Instructions to use stamchry/greek-keyboard-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use stamchry/greek-keyboard-lm 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 stamchry/greek-keyboard-lm:Q6_K
# Run inference directly in the terminal:
llama cli -hf stamchry/greek-keyboard-lm:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf stamchry/greek-keyboard-lm:Q6_K
# Run inference directly in the terminal:
llama cli -hf stamchry/greek-keyboard-lm:Q6_K

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 stamchry/greek-keyboard-lm:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf stamchry/greek-keyboard-lm:Q6_K

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 stamchry/greek-keyboard-lm:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf stamchry/greek-keyboard-lm:Q6_K

Use Docker

docker model run hf.co/stamchry/greek-keyboard-lm:Q6_K

LM Studio
Jan

vLLM

How to use stamchry/greek-keyboard-lm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "stamchry/greek-keyboard-lm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "stamchry/greek-keyboard-lm",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/stamchry/greek-keyboard-lm:Q6_K

Ollama
How to use stamchry/greek-keyboard-lm with Ollama:
```
ollama run hf.co/stamchry/greek-keyboard-lm:Q6_K
```
Unsloth Desktop
Docker Model Runner
How to use stamchry/greek-keyboard-lm with Docker Model Runner:
```
docker model run hf.co/stamchry/greek-keyboard-lm:Q6_K
```

Lemonade

How to use stamchry/greek-keyboard-lm with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull stamchry/greek-keyboard-lm:Q6_K

Run and chat with the model

lemonade run user.greek-keyboard-lm-Q6_K

List all available models

lemonade list

Atomic Chat

Greek Transformer Language Model for FUTO Keyboard (~36.1M)

Custom Modern Greek (el) predictive text and autocorrect Transformer Language Model (~36.15M parameters) built for the FUTO Android Keyboard.

Architecture: LlamaForCausalLM (9 layers, 512 hidden size, 1376 intermediate, 8 heads, tied embeddings)
Quantization Formats: Q6_K (~~36.8 MB), Q8_0 (~~45.4 MB), F16 (~85 MB)
Tokenizer: SentencePiece Unigram (15,008 vocab, treat_whitespace_as_suffix=True)
Control Tokens: <XBU>, <XBC>, <XEC> for FUTO autocorrect protocol

🚀 Quick Start & Mobile Deployment

1. Requirements

To support Greek in-word typing, Unicode codepoints, and spatial keystroke decoding, install the APK built from the Greek-enabled fork: 👉 https://github.com/stamchry/android-keyboard

2. Download Model

Download el_keyboard_v3_Q6_K.gguf (or el_keyboard_Q6_K.gguf) to your Android device storage.

3. Setup in FUTO Keyboard

Open FUTO Keyboard Settings → Help & About.
Tap "Version code" 8 times rapidly to unlock Developer Settings.
Open Settings → Developer → toggle "Allow transformer models on non QWERTY layouts" to ON.
Go to Settings → Predictive Text → Transformer Models.
Tap Actions (top-right) → Import from file → select el_keyboard_v3_Q6_K.gguf.
Ensure it displays: "Model is set to default for el".

📊 Benchmark Results

Metric / Benchmark	Result
Next-Word Top-1 Accuracy	39.33%
Next-Word Top-3 Accuracy	53.06%
Next-Word Top-10 Accuracy	64.48%
Accent Restoration Accuracy	38.60%
Synthetic Typo Autocorrect	37.40%

🔗 Repository

Source training code and pipeline: https://github.com/stamchry/greek-keyboard-lm

Downloads last month: 505

Safetensors

Model size

36.2M params

Tensor type

F32