Instructions to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-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 matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

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 matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

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 matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

Use Docker

docker model run hf.co/matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

LM Studio
Jan

vLLM

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-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": "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

SGLang

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with Ollama:
```
ollama run hf.co/matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
```

Unsloth Studio

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-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 matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-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 matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with Docker Model Runner:
```
docker model run hf.co/matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S
```

Lemonade

How to use matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull matrixportalx/wiroai-turkish-llm-9b-Q4_K_S-GGUF:Q4_K_S

Run and chat with the model

lemonade run user.wiroai-turkish-llm-9b-Q4_K_S-GGUF-Q4_K_S

List all available models

lemonade list

wiroai-turkish-llm-9b-Q4_K_S-GGUF / README.md

Matrix

Upload README.md with huggingface_hub

51ea599 verified over 1 year ago

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	---
	license: gemma
	library_name: transformers
	pipeline_tag: text-generation
	extra_gated_heading: Access Gemma on Hugging Face
	extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
	agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
	Face and click below. Requests are processed immediately.
	extra_gated_button_content: Acknowledge license
	tags:
	- conversational
	- llama-cpp
	- gguf-my-repo
	base_model: WiroAI/wiroai-turkish-llm-9b
	language:
	- tr
	model-index:
	- name: wiroai-turkish-llm-9b
	results:
	- task:
	type: multiple-choice
	dataset:
	name: MMLU_TR_V0.2
	type: multiple-choice
	metrics:
	- type: 5-shot
	value: 0.5982
	name: 5-shot
	verified: false
	- type: 0-shot
	value: 0.4991
	name: 0-shot
	verified: false
	- type: 25-shot
	value: 0.5367
	name: 25-shot
	verified: false
	- type: 10-shot
	value: 0.5701
	name: 10-shot
	verified: false
	- type: 5-shot
	value: 0.6682
	name: 5-shot
	verified: false
	- type: 5-shot
	value: 0.6058
	name: 5-shot
	verified: false
	---

	# matrixportal/wiroai-turkish-llm-9b-Q4_K_S-GGUF
	This model was converted to GGUF format from [`WiroAI/wiroai-turkish-llm-9b`](https://huggingface.co/WiroAI/wiroai-turkish-llm-9b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
	Refer to the [original model card](https://huggingface.co/WiroAI/wiroai-turkish-llm-9b) for more details on the model.

	## Use with llama.cpp
	Install llama.cpp through brew (works on Mac and Linux)

	```bash
	brew install llama.cpp

	```
	Invoke the llama.cpp server or the CLI.

	### CLI:
	```bash
	llama-cli --hf-repo matrixportal/wiroai-turkish-llm-9b-Q4_K_S-GGUF --hf-file wiroai-turkish-llm-9b-q4_k_s.gguf -p "The meaning to life and the universe is"
	```

	### Server:
	```bash
	llama-server --hf-repo matrixportal/wiroai-turkish-llm-9b-Q4_K_S-GGUF --hf-file wiroai-turkish-llm-9b-q4_k_s.gguf -c 2048
	```

	Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

	Step 1: Clone llama.cpp from GitHub.
	```
	git clone https://github.com/ggerganov/llama.cpp
	```

	Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
	```
	cd llama.cpp && LLAMA_CURL=1 make
	```

	Step 3: Run inference through the main binary.
	```
	./llama-cli --hf-repo matrixportal/wiroai-turkish-llm-9b-Q4_K_S-GGUF --hf-file wiroai-turkish-llm-9b-q4_k_s.gguf -p "The meaning to life and the universe is"
	```
	or
	```
	./llama-server --hf-repo matrixportal/wiroai-turkish-llm-9b-Q4_K_S-GGUF --hf-file wiroai-turkish-llm-9b-q4_k_s.gguf -c 2048
	```