Instructions to use olamide226/ofin-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use olamide226/ofin-model with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="olamide226/ofin-model",
	filename="ofin-model.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use olamide226/ofin-model 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 olamide226/ofin-model
# Run inference directly in the terminal:
llama cli -hf olamide226/ofin-model

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf olamide226/ofin-model
# Run inference directly in the terminal:
llama cli -hf olamide226/ofin-model

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 olamide226/ofin-model
# Run inference directly in the terminal:
./llama-cli -hf olamide226/ofin-model

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 olamide226/ofin-model
# Run inference directly in the terminal:
./build/bin/llama-cli -hf olamide226/ofin-model

Use Docker

docker model run hf.co/olamide226/ofin-model

LM Studio
Jan
Ollama
How to use olamide226/ofin-model with Ollama:
```
ollama run hf.co/olamide226/ofin-model
```

Unsloth Studio

How to use olamide226/ofin-model 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 olamide226/ofin-model 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 olamide226/ofin-model to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for olamide226/ofin-model to start chatting

How to use olamide226/ofin-model with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf olamide226/ofin-model

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "olamide226/ofin-model"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use olamide226/ofin-model with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf olamide226/ofin-model

Configure Hermes

# 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 olamide226/ofin-model

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use olamide226/ofin-model with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf olamide226/ofin-model

Configure OpenClaw

# 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 "olamide226/ofin-model" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use olamide226/ofin-model with Docker Model Runner:
```
docker model run hf.co/olamide226/ofin-model
```

Lemonade

How to use olamide226/ofin-model with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull olamide226/ofin-model

Run and chat with the model

lemonade run user.ofin-model-{{QUANT_TAG}}

List all available models

lemonade list

Òfin — Offline Nigerian Legal Companion

This is the baked model for Òfin, an offline legal assistant for Nigerian labour, tenancy, and tax law. It's based on Llama 3.2 3B Instruct Q4_K_M with the Òfin legal persona baked directly into the chat template — no system prompt needed.

Part of the Òfin system built for the Africa Deep Tech Challenge 2026 (Laptop LLM track, corporate enterprise).

What makes this model different

The vanilla Llama 3.2 3B chat template has been surgically modified to replace the tools-and-dates boilerplate with Òfin's legal persona. When loaded standalone (e.g. llama-cli -m ofin-model.gguf), the model defaults to:

Nigerian legal framing (labour, tenancy, and tax law)
Nigerian Pidgin capability (matches the question language)
Statutory citation format ([Act Name, s.X(Y)])
Scope-awareness (refuses questions outside its three domains)

The baked persona makes the standalone model present correctly to judges testing the raw GGUF. In production, Òfin wraps the model with a retrieval pipeline, deterministic rules engine, and citation verifier — the model itself is not the product.

How the bake works

The chat template's 624-byte section between the system header and {{ system_message }} — originally tools/dates boilerplate — was replaced with a same-length Jinja2 literal containing the Òfin persona:

You are Òfin, an offline legal companion for Nigerian law. You cover three
areas: (1) Labour law — employment termination and notice periods, wages
and deductions, redundancy, maternity leave, sick leave, written employment
terms, minimum wage, workplace injury compensation. (2) Tenancy law —
notice to quit, advance rent, eviction, landlord and tenant obligations
(Lagos State law). (3) Tax law — PAYE income tax, tax bands and rates,
business tax registration, tax filing...

The bake is byte-accurate (no offset shifts) and fully reproducible via scripts/bake_chat_template.py in the main repo.

Quick start

# Download
huggingface-cli download olamide226/ofin-model ofin-model.gguf

# Run (standalone)
llama-cli -m ofin-model.gguf -p "How much notice must my employer give me after 3 years?" -n 256

# Or with the full Òfin stack
git clone https://github.com/olamide226/ofin.git
bash download_model.sh
make build && make ask Q="How much notice after 3 years?"

Model details

Field	Value
Base model	Llama 3.2 3B Instruct
Quantization	Q4_K_M (GGUF)
Size	1.88 GB
Context length	131,072 (native); 6,144 (Òfin app)
KV cache	f16 + flash attention
Runtime	llama.cpp only
Languages	English, Nigerian Pidgin (pcm)
Offline	Yes — zero network calls at runtime

Limitations (honest)

This model hallucinates Nigerian law when run standalone — it will invent section numbers and wrong notice bands. That's expected and by design. Òfin's full stack (8-act statutory corpus, hybrid retrieval, 3-layer citation verifier, deterministic rules engine) provides the legal accuracy. This baked GGUF provides the correct framing and language for standalone judge testing; the full system provides the correct answers.

Part of the Òfin system

Repo: github.com/olamide226/ofin
Submission: Africa Deep Tech Challenge 2026, corporate_enterprise domain
Team: Ruach Tech
Docs: PROGRESS.md · DECISIONS.md

Downloads last month: -

GGUF

Model size

3B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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Model tree for olamide226/ofin-model

Base model

meta-llama/Llama-3.2-3B-Instruct

Quantized

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Quantized

(4)

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