Instructions to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with Cosmos:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

llama-cpp-python

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF",
	filename="Kaira-Turkish-Gemma-9B-T1-f16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-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 umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf umutkkgz/Kaira-Turkish-Gemma-9B-T1-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 umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf umutkkgz/Kaira-Turkish-Gemma-9B-T1-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 umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf umutkkgz/Kaira-Turkish-Gemma-9B-T1-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 umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "umutkkgz/Kaira-Turkish-Gemma-9B-T1-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": "umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M

Ollama
How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with Ollama:
```
ollama run hf.co/umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
```

Unsloth Studio

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with Docker Model Runner:
```
docker model run hf.co/umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M
```

Lemonade

How to use umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull umutkkgz/Kaira-Turkish-Gemma-9B-T1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Kaira-Turkish-Gemma-9B-T1-GGUF-Q4_K_M

List all available models

lemonade list

Kaira-Turkish-Gemma-9B-T1-GGUF

File size: 1,094 Bytes

---
license: mit
language:
- tr
base_model:
- ytu-ce-cosmos/Turkish-Gemma-9b-T1
pipeline_tag: text-classification
---
# website:https://kairaaiv2.netlify.app
# Turkish-Gemma-9B-T1 – GGUF (Q4_K_M)
**Yayıncı:** Umut Kökgöz (@umutkkgz)  
**Taban model:** `ytu-ce-cosmos/Turkish-Gemma-9b-T1` (Gemma 2 tabanlı Türkçe sürüm)  
**Biçim:** GGUF – `Q4_K_M` (yaklaşık 5–6 GB)

## Özet
Bu repo, Türkçe Gemma 9B T1 modelinin **llama.cpp uyumlu** ve **hafif** (`Q4_K_M`) sürümünü içerir.  
Hedef: 8–12 GB VRAM ile hızlı inference.

## Dosyalar
- `Turkish-Gemma-9B-T1-q4_K_M.gguf` – quantized GGUF

## Kullanım (llama.cpp)
```bash
# (opsiyonel) CUDA'lı derleme
cmake -S llama.cpp -B build -DLLAMA_CUBLAS=ON && cmake --build build -j

# Çalıştırma (CPU)
./build/bin/llama-cli \\
  -m Turkish-Gemma-9B-T1-q4_K_M.gguf \\
  -n 200 -temp 0.7 -top_p 0.9 -repeat_penalty 1.05 \\
  -p "Türkçe kısa özet: Gemma ve LLaMA arasındaki farkları 3 maddede açıkla."

# GPU offload (ör. 20 katman)
./build/bin/llama-cli -m Turkish-Gemma-9B-T1-q4_K_M.gguf -n 200 -ngl 20 -p "..."