Instructions to use DraconicDragon/ToriiGate-0.5-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DraconicDragon/ToriiGate-0.5-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="DraconicDragon/ToriiGate-0.5-GGUF",
	filename="ToriiGate-0.5-IQ4_NL.gguf",
)

llm.create_chat_completion(
	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"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M

Use Docker

docker model run hf.co/DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use DraconicDragon/ToriiGate-0.5-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DraconicDragon/ToriiGate-0.5-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": "DraconicDragon/ToriiGate-0.5-GGUF",
		"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/DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M

Ollama
How to use DraconicDragon/ToriiGate-0.5-GGUF with Ollama:
```
ollama run hf.co/DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
```

Unsloth Studio

How to use DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-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 DraconicDragon/ToriiGate-0.5-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DraconicDragon/ToriiGate-0.5-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use DraconicDragon/ToriiGate-0.5-GGUF with Docker Model Runner:
```
docker model run hf.co/DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M
```

Lemonade

How to use DraconicDragon/ToriiGate-0.5-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DraconicDragon/ToriiGate-0.5-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.ToriiGate-0.5-GGUF-Q4_K_M

List all available models

lemonade list

generic llama.cpp quants of Minthy/ToriiGate-0.5 | Using llama.cpp release b8720

You can find imatrix, K_L quants (--token-embedding-type & --output-tensor-type are in Q8_0) here:
- https://huggingface.co/SleepVeryHard/ToriiGate-0.5_GGUF

The README mentions that --reasoning off/-rea off should be added as llama.cpp cli arg to workaround an issue where the actual output is just in the reasoning part - I found that to be the case too and disabling reasoning helped. GGUFs have been updated to include the correct chat template

Original model + more info like prompts/formats, examples, stats:
- https://huggingface.co/Minthy/ToriiGate-0.5

Tested the Q4KM variant with Q8 vision encoder:

Downloads last month: 7,593

GGUF

Model size

5B params

Architecture

qwen35

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for DraconicDragon/ToriiGate-0.5-GGUF

Base model

Qwen/Qwen3.5-4B-Base

Finetuned

Minthy/ToriiGate-0.5

Quantized

(5)

this model