Instructions to use geolazagr/greko 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 geolazagr/greko 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 geolazagr/greko:Q4_K_M # Run inference directly in the terminal: llama cli -hf geolazagr/greko:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf geolazagr/greko:Q4_K_M # Run inference directly in the terminal: llama cli -hf geolazagr/greko: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 geolazagr/greko:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf geolazagr/greko: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 geolazagr/greko:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf geolazagr/greko:Q4_K_M
Use Docker
docker model run hf.co/geolazagr/greko:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use geolazagr/greko with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "geolazagr/greko" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "geolazagr/greko", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/geolazagr/greko:Q4_K_M
- Ollama
How to use geolazagr/greko with Ollama:
ollama run hf.co/geolazagr/greko:Q4_K_M
- Unsloth Desktop
- Pi
How to use geolazagr/greko with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf geolazagr/greko:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "geolazagr/greko:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use geolazagr/greko with Docker Model Runner:
docker model run hf.co/geolazagr/greko:Q4_K_M
- Lemonade
How to use geolazagr/greko with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull geolazagr/greko:Q4_K_M
Run and chat with the model
lemonade run user.greko-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use geolazagr/greko with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf geolazagr/greko:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default geolazagr/greko:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use geolazagr/greko with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf geolazagr/greko:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "geolazagr/greko:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Greko 2.1 (beta)
Greko is a friendly AI assistant that runs entirely offline on your phone: nothing you type leaves the device, unless you turn on web search. It can see photos, read your documents, and make Word and Excel files. Greko 2.1 is Greko 2 with much better Greek.
New to Greko? Follow the step-by-step install guide (English and Greek), which shows each Android prompt and what to tap.
- Android app: install
greko.apk(Android 13+, arm64, 2 GB of RAM or more). On first launch it offers Download Greko, which fetches the model and its vision encoder once: about 1.3 GB, or 1 GB for Greko 2.1 Lite on phones with less than 2.4 GB of RAM. After that no internet is needed. Phones that already have Greko 2 are offered Greko 2.1 (about 1.1 GB), and phones with the older 4-bit eyes the smaller 3-bit ones (190 MB), so photos need less free memory. - Photos and documents (๐): send a photo, or a PDF, Word (.docx) or text file, and ask about it: "summarise this", "what's the deadline in this contract?". Everything is read on the phone. A long document is searched for the parts that match your question, since a phone's model can only take in a few pages at once.
- Word and Excel files: ask "make me an Excel file withโฆ" or "put this receipt in Excel" with a photo, and Greko's answer comes with a real .docx or .xlsx file to open, share or save.
- Think mode (๐ก): Greko reasons step by step before answering. Better at maths and logic, but slower.
- Web search (๐, optional): while the phone is online, a question is searched on DuckDuckGo (or Wikipedia) and Greko answers from the results, listing its sources, with pictures of what you asked about from Wikipedia when it has some. Only the question is sent, to those two sites. It's off until you turn it on.
- Voice (๐ค / ๐): talk instead of typing, and hear answers read aloud. Speech is recognized and spoken by the phone itself; the voice is never sent anywhere.
- Updates: once a day the app checks this repository for a newer version and installs it on your OK (only the version file is fetched; nothing about you is sent).
- Languages: English and Greek; the app follows the phone's language.
- Made by: George
Files
| File | What it is |
|---|---|
greko-2.1-Q4_K_M.gguf |
Greko 2.1: Qwen3-VL-2B-Instruct fine-tuned with QLoRA (language model only), 4-bit |
greko-2.1-lite.gguf |
Greko 2.1 Lite for 2 GB phones: the same model at IQ3_M with an importance matrix |
mmproj-greko-2-q3.gguf |
Greko's eyes: the vision encoder and projector, unchanged from Qwen3-VL-2B, at 3 bits (Q3_K, 190 MB). The app uses these, for Greko 2 and 2.1 alike: in tests they read photos as well as the 4-bit and 8-bit ones, a little more slowly |
mmproj-greko-2-q4.gguf |
The same eyes at 4 bits (241 MB), used by the app until 2.7-beta |
mmproj-greko-2.gguf |
The same eyes at 8 bits (445 MB), for PCs |
greko.apk |
The Android app (2.10-beta) |
app-version.json |
What the app reads once a day to offer its own updates |
greko-2-Q4_K_M.gguf, greko-2-lite.gguf |
Greko 2, the previous model, kept for older installs |
greko-2.5-beta.apk |
An earlier app (2.5-beta), in case the current one has a problem on your phone |
greko-1.7b-beta-Q4_K_M.gguf, greko-1-beta.apk |
Greko 1 beta (Qwen3-1.7B, text only) |
Training
Greko 2.1 was fine-tuned on 22,423 conversations:
- 12,000 general conversations from smol-smoltalk
- 8,557 Greek conversations (chat, instructions and maths) from the Greek part of openeurollm/Dolci-Instruct-SFT-translated, filtered: no code, mostly Greek, no other assistant's name
- chats written for Greko's persona in English and Greek, hand-written Greek conversations, and multi-turn chats that teach it to answer from the conversation so far
- step-by-step reasoning examples for Think mode, written by Qwen3-1.7B for questions from the train splits of GSM8K and ARC-Easy, keeping only those that reached the right answer
| Qwen3-VL-2B | Greko 2 | Greko 2.1 | |
|---|---|---|---|
| Held-out "what's your name" questions naming Greko | 4/5 | 5/5 | 5/5 |
| Held-out "who made you" questions naming George | 0/2 | 2/2 | 2/2 |
| GSM8K (100 test questions) | 82% | 71% | 69% |
| ARC-Easy (200 test questions) | 91% | 91% | 92% |
| Greek perplexity on 200 held-out Greek chats (lower is better) | 1.82 | 1.63 |
The GSM8K and ARC-Easy differences between Greko 2 and 2.1 are within noise (ยฑ9 and ยฑ4 points at these sample sizes).
Beta: Greko 2.1's Greek is much better than Greko 2's, but it still gets facts wrong and can ramble in longer Greek answers (summaries, letters). Its maths is below the base model's. Check anything important.
On a PC
llama-mtmd-cli -m greko-2.1-Q4_K_M.gguf --mmproj mmproj-greko-2-q3.gguf --image photo.jpg -p "What's in this photo?"
Greko's system prompt is built into the chat template.
License
Apache 2.0, the same as Qwen3-VL-2B. The Greek training data's license terms are on its dataset page.
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Model tree for geolazagr/greko
Base model
Qwen/Qwen3-VL-2B-Instruct