docker Model Runner:
docker model run hf.co/vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
- Lemonade
How to use vishinvents/OpenEuroLLM-Czech-Ollama-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.OpenEuroLLM-Czech-Ollama-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
OpenEuroLLM-Czech (Ollama GGUF Mirror)
This repository mirrors the Ollama model jobautomation/OpenEuroLLM-Czech as a standalone GGUF plus the supporting Ollama metadata needed to recreate the package locally.
Contents
OpenEuroLLM-Czech-Q4_K_M.gguf: the main GGUF weights fileModelfile: Ollama recipe adjusted to use the local GGUF fileollama-manifest.json: original Ollama manifestparams.json: Ollama parameter blocktemplate.txt: Ollama chat templatesystem.txt: default Czech system promptlicenses/: license materials shipped with the Ollama packageNOTICE: required Gemma redistribution notice
Model Notes
- Architecture:
gemma3 - Parameters:
12.2B - Quantization:
Q4_K_M - Context length in GGUF metadata:
131072 - Default Ollama runtime context:
2048 - Primary language behavior: Czech
Use With Ollama
After downloading the repository locally:
ollama create OpenEuroLLM-Czech -f Modelfile
Use With GGUF Runtimes
The file OpenEuroLLM-Czech-Q4_K_M.gguf can also be used directly with GGUF-compatible runtimes such as llama.cpp and other tools that support Gemma 3 GGUF models.
Use With vLLM
This mirror now includes a root config.json and generation_config.json to improve compatibility with serving stacks that expect Hugging Face-style metadata.
For vLLM, you will typically still want to point the tokenizer at the original Gemma 3 tokenizer:
vllm serve vishinvents/OpenEuroLLM-Czech-Ollama-GGUF:Q4_K_M \
--tokenizer google/gemma-3-12b-it
Licensing
This package includes the original license materials surfaced by Ollama:
licenses/Gemma-Terms-of-Use.txtlicenses/Additional-License.txt
Please review those files before use or redistribution.
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