Turkish LLM Family
Collection
Open-source Turkish LLM family (1.5B-32B). Models, GGUF quantizations, datasets, and demos. • 8 items • Updated
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
# 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 ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
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 ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
docker model run hf.co/ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ogulcanaydogan/Turkish-LLM-32B-Instruct-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": "ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with Ollama:
ollama run hf.co/ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with Pi:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
# 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": "ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M"
}
]
}
}
}# Start Pi in your project directory: pi
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
lemonade run user.Turkish-LLM-32B-Instruct-GGUF-Q4_K_M
lemonade list
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with Hermes Agent:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
# 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 ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
hermes
How to use ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF with OpenClaw:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
# 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 "ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
openclaw agent --local --agent main --message "Hello from Hugging Face"
GGUF quantizations of Turkish-LLM-32B-Instruct.
Part of the Turkish LLM Family.
| File | Size | Use Case |
|---|---|---|
| Q4_K_M | 19GB | Best balance of quality and size. Recommended for most users. |
| Q5_K_M | 22GB | Higher quality, slightly larger. |
| Q8_0 | 33GB | Near-original quality. Requires 40GB+ VRAM. |
| F16 | 62GB | Full precision. Research use. |
# Download and run
ollama run hf.co/ogulcanaydogan/Turkish-LLM-32B-Instruct-GGUF:Q4_K_M
./llama-cli -m Turkish-LLM-32B-Instruct-Q4_K_M.gguf -p "Turkiye'nin ekonomik durumu hakkinda bilgi ver." -n 256
| Benchmark | Base Model | Turkish-LLM-32B | Delta |
|---|---|---|---|
| MMLU-TR | 0.6518 | 0.6564 | +0.46 |
| XNLI-TR | 0.4578 | 0.4610 | +0.32 |
| XCOPA-TR | 0.6800 | 0.6740 | -0.60 |
4-bit
5-bit
8-bit
Base model
Qwen/Qwen2.5-32B