Instructions to use LumenSyntax/logos-theological-9b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LumenSyntax/logos-theological-9b-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="LumenSyntax/logos-theological-9b-gguf",
	filename="logos-theological-9b.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use LumenSyntax/logos-theological-9b-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LumenSyntax/logos-theological-9b-gguf
# Run inference directly in the terminal:
llama-cli -hf LumenSyntax/logos-theological-9b-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LumenSyntax/logos-theological-9b-gguf
# Run inference directly in the terminal:
llama-cli -hf LumenSyntax/logos-theological-9b-gguf

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 LumenSyntax/logos-theological-9b-gguf
# Run inference directly in the terminal:
./llama-cli -hf LumenSyntax/logos-theological-9b-gguf

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 LumenSyntax/logos-theological-9b-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LumenSyntax/logos-theological-9b-gguf

Use Docker

docker model run hf.co/LumenSyntax/logos-theological-9b-gguf

LM Studio
Jan
Ollama
How to use LumenSyntax/logos-theological-9b-gguf with Ollama:
```
ollama run hf.co/LumenSyntax/logos-theological-9b-gguf
```

Unsloth Studio new

How to use LumenSyntax/logos-theological-9b-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 LumenSyntax/logos-theological-9b-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 LumenSyntax/logos-theological-9b-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LumenSyntax/logos-theological-9b-gguf to start chatting

Docker Model Runner
How to use LumenSyntax/logos-theological-9b-gguf with Docker Model Runner:
```
docker model run hf.co/LumenSyntax/logos-theological-9b-gguf
```

Lemonade

How to use LumenSyntax/logos-theological-9b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LumenSyntax/logos-theological-9b-gguf

Run and chat with the model

lemonade run user.logos-theological-9b-gguf-{{QUANT_TAG}}

List all available models

lemonade list

Logos Theological 9B (GGUF)

Gemma 2 9B fine-tuned for structural biblical analysis. Identifies patterns — kenosis, authority, inversion — without claiming theological authority. Engages mystery without resolving it.

Usage

Requires Ollama.

# Create model
ollama create logos-bible -f Modelfile

# Chat
ollama run logos-bible

Model Details

Base: Google Gemma 2 9B
Format: GGUF (quantized)
Size: ~6.2 GB
RAM required: 16 GB minimum
Research: The Instrument Trap

Access

This is a gated model. Request access and it will be manually approved.

License

Research use. Contact Rafael Rodriguez for commercial licensing.

Downloads last month: 42

GGUF

Model size

9B params

Architecture

gemma2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support