Instructions to use ZirTech/OmniMath-2B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ZirTech/OmniMath-2B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ZirTech/OmniMath-2B-GGUF",
	filename="OmniMath-2B-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 ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ZirTech/OmniMath-2B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/ZirTech/OmniMath-2B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use ZirTech/OmniMath-2B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ZirTech/OmniMath-2B-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": "ZirTech/OmniMath-2B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ZirTech/OmniMath-2B-GGUF:Q4_K_M

Ollama
How to use ZirTech/OmniMath-2B-GGUF with Ollama:
```
ollama run hf.co/ZirTech/OmniMath-2B-GGUF:Q4_K_M
```

Unsloth Studio

How to use ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-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 ZirTech/OmniMath-2B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ZirTech/OmniMath-2B-GGUF to start chatting

How to use ZirTech/OmniMath-2B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ZirTech/OmniMath-2B-GGUF:Q4_K_M

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": "ZirTech/OmniMath-2B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use ZirTech/OmniMath-2B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ZirTech/OmniMath-2B-GGUF:Q4_K_M

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 ZirTech/OmniMath-2B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use ZirTech/OmniMath-2B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ZirTech/OmniMath-2B-GGUF:Q4_K_M

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 "ZirTech/OmniMath-2B-GGUF:Q4_K_M" \
  --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 ZirTech/OmniMath-2B-GGUF with Docker Model Runner:
```
docker model run hf.co/ZirTech/OmniMath-2B-GGUF:Q4_K_M
```

Lemonade

How to use ZirTech/OmniMath-2B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ZirTech/OmniMath-2B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.OmniMath-2B-GGUF-Q4_K_M

List all available models

lemonade list

ZirTech commited on Apr 14

Commit

c6482c2

verified ·

1 Parent(s): cf3c8e0

Update README.md

Browse files

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README.md +32 -5

README.md CHANGED Viewed

@@ -1,5 +1,32 @@
----
-license: other
-license_name: ztech-license
-license_link: LICENSE
----

+---
+license: other
+license_name: ztech-license
+license_link: LICENSE
+language:
+- en
+pipeline_tag: text-generation
+---
+# OmniMath-2B - GGUF Quantized
+This repository contains **GGUF format quantizations** of the [OmniMath-2B](https://huggingface.co/ZirTech/OmniMath-2B) model, a 2-billion parameter language model specialized for mathematical reasoning.
+Original model: [ZirTech/OmniMath-2B](https://huggingface.co/ZirTech/OmniMath-2B)
+## Quantizations & File Sizes
+| Quantization | File Size | Description |
+|--------------|-----------|-------------|
+| **Q2_K**     | 969 MB    | 2-bit, smallest, lowest quality |
+| **Q3_K_S**   | 1.02 GB   | 3-bit, small |
+| **Q3_K_M**   | 1.10 GB   | 3-bit, medium |
+| **Q3_K_L**   | 1.16 GB   | 3-bit, large |
+| **IQ4_XS**   | 1.20 GB   | 4-bit integer with improved accuracy |
+| **Q4_K_S**   | 1.21 GB   | 4-bit, small |
+| **Q4_K_M**   | 1.27 GB   | 4-bit, medium (good balance) |
+| **Q5_K_S**   | 1.37 GB   | 5-bit, small |
+| **Q5_K_M**   | 1.41 GB   | 5-bit, medium |
+| **Q6_K**     | 1.56 GB   | 6-bit, high quality |
+| **Q8_0**     | 2.01 GB   | 8-bit, near‑original quality |
+| **F16**      | 3.78 GB   | 16-bit float (original weights) |